Upload folder using huggingface_hub
Browse files- .gitignore +174 -0
- LICENSE +21 -0
- README.md +139 -3
- dataset/channels.csv +247 -0
- dataset/split/test.txt +3063 -0
- dataset/split/train.txt +0 -0
- docs/clean.md +57 -0
- docs/crawl.md +141 -0
- docs/img/clean.png +3 -0
- docs/img/crawl.png +3 -0
- toolset/clean/ImageBind/test.py +147 -0
- toolset/clean/SenseVoice/check_voice.py +81 -0
- toolset/clean/requirements.txt +8 -0
- toolset/clean/silent/check_new_silent.py +69 -0
- toolset/clean/static/check_static_ffmpeg.py +121 -0
- toolset/crawl/channel/channel_analyzer.py +127 -0
- toolset/crawl/channel/get_channel_vids.py +80 -0
- toolset/crawl/channel/get_channels_vids.py +52 -0
- toolset/crawl/channel/get_test_list.py +79 -0
- toolset/crawl/core/__init__.py +1 -0
- toolset/crawl/core/build.py +43 -0
- toolset/crawl/core/channel.py +91 -0
- toolset/crawl/core/download/__init__.py +1 -0
- toolset/crawl/core/download/download_list.py +1073 -0
- toolset/crawl/core/filelist.py +164 -0
- toolset/crawl/core/filters/__init__.py +2 -0
- toolset/crawl/core/filters/filefilter.py +99 -0
- toolset/crawl/core/filters/ytfilter.py +58 -0
- toolset/crawl/core/search.py +153 -0
- toolset/crawl/download/download_list.py +27 -0
- toolset/crawl/download/download_list.sh +12 -0
- toolset/crawl/filter/filter_exist.py +72 -0
- toolset/crawl/requirements.txt +5 -0
- toolset/crawl/search/search.py +57 -0
- toolset/crawl/search/search.sh +19 -0
.gitignore
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| 1 |
+
# Byte-compiled / optimized / DLL files
|
| 2 |
+
__pycache__/
|
| 3 |
+
*.py[cod]
|
| 4 |
+
*$py.class
|
| 5 |
+
|
| 6 |
+
# C extensions
|
| 7 |
+
*.so
|
| 8 |
+
|
| 9 |
+
# Distribution / packaging
|
| 10 |
+
.Python
|
| 11 |
+
build/
|
| 12 |
+
develop-eggs/
|
| 13 |
+
dist/
|
| 14 |
+
downloads/
|
| 15 |
+
eggs/
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| 16 |
+
.eggs/
|
| 17 |
+
lib/
|
| 18 |
+
lib64/
|
| 19 |
+
parts/
|
| 20 |
+
sdist/
|
| 21 |
+
var/
|
| 22 |
+
wheels/
|
| 23 |
+
share/python-wheels/
|
| 24 |
+
*.egg-info/
|
| 25 |
+
.installed.cfg
|
| 26 |
+
*.egg
|
| 27 |
+
MANIFEST
|
| 28 |
+
|
| 29 |
+
# PyInstaller
|
| 30 |
+
# Usually these files are written by a python script from a template
|
| 31 |
+
# before PyInstaller builds the exe, so as to inject date/other infos into it.
|
| 32 |
+
*.manifest
|
| 33 |
+
*.spec
|
| 34 |
+
|
| 35 |
+
# Installer logs
|
| 36 |
+
pip-log.txt
|
| 37 |
+
pip-delete-this-directory.txt
|
| 38 |
+
|
| 39 |
+
# Unit test / coverage reports
|
| 40 |
+
htmlcov/
|
| 41 |
+
.tox/
|
| 42 |
+
.nox/
|
| 43 |
+
.coverage
|
| 44 |
+
.coverage.*
|
| 45 |
+
.cache
|
| 46 |
+
nosetests.xml
|
| 47 |
+
coverage.xml
|
| 48 |
+
*.cover
|
| 49 |
+
*.py,cover
|
| 50 |
+
.hypothesis/
|
| 51 |
+
.pytest_cache/
|
| 52 |
+
cover/
|
| 53 |
+
|
| 54 |
+
# Translations
|
| 55 |
+
*.mo
|
| 56 |
+
*.pot
|
| 57 |
+
|
| 58 |
+
# Django stuff:
|
| 59 |
+
*.log
|
| 60 |
+
local_settings.py
|
| 61 |
+
db.sqlite3
|
| 62 |
+
db.sqlite3-journal
|
| 63 |
+
|
| 64 |
+
# Flask stuff:
|
| 65 |
+
instance/
|
| 66 |
+
.webassets-cache
|
| 67 |
+
|
| 68 |
+
# Scrapy stuff:
|
| 69 |
+
.scrapy
|
| 70 |
+
|
| 71 |
+
# Sphinx documentation
|
| 72 |
+
docs/_build/
|
| 73 |
+
|
| 74 |
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# PyBuilder
|
| 75 |
+
.pybuilder/
|
| 76 |
+
target/
|
| 77 |
+
|
| 78 |
+
# Jupyter Notebook
|
| 79 |
+
.ipynb_checkpoints
|
| 80 |
+
|
| 81 |
+
# IPython
|
| 82 |
+
profile_default/
|
| 83 |
+
ipython_config.py
|
| 84 |
+
|
| 85 |
+
# pyenv
|
| 86 |
+
# For a library or package, you might want to ignore these files since the code is
|
| 87 |
+
# intended to run in multiple environments; otherwise, check them in:
|
| 88 |
+
# .python-version
|
| 89 |
+
|
| 90 |
+
# pipenv
|
| 91 |
+
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
|
| 92 |
+
# However, in case of collaboration, if having platform-specific dependencies or dependencies
|
| 93 |
+
# having no cross-platform support, pipenv may install dependencies that don't work, or not
|
| 94 |
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# install all needed dependencies.
|
| 95 |
+
#Pipfile.lock
|
| 96 |
+
|
| 97 |
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# UV
|
| 98 |
+
# Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control.
|
| 99 |
+
# This is especially recommended for binary packages to ensure reproducibility, and is more
|
| 100 |
+
# commonly ignored for libraries.
|
| 101 |
+
#uv.lock
|
| 102 |
+
|
| 103 |
+
# poetry
|
| 104 |
+
# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
|
| 105 |
+
# This is especially recommended for binary packages to ensure reproducibility, and is more
|
| 106 |
+
# commonly ignored for libraries.
|
| 107 |
+
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
|
| 108 |
+
#poetry.lock
|
| 109 |
+
|
| 110 |
+
# pdm
|
| 111 |
+
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
|
| 112 |
+
#pdm.lock
|
| 113 |
+
# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
|
| 114 |
+
# in version control.
|
| 115 |
+
# https://pdm.fming.dev/latest/usage/project/#working-with-version-control
|
| 116 |
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.pdm.toml
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| 117 |
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.pdm-python
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| 118 |
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.pdm-build/
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| 119 |
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| 120 |
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
|
| 121 |
+
__pypackages__/
|
| 122 |
+
|
| 123 |
+
# Celery stuff
|
| 124 |
+
celerybeat-schedule
|
| 125 |
+
celerybeat.pid
|
| 126 |
+
|
| 127 |
+
# SageMath parsed files
|
| 128 |
+
*.sage.py
|
| 129 |
+
|
| 130 |
+
# Environments
|
| 131 |
+
.env
|
| 132 |
+
.venv
|
| 133 |
+
env/
|
| 134 |
+
venv/
|
| 135 |
+
ENV/
|
| 136 |
+
env.bak/
|
| 137 |
+
venv.bak/
|
| 138 |
+
|
| 139 |
+
# Spyder project settings
|
| 140 |
+
.spyderproject
|
| 141 |
+
.spyproject
|
| 142 |
+
|
| 143 |
+
# Rope project settings
|
| 144 |
+
.ropeproject
|
| 145 |
+
|
| 146 |
+
# mkdocs documentation
|
| 147 |
+
/site
|
| 148 |
+
|
| 149 |
+
# mypy
|
| 150 |
+
.mypy_cache/
|
| 151 |
+
.dmypy.json
|
| 152 |
+
dmypy.json
|
| 153 |
+
|
| 154 |
+
# Pyre type checker
|
| 155 |
+
.pyre/
|
| 156 |
+
|
| 157 |
+
# pytype static type analyzer
|
| 158 |
+
.pytype/
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| 159 |
+
|
| 160 |
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# Cython debug symbols
|
| 161 |
+
cython_debug/
|
| 162 |
+
|
| 163 |
+
# PyCharm
|
| 164 |
+
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
|
| 165 |
+
# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
|
| 166 |
+
# and can be added to the global gitignore or merged into this file. For a more nuclear
|
| 167 |
+
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
|
| 168 |
+
#.idea/
|
| 169 |
+
|
| 170 |
+
# Ruff stuff:
|
| 171 |
+
.ruff_cache/
|
| 172 |
+
|
| 173 |
+
# PyPI configuration file
|
| 174 |
+
.pypirc
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LICENSE
ADDED
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| 1 |
+
MIT License
|
| 2 |
+
|
| 3 |
+
Copyright (c) 2025 Anonymous Authors
|
| 4 |
+
|
| 5 |
+
Permission is hereby granted, free of charge, to any person obtaining a copy
|
| 6 |
+
of this software and associated documentation files (the "Software"), to deal
|
| 7 |
+
in the Software without restriction, including without limitation the rights
|
| 8 |
+
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
|
| 9 |
+
copies of the Software, and to permit persons to whom the Software is
|
| 10 |
+
furnished to do so, subject to the following conditions:
|
| 11 |
+
|
| 12 |
+
The above copyright notice and this permission notice shall be included in all
|
| 13 |
+
copies or substantial portions of the Software.
|
| 14 |
+
|
| 15 |
+
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
| 16 |
+
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
| 17 |
+
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
|
| 18 |
+
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
| 19 |
+
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
|
| 20 |
+
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
|
| 21 |
+
SOFTWARE.
|
README.md
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| 1 |
+
# Sphere360
|
| 2 |
+
|
| 3 |
+
Sphere360 is a comprehensive dataset of paired 360-degree videos and spatial audio content sourced from YouTube. The collection contains over 103,000 matched 360-degree video and audio clips, representing a total of 288 hours of immersive content. This repository includes both the curated dataset and the essential web crawling and data processing tools used for its compilation.
|
| 4 |
+
|
| 5 |
+
|
| 6 |
+
|
| 7 |
+
|
| 8 |
+
- [Sphere360](#sphere360)
|
| 9 |
+
- [Copyright](#copyright)
|
| 10 |
+
- [Dataset Split](#dataset-split)
|
| 11 |
+
- [Toolset Environment](#toolset-environment)
|
| 12 |
+
- [Python Environment](#python-environment)
|
| 13 |
+
- [YouTube API](#youtube-api)
|
| 14 |
+
- [FFmpeg](#ffmpeg)
|
| 15 |
+
- [yt-dlp (Optional)](#yt-dlp-optional)
|
| 16 |
+
- [Data Crawling](#data-crawling)
|
| 17 |
+
- [Data Cleaning](#data-cleaning)
|
| 18 |
+
- [Acknowledgments](#acknowledgments)
|
| 19 |
+
- [Data Sources](#data-sources)
|
| 20 |
+
- [Data Cleaning Dependencies](#data-cleaning-dependencies)
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
|
| 24 |
+
|
| 25 |
+
## Copyright
|
| 26 |
+
|
| 27 |
+
The video data utilized in this study were sourced from the YouTube platform. All content is copyrighted by their respective creators and owners. The videos included in this research adhere to YouTube's terms of service and, where applicable, to Creative Commons licenses. Specifically, videos under the Creative Commons license have been appropriately attributed to the original authors in accordance with the license terms (CC BY 4.0).
|
| 28 |
+
|
| 29 |
+
For videos not governed by a Creative Commons license, we acknowledge that they are protected by copyright and are used exclusively for academic research purposes. No commercial use of these videos or content is intended. The use of these videos falls under the fair use doctrine for educational and research purposes, as permitted by copyright law.
|
| 30 |
+
|
| 31 |
+
All channel information contained in the dataset is recorded in `dataset/channels.csv`.
|
| 32 |
+
|
| 33 |
+
## Dataset Split
|
| 34 |
+
|
| 35 |
+
The dataset split configuration can be found in the `dataset/split` directory, containing:
|
| 36 |
+
|
| 37 |
+
- Training set: ~100.5k samples
|
| 38 |
+
- Test set: ~3k samples
|
| 39 |
+
- Each sample duration: 10 seconds
|
| 40 |
+
|
| 41 |
+
|
| 42 |
+
|
| 43 |
+
## Toolset Environment
|
| 44 |
+
|
| 45 |
+
#### Python Environment
|
| 46 |
+
|
| 47 |
+
**Data Crawling:**
|
| 48 |
+
|
| 49 |
+
- Python Version: 3.10
|
| 50 |
+
- Requirements: [toolset/crawl/requirements.txt](toolset/crawl/requirements.txt)
|
| 51 |
+
|
| 52 |
+
**Data Cleaning:**
|
| 53 |
+
|
| 54 |
+
- Python Version: 3.10
|
| 55 |
+
- Requirements: [toolset/clean/requirements.txt](toolset/clean/requirements.txt)
|
| 56 |
+
|
| 57 |
+
#### YouTube API
|
| 58 |
+
|
| 59 |
+
1. Apply for a [YouTube API](https://developers.google.com/youtube/v3/) Key from Google Cloud Console
|
| 60 |
+
2. Insert the obtained key into:
|
| 61 |
+
```python
|
| 62 |
+
# Location: toolset/crawl/core/build.py
|
| 63 |
+
__API_KEY = "YOUR_YOUTUBE_API_KEY_HERE" # Enter your YouTube API key here
|
| 64 |
+
```
|
| 65 |
+
|
| 66 |
+
#### FFmpeg
|
| 67 |
+
|
| 68 |
+
This project uses FFmpeg for audio/video data processing. Please configure the [FFmpeg](https://ffmpeg.org/) environment.
|
| 69 |
+
|
| 70 |
+
#### yt-dlp (Optional)
|
| 71 |
+
|
| 72 |
+
To use the download scripts provided in this repository, please configure the [yt-dlp](https://github.com/yt-dlp/yt-dlp/tree/master) environment.
|
| 73 |
+
|
| 74 |
+
|
| 75 |
+
|
| 76 |
+
## Data Crawling
|
| 77 |
+
|
| 78 |
+
|
| 79 |
+
|
| 80 |
+
The general workflow for data crawling is as follows:
|
| 81 |
+
|
| 82 |
+
+ Use formatted keywords for search, combining specific event labels (e.g. `firework`, `cat`, `waterfall`) with qualifying terms (e.g. `spatial audio 360`) to ensure class diversity and retrieve more 360° and FOA content
|
| 83 |
+
|
| 84 |
+
+ Implement two-stage data crawling:
|
| 85 |
+
|
| 86 |
+
+ **Stage 1: Channel-Based Crawling**
|
| 87 |
+
|
| 88 |
+
Use a large-scale approach to filter relevant channels. Detailed process:
|
| 89 |
+
|
| 90 |
+
+ Identify channels that appear in search results more than a specified threshold count
|
| 91 |
+
+ Sample and download from these channels, then perform quality verification (manually or using cleaning pipelines) to filter out high-quality channels from unusable ones
|
| 92 |
+
+ Obtain video lists from high-quality channels and proceed with downloading
|
| 93 |
+
|
| 94 |
+
+ **Stage 2: Video-Based Crawling**
|
| 95 |
+
|
| 96 |
+
+ Filter out videos from unusable channels in search results
|
| 97 |
+
+ Screen remaining videos (manually or using cleaning pipelines)
|
| 98 |
+
|
| 99 |
+
**For detailed workflow and script usage, please refer to [docs/crawl.md](docs/crawl.md).**
|
| 100 |
+
|
| 101 |
+
|
| 102 |
+
|
| 103 |
+
## Data Cleaning
|
| 104 |
+
|
| 105 |
+
|
| 106 |
+
|
| 107 |
+
The cleaning pipeline primarily consists of four dimensions:
|
| 108 |
+
|
| 109 |
+
- **Silent Filtering**: Filters out silent audio segments
|
| 110 |
+
- **Static Frame Filtering**: Removes static or nearly static videos
|
| 111 |
+
- **Audio-Visual Matching Filtering**: Eliminates videos with audio-visual mismatches (e.g., those containing background music, voiceovers, or post-production audio)
|
| 112 |
+
- **Voice Detection Filtering**: Filters out videos containing human speech
|
| 113 |
+
|
| 114 |
+
**For detailed workflow and script usage, please refer to [docs/clean.md](docs/clean.md).**
|
| 115 |
+
|
| 116 |
+
|
| 117 |
+
|
| 118 |
+
## Acknowledgments
|
| 119 |
+
|
| 120 |
+
This project is built upon the following resources and open-source projects:
|
| 121 |
+
|
| 122 |
+
### Data Sources
|
| 123 |
+
- **[YouTube Data API v3](https://developers.google.com/youtube/v3/)**
|
| 124 |
+
|
| 125 |
+
Our project utilizes its end-to-end speech recognition model to achieve Voice Detection Filtering.
|
| 126 |
+
|
| 127 |
+
|
| 128 |
+
### Data Cleaning Dependencies
|
| 129 |
+
- **[ImageBind](https://github.com/facebookresearch/ImageBind)**
|
| 130 |
+
|
| 131 |
+
|
| 132 |
+
Our project employs its cross-modal alignment capability to implement the Audio-Visual Matching Filtering.
|
| 133 |
+
|
| 134 |
+
- **[SenseVoice](https://github.com/FunAudioLLM/SenseVoice)** (Replace with actual link)
|
| 135 |
+
|
| 136 |
+
An advanced speech understanding toolkit, licensed under **[License Type]** (e.g., Apache 2.0).
|
| 137 |
+
|
| 138 |
+
Its end-to-end speech recognition model was instrumental in generating textual metadata for this project.
|
| 139 |
+
|
dataset/channels.csv
ADDED
|
@@ -0,0 +1,247 @@
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|
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|
|
|
| 1 |
+
channel_id
|
| 2 |
+
UC-0V6BpzC8qRrUEQTfZCWhg
|
| 3 |
+
UC-0Vhl624BIiNgMLSNHXdiQ
|
| 4 |
+
UC-H1n8_mJSNRJU6QyA-lysw
|
| 5 |
+
UC-JmtmWgYvtFCcDqyA6xoFw
|
| 6 |
+
UC-KyB39XyC6hVMOuN6NMcPw
|
| 7 |
+
UC-_mMEFh_62Wur7Zls67eOQ
|
| 8 |
+
UC-i5I5VmwsAF_oRKtsDpyLQ
|
| 9 |
+
UC-tXYTUZP7XW_0H95g04ECw
|
| 10 |
+
UC-vzk2hnTGHQatH7MSHwetw
|
| 11 |
+
UC02kV4SC13MtoadGB1QUIgQ
|
| 12 |
+
UC0LKzPzCaxEWJ6JzRsXWIYw
|
| 13 |
+
UC0pXAJNXLm0VkOWVr2m-dcQ
|
| 14 |
+
UC1DZnVaxNgNjRep8Vswqh-Q
|
| 15 |
+
UC1HX8DWEmVTWj5WNaLd1a_Q
|
| 16 |
+
UC1I_lLzVbMYNm0JBWJ2g-NA
|
| 17 |
+
UC2GDAXqAxMNtUMjwkvd_aRA
|
| 18 |
+
UC2kKD5FrPHGLaFo8T3rRl3Q
|
| 19 |
+
UC2n363potl9XmBbkrhkF9nA
|
| 20 |
+
UC2sojyHvA7RWfaQmRw3FSZQ
|
| 21 |
+
UC36a8bZhRwV2XVpB79oRjeg
|
| 22 |
+
UC3AAkmimqkNA0RiwBMPVXyg
|
| 23 |
+
UC3FfjxGHd2oghObfnORWatg
|
| 24 |
+
UC3Nt-50NEWzH6R1ovbtIrGA
|
| 25 |
+
UC45t78-1NUPa8SiAjf6hluw
|
| 26 |
+
UC49Gd9W9yphYWa-MWwtPe2A
|
| 27 |
+
UC4A3dgWtWNk7RHt2T7cCWbw
|
| 28 |
+
UC4WCmUAQWXiZOdR3LuQbVxw
|
| 29 |
+
UC4adL1ao1n49oRV5K28sOjA
|
| 30 |
+
UC5nGc3TtgRxukjPlHc1v9Fg
|
| 31 |
+
UC5stUbrIlkm5UTMPgVm2dsg
|
| 32 |
+
UC6B7o6snb1gtczzLsC1ZVMw
|
| 33 |
+
UC6NkTCJimTbM1KKCHkpL4uw
|
| 34 |
+
UC6_696Vph-306CVsenXvbvQ
|
| 35 |
+
UC7wzycNHhEL85fk2QlAtTrw
|
| 36 |
+
UC86zaFXqv993RLbR1w_LJSQ
|
| 37 |
+
UC8KSiJmfPQ0HasbHRNyyXWQ
|
| 38 |
+
UC8OHmFHOZW3krsDWdvcjuKQ
|
| 39 |
+
UC9-cU0_3nV5LvYCj7dI-fqA
|
| 40 |
+
UC9S1bbeiuKN_BeZLJ-VNu_Q
|
| 41 |
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UCA8m3PAK3BvUNR3cZHZ4oKg
|
| 42 |
+
UCALKj3WMatLxhtMtwcjUutQ
|
| 43 |
+
UCAeZgseUaAmIAyHOg1Yx-6g
|
| 44 |
+
UCB2CFRLQ4qC37-5JebM13VQ
|
| 45 |
+
UCB54hjznJECeluoAI5TsGpQ
|
| 46 |
+
UCBpWTx0VlXYZsMul4Mp9EuQ
|
| 47 |
+
UCBrC3IijY8Rn3VhsDNAc7Zg
|
| 48 |
+
UCC4MmGA_F2RlraxHdVCRNmw
|
| 49 |
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UCCMzuoJS4OXjy35Zah0txuA
|
| 50 |
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UCCgQes9d7seWAeNbhC8Tidg
|
| 51 |
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UCCmfZuv1KR-WpKt6s-FJPmQ
|
| 52 |
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UCCr3yFFXHDFDYzM0Gm08zjA
|
| 53 |
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UCCtj8-RJGZiv4K9NuBOO8Kg
|
| 54 |
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UCD1Em4q90ZUK2R5HKesszJg
|
| 55 |
+
UCD7_UQQs4a3k7nxSqDBzhxA
|
| 56 |
+
UCDEFYX06AvP54D_F-HHbgkg
|
| 57 |
+
UCDZbkPxlQuESBFq38u7kaYA
|
| 58 |
+
UCDsaUsbzJgNJ-zLJp3kluxA
|
| 59 |
+
UCE9vXEImVsVuCzKy-WJJu1A
|
| 60 |
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UCEf15bpur2w969lnPkzY3VQ
|
| 61 |
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UCEjkWMLZWz4rDsp-ahHLmjA
|
| 62 |
+
UCEnFPoPWMEXLPX-GZfX5Umw
|
| 63 |
+
UCFJFUjH4EwdmH7OVfzcy22g
|
| 64 |
+
UCFRU-wmA7HwqkOjrX9j4H6g
|
| 65 |
+
UCF_NASwEEfS2dvBfExBiLgQ
|
| 66 |
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UCG3uX7cQOfNP4BHLAd4GFEw
|
| 67 |
+
UCGALpeOi9Cu5ypGoOM3KY5g
|
| 68 |
+
UCGT4mjOPgaPjtEHayBJY79A
|
| 69 |
+
UCGj7vE2XblTLSp06F0KCQmQ
|
| 70 |
+
UCGnOZEnI03LLOrrdPZKfnTw
|
| 71 |
+
UCGsc3rEP5QxgDmiwN1syqig
|
| 72 |
+
UCGt20xKaE_37kQPVE5xhf4w
|
| 73 |
+
UCGzbiQGtI4f-S6hE3MLR9dg
|
| 74 |
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UCHYJ8f6Otp0NaefHWxSiq1Q
|
| 75 |
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UCIAwOlQqN7Z-ss6XF3qfPrQ
|
| 76 |
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UCIZ9sXrDrWwB40U0Zg2zA7g
|
| 77 |
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UCIblnJ0mWIZ4QHJaB1p-BLg
|
| 78 |
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UCIegeCgzFPOZhiYRn4L-gbQ
|
| 79 |
+
UCIzpdYS-tlHY8wHdpetqt8g
|
| 80 |
+
UCJ7vjf6yFJGv9jIiEXKIXJA
|
| 81 |
+
UCJ84fTiF5ppiEUmdJKMgwGQ
|
| 82 |
+
UCJJNCcGSG8xEe8RbVBmLd2Q
|
| 83 |
+
UCK9qLJvm6X9ACmDI8c6_xQA
|
| 84 |
+
UCKgVX-k42818DA6UiYyXLQQ
|
| 85 |
+
UCKkc9WmQrarYY7hIZv_43eA
|
| 86 |
+
UCLC5ZvdgBMfPINC57QJXnkQ
|
| 87 |
+
UCLNGrXFInRUehzwskSCTfrA
|
| 88 |
+
UCLSzi_703BpBS1Pv6XweiHQ
|
| 89 |
+
UCLl46BWTrgkmiXPWWe9fJrg
|
| 90 |
+
UCLpIDPp8Z0JBmYJJ2Jc-L0w
|
| 91 |
+
UCLvwyjVJ2Tr025oaN_MQTpQ
|
| 92 |
+
UCMd3dW1_hrpLODFB4wOI31A
|
| 93 |
+
UCN027-rS7Z7QmmR336HJA1Q
|
| 94 |
+
UCNNFrjzLIVOBzULaggXGDxw
|
| 95 |
+
UCOLvC1S6fSuaYZ2-Vy8_DEQ
|
| 96 |
+
UCQ7y9s6AiXdAvFQ6ws-bMCg
|
| 97 |
+
UCQVuV2rIkpzU3E60YuyWquA
|
| 98 |
+
UCQqhBPYwK01P9hp41hRdkdA
|
| 99 |
+
UCQyej2QC2_-ARo7eYehDoNw
|
| 100 |
+
UCRAXFP7Ha4_pxmANlPvo-Vg
|
| 101 |
+
UCSGy58gvmU7EclBrTjZo_kQ
|
| 102 |
+
UCSQSRHSMjJthdtNpHuuoFIw
|
| 103 |
+
UCSYCauuVNgyRQZ6_DNFGUSQ
|
| 104 |
+
UCSruQoGkqd7C55KP2cHeL5g
|
| 105 |
+
UCT-AHMyQGneK3u_VvnYB6JQ
|
| 106 |
+
UCT7_0KK0x3M5cep_idJbkTA
|
| 107 |
+
UCTkX5coSMfkjf-QTFr36bRg
|
| 108 |
+
UCU2XevOWA1IkxF3Xaw-acTg
|
| 109 |
+
UCU6pwlIPjpKK3ADt822u4yQ
|
| 110 |
+
UCU8jFCZLbp-pqLfgsNwF_7w
|
| 111 |
+
UCUVQBSQ4JaPENX5qXb-jMmA
|
| 112 |
+
UCUyWFR-faejrl4Ss5gkt5GA
|
| 113 |
+
UCUzJ4K-4QQYEHlUbnHkZSdA
|
| 114 |
+
UCV5Rj2FZ8L2Rwrl4HrqveqQ
|
| 115 |
+
UCV7VA54Bix5uNwHVkKTZwUg
|
| 116 |
+
UCV7zYe2HkgQAz0wuC6_BXkg
|
| 117 |
+
UCVosJQqnTScwwtBGq_KnEUA
|
| 118 |
+
UCVv3JBile7OCTU9mSGGNqdA
|
| 119 |
+
UCVydZvHpPbYZ0bisPgVll0A
|
| 120 |
+
UCWGQ4MffFyjAh6S5ZVZaFNg
|
| 121 |
+
UCWIUwxGNbhMjAA5I-c-wLdg
|
| 122 |
+
UCWZfaG02u0MNog4MVP_JxoQ
|
| 123 |
+
UCWpZYZv6Nv3BMVL1lux0UAw
|
| 124 |
+
UCWuLzj3_RljzsY2zHGABu6g
|
| 125 |
+
UCXXlojbBdfF60U_ILu6oLoA
|
| 126 |
+
UCXz1Pr5-y8XSEUiEQv8v-ag
|
| 127 |
+
UCYIMb8o8mazHmVjxTsHv9ug
|
| 128 |
+
UCYWISqscop1eMKcxADf_okQ
|
| 129 |
+
UCYcjlfmQkqrwFmYdUG-kwqg
|
| 130 |
+
UCYideORuJs4pgx3LJTLEQQQ
|
| 131 |
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UCYzzY8r36QIYmnDGg5c-54w
|
| 132 |
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UCZCDzlWGXZCai8y8Z-2Oi7g
|
| 133 |
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UCZF5M7nl3AilyG-9Gbx1OFg
|
| 134 |
+
UCZOAMSMPtGMD524xeVLdZ_w
|
| 135 |
+
UCZkjyM_8fvadBtDVZggN-gA
|
| 136 |
+
UCZtbc7OlDAY56ZT6Fh7Bwhw
|
| 137 |
+
UCZxmrNsN5Vo05oNNvyzoByQ
|
| 138 |
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UC_bKhergk63u0pQ85tBIdVQ
|
| 139 |
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UC_zlYlSb3aHcYH5UmAZPrSg
|
| 140 |
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UCaKLpauH3hH7vMjt1cbPtUw
|
| 141 |
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UCaMbNKU_piTrmhHm-Ux3w1w
|
| 142 |
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UCabfiEzAwNHfShgmt2Y--Yw
|
| 143 |
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UCatg8cgQfntfjhGDVvB1CcQ
|
| 144 |
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UCb6Jvgc9qW0sE4puekJb8EA
|
| 145 |
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UCbJnRkk3Pl8FsCn1sRFRP5A
|
| 146 |
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UCbLvqEItBO_cSUJrAGnZDUg
|
| 147 |
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UCbNrSYar86ZP4f7k9DoF8BQ
|
| 148 |
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UCblOcVvO-1X-iaeyv8nT34Q
|
| 149 |
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UCc8mYQRLXaQIizk7M_NVXyw
|
| 150 |
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UCcGpVGB7p8pcpuyVXFLxQhg
|
| 151 |
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UCcLeiuZ_bPJeoTuKUiVtApQ
|
| 152 |
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UCcftblae5aEnraa34d1FPQg
|
| 153 |
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UCd0Yn5SKGaujdXCwk2TwmoA
|
| 154 |
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UCd36LBcHwLrAbNH30SxSDSA
|
| 155 |
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UCdZvc25NNcNLHd6IAUwmhKA
|
| 156 |
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UCdc0AuchHvvQH5Q2ZhPKS4Q
|
| 157 |
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UCdtk0XZd9cp3ZDr9b1Yh4rA
|
| 158 |
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UCeCpCTOdQSCQHVc_0b_KDxw
|
| 159 |
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UCeEqIv7lVwOOLnwxuuhQFuQ
|
| 160 |
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UCeNdmyaAJfxk7Ut0q2mwEYA
|
| 161 |
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UCelfK7CInt-Sm6VPQFtMnMQ
|
| 162 |
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UCf4_ArJPd3vT2FmErBbEcUA
|
| 163 |
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UCfIXdjDQH9Fau7y99_Orpjw
|
| 164 |
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UCfOA_P5G1KfzCs2NK2Jbgtw
|
| 165 |
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UCfSRqWaFCso_YfSJDmX57SA
|
| 166 |
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UCfc9B9Xf31nOsrlU8KHSVlQ
|
| 167 |
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UCfuTEc4aUK9v_m9PFN1qdXA
|
| 168 |
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UCfxxwjehaooC3LBpoMVTLqg
|
| 169 |
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UCg9X0uS63L4_z1M2ggMgOeg
|
| 170 |
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UCgH3ODZVQQNv8SD774ApLOQ
|
| 171 |
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UCgQx6leIwS_OuXVcRJyhaGA
|
| 172 |
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UCgYaFZrthF3DwzT2uI5w7dg
|
| 173 |
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UCgdLokRl-xkPuEAI71IKrJw
|
| 174 |
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UCh1HH2c8bidZ_jWovXV0yYg
|
| 175 |
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UCh3mGydGhqSqPGsa68tj73g
|
| 176 |
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UChY1e-jzmr8usmOmcUZO-mw
|
| 177 |
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UCiVHWCnex0BVxOH0Xku1rVg
|
| 178 |
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UCiXjkefMyLGOzDybniQFFpg
|
| 179 |
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UCiegRCalBotJFtQPRSfw4YQ
|
| 180 |
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UCisNZz9PNzeu5oNFeVHbKTA
|
| 181 |
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UCjDU4xfJAmqLQzg-w8wdFQA
|
| 182 |
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UCjL2kNSzxjyw9elGrdbdmaA
|
| 183 |
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UCjTzS-dtYS1wX-0LGdgZnWA
|
| 184 |
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UCjXuZhd12PHlLWx2AcQGZcA
|
| 185 |
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UCjlBVnMb-zhaTfAvMQDP9lQ
|
| 186 |
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UCjyi6by44TTH0j_U3vXEGpA
|
| 187 |
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UCk1Tx81B-jHRGRCU_YvO0gQ
|
| 188 |
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UCkJu9agRvoPmq3_bkgjJbxg
|
| 189 |
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UCkdjSBYWD9zN7ZrPVWFhLcg
|
| 190 |
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UCkgFfGKT-1wI8FuMuGjh0kQ
|
| 191 |
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UCkxbmufzXVf68d6hrsX0NeA
|
| 192 |
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UCl9LJTi8CtX8iFsdeLMwq-A
|
| 193 |
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UClJqI_j5qpgyUcq1VpK_DlQ
|
| 194 |
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UCld6ez7tPz_q4HEsOVIB2Bg
|
| 195 |
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UClr4KQSHx2lSuDtmQE56a8A
|
| 196 |
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UClweSIcLYVqzHW-2OTfr-3A
|
| 197 |
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UCmEOWndZDS5FMxUxGtlLhww
|
| 198 |
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UCmIgKn7CF8frAV5wdFs2AwQ
|
| 199 |
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UCmalWOci_SK9IetBfbeRgsA
|
| 200 |
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UCmvYXGfm1n4vtDtBLaeQwrw
|
| 201 |
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UCn-c-is8vErEPM-1r78-1IQ
|
| 202 |
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UCnES4PHruL_MxebogC_zGzA
|
| 203 |
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UCnVgAu4qIQG10Tg8FvxxD6g
|
| 204 |
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UCnfmo4KkHHRDYOhyw9TMPRw
|
| 205 |
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UCoMBHqM1_Pmd3YHild1YGlg
|
| 206 |
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UCoUkd3WYKgJUOaV_yVLv6Ug
|
| 207 |
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UCofYNEXHHVylft1xnNVJqmg
|
| 208 |
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UCpNYbE8StrKO-Fuu3jVmDRQ
|
| 209 |
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UCpkGFv7mqFVQqeHMQxZKlVQ
|
| 210 |
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UCpnuaGaAwLXUOYJc6q1zMsA
|
| 211 |
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UCqD2-9aE3WUvZNxBgf9E1Tw
|
| 212 |
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UCqJT2LVdpv1upluJegKADZw
|
| 213 |
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UCqp_emcvW1P27C7EqpnyV3Q
|
| 214 |
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UCqzV52cyTydo2E2x_LfvuYg
|
| 215 |
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UCrOpWTY2sbByAh8lOZSIJMg
|
| 216 |
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UCrX4UaYW0aF7P7WfbueXFVg
|
| 217 |
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UCrejptoJXkmw7TXxMgYuHNg
|
| 218 |
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UCrsVUOmLa3HfFvf7WKAZGCA
|
| 219 |
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UCsc4mwD4ha_OVzx7g-K6JFg
|
| 220 |
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UCspjXHQpri5a8bD9k3nNDdQ
|
| 221 |
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UCssg2PIQaacJK6vMaxjFypQ
|
| 222 |
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UCtDjizhBtoLXLHq48n7_Gmw
|
| 223 |
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UCtMlWVnP_ozMciD1ZE4i91g
|
| 224 |
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UCtVaEEdhsSt1K6OkXwHDWBg
|
| 225 |
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UCukH8wisjTfKfpi90knuRaA
|
| 226 |
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UCuwJia_kBt7CenzQa_mr70w
|
| 227 |
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UCvAWkeQUlVeEOwIowFlBI8Q
|
| 228 |
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UCvmqU5FdkZ_F5Eml_cZKfvw
|
| 229 |
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UCvshAbYgugPEG6aYAA1jEVg
|
| 230 |
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UCvvzTkszo5eVo9hdf-6hPHg
|
| 231 |
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UCvw3ecEpQzbojYEWz12bypw
|
| 232 |
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UCwb-o8JMje-IIRDuwPII8Vw
|
| 233 |
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UCwl0S6vpeLjAr1q7d--I3EA
|
| 234 |
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UCwmZiChSryoWQCZMIQezgTg
|
| 235 |
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UCwx0Aw3cmECMNBGCNckRgIg
|
| 236 |
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UCx3G55dhoS-nCypRTc22aOQ
|
| 237 |
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UCxI2tF0qHfgZrY2861Z1NpQ
|
| 238 |
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UCxXMlvodTtcT_eO5DQKb4PQ
|
| 239 |
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UCxw58f9l5fgyQzyTtmk4k6A
|
| 240 |
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UCydwHbFRpLghukV7671QjBg
|
| 241 |
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UCypI2Z4z-s5ic7IH3Vom-uA
|
| 242 |
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UCys3xtL8VEUb_36e210_4Nw
|
| 243 |
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UCzYgb2oC7ILtxWzk_uHsXAg
|
| 244 |
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UCz_8H553XHFTJQjUtMoy_Ig
|
| 245 |
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UCzks_AeKg9G0SpFwdPyqK9Q
|
| 246 |
+
UCzo3y2unXfuTcVfCgpMoRXA
|
| 247 |
+
UCztKHDTCyuhGDkEn9EXhczw
|
dataset/split/test.txt
ADDED
|
@@ -0,0 +1,3063 @@
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| 1 |
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530swnPWJrQ_17
|
| 2 |
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7ZVYcIsEeHo_130
|
| 3 |
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RpNrYMA2y6c_110
|
| 4 |
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|
| 5 |
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u-Hpf2_wzB8_390
|
| 6 |
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glZ5cH82ycE_210
|
| 7 |
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p5Ady9RJyhU_90
|
| 8 |
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530swnPWJrQ_5
|
| 9 |
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CXeKld-Irmk_69
|
| 10 |
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Y7YBDESILgY_334
|
| 11 |
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grWuEPQKFAs_140
|
| 12 |
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fQukntBmFvY_240
|
| 13 |
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|
| 14 |
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0FB9jMXMP8A_0
|
| 15 |
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| 16 |
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|
| 17 |
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|
| 18 |
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fciO6_q2wk4_210
|
| 19 |
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tmO6N6TBXoE_95
|
| 20 |
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Wc_gzO9i38k_206
|
| 21 |
+
UG3nqEzgq00_380
|
| 22 |
+
fhuwLnHsH5U_744
|
| 23 |
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bA_7toCijrk_18
|
| 24 |
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9X2wM6HD_og_1022
|
| 25 |
+
glZ5cH82ycE_600
|
| 26 |
+
samc7Y4r3fg_879
|
| 27 |
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u-Hpf2_wzB8_90
|
| 28 |
+
RH5K2P6pH9Y_780
|
| 29 |
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6DHUZ1Jt4wo_10
|
| 30 |
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CBMUhxJC6TU_250
|
| 31 |
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|
| 32 |
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WZ2zz4TfGvA_315
|
| 33 |
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fQukntBmFvY_10
|
| 34 |
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|
| 35 |
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QO-pWw4_z8Y_50
|
| 36 |
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AaculwvmaTA_1971
|
| 37 |
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6DHUZ1Jt4wo_1490
|
| 38 |
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WU6WFEyfeH4_460
|
| 39 |
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hSbaRwmJ5AA_1302
|
| 40 |
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pxf-4iLOUVA_1101
|
| 41 |
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zK3mQlK9ZVo_70
|
| 42 |
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RpNrYMA2y6c_680
|
| 43 |
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UfGDEXV2F60_161
|
| 44 |
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dQaNzwqCUAA_291
|
| 45 |
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hSbaRwmJ5AA_214
|
| 46 |
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RbFEpkuFCjI_176
|
| 47 |
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7ZVYcIsEeHo_170
|
| 48 |
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aIQnFp5sSc8_307
|
| 49 |
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glZ5cH82ycE_110
|
| 50 |
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grWuEPQKFAs_130
|
| 51 |
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VQAGxC8mSzA_27
|
| 52 |
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Wc_gzO9i38k_152
|
| 53 |
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kSyessjQYeA_605
|
| 54 |
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oOLW1t9vpVQ_470
|
| 55 |
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WU6WFEyfeH4_660
|
| 56 |
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fhuwLnHsH5U_216
|
| 57 |
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Pz4HjQhZDmk_277
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| 58 |
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| 59 |
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RpNrYMA2y6c_240
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| 60 |
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qWpImMW4DHI_1619
|
| 61 |
+
RpNrYMA2y6c_690
|
| 62 |
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tOJ6CGr-iho_200
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| 63 |
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fhuwLnHsH5U_1340
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| 64 |
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LQrZLRdjqww_220
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| 65 |
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91jpE2P8SPM_35
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yhFN_xVmNsI_50
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6DHUZ1Jt4wo_1440
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hm65SlpTXZo_90
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grWuEPQKFAs_30
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1WFJLucjK50_692
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qvtEdv1WlUw_360
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kSyessjQYeA_1722
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1WFJLucjK50_529
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RH5K2P6pH9Y_300
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tt02LzCbIcU_110
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GmtUEtUCX8o_347
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7ZVYcIsEeHo_100
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fhuwLnHsH5U_1385
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fhuwLnHsH5U_835
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qWpImMW4DHI_1787
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aieThfuvmtY_6
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6DHUZ1Jt4wo_890
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CBMUhxJC6TU_30
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dQaNzwqCUAA_47
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n91RZ57a3mI_890
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Y7YBDESILgY_2837
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lOJBGAd0mSw_220
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tmO6N6TBXoE_161
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SCiA9KmQIEw_20
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u-Hpf2_wzB8_330
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GmtUEtUCX8o_953
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GmtUEtUCX8o_241
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hSbaRwmJ5AA_1959
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| 408 |
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aM9v-6LKKhE_960
|
| 409 |
+
LSeJeKHsUkw_98
|
| 410 |
+
6DHUZ1Jt4wo_1130
|
| 411 |
+
hSbaRwmJ5AA_1704
|
| 412 |
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UG3nqEzgq00_550
|
| 413 |
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dQaNzwqCUAA_301
|
| 414 |
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glZ5cH82ycE_150
|
| 415 |
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WU6WFEyfeH4_30
|
| 416 |
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Wc_gzO9i38k_228
|
| 417 |
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yhFN_xVmNsI_110
|
| 418 |
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pxf-4iLOUVA_951
|
| 419 |
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KVvDejzzQjM_24
|
| 420 |
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bul6AM9JaDQ_421
|
| 421 |
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yhFN_xVmNsI_10
|
| 422 |
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GGTOvP9OaXI_80
|
| 423 |
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vPOh8bauanA_13
|
| 424 |
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yhFN_xVmNsI_400
|
| 425 |
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oOLW1t9vpVQ_550
|
| 426 |
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OWN_J9FGZ5I_346
|
| 427 |
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hSbaRwmJ5AA_2138
|
| 428 |
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yhFN_xVmNsI_550
|
| 429 |
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Eeg_WJTTRX0_150
|
| 430 |
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Eeg_WJTTRX0_180
|
| 431 |
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7ZVYcIsEeHo_150
|
| 432 |
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hSbaRwmJ5AA_2814
|
| 433 |
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fciO6_q2wk4_40
|
| 434 |
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xiPfXsNhgIc_140
|
| 435 |
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lRiyTbH0D24_250
|
| 436 |
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hSbaRwmJ5AA_1762
|
| 437 |
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_74aGilhTGU_2799
|
| 438 |
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6DHUZ1Jt4wo_520
|
| 439 |
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7ZVYcIsEeHo_330
|
| 440 |
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Eeg_WJTTRX0_270
|
| 441 |
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RH5K2P6pH9Y_40
|
| 442 |
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WQzEsz-lfIc_650
|
| 443 |
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LQrZLRdjqww_50
|
| 444 |
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oOLW1t9vpVQ_260
|
| 445 |
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HiaNsIscHPY_110
|
| 446 |
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dQaNzwqCUAA_229
|
| 447 |
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PVQiHhIVa48_297
|
| 448 |
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aieThfuvmtY_386
|
| 449 |
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hSbaRwmJ5AA_1905
|
| 450 |
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RH5K2P6pH9Y_370
|
| 451 |
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hSbaRwmJ5AA_1923
|
| 452 |
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aM9v-6LKKhE_490
|
| 453 |
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GmtUEtUCX8o_70
|
| 454 |
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CBMUhxJC6TU_460
|
| 455 |
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GmtUEtUCX8o_82
|
| 456 |
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CBMUhxJC6TU_380
|
| 457 |
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OLBCzxzvBZM_49
|
| 458 |
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u-Hpf2_wzB8_420
|
| 459 |
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7ZVYcIsEeHo_40
|
| 460 |
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aieThfuvmtY_294
|
| 461 |
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lRiyTbH0D24_170
|
| 462 |
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yhFN_xVmNsI_30
|
| 463 |
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RH5K2P6pH9Y_640
|
| 464 |
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uuzlaAPBXYs_344
|
| 465 |
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_74aGilhTGU_1767
|
| 466 |
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9X2wM6HD_og_736
|
| 467 |
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RbDBfWg_6QU_196
|
| 468 |
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91jpE2P8SPM_127
|
| 469 |
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pxf-4iLOUVA_1654
|
| 470 |
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TETd0Q2wnbY_257
|
| 471 |
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AaculwvmaTA_491
|
| 472 |
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VvXNTF68hdE_240
|
| 473 |
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rYKxKYUBcjo_159
|
| 474 |
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_74aGilhTGU_2843
|
| 475 |
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pC2WmY6bkB4_251
|
| 476 |
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fhuwLnHsH5U_588
|
| 477 |
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5WrI-nS59kA_410
|
| 478 |
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kSyessjQYeA_1362
|
| 479 |
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_74aGilhTGU_3388
|
| 480 |
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UG3nqEzgq00_40
|
| 481 |
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bGnivk-jepU_159
|
| 482 |
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aM9v-6LKKhE_720
|
| 483 |
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qWpImMW4DHI_2213
|
| 484 |
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b6L0bCePL0c_210
|
| 485 |
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oOLW1t9vpVQ_460
|
| 486 |
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kSyessjQYeA_585
|
| 487 |
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hSbaRwmJ5AA_2709
|
| 488 |
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b6L0bCePL0c_270
|
| 489 |
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6DHUZ1Jt4wo_300
|
| 490 |
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JxMFgRCZuo0_130
|
| 491 |
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aIQnFp5sSc8_48
|
| 492 |
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aieThfuvmtY_627
|
| 493 |
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lRiyTbH0D24_110
|
| 494 |
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qWpImMW4DHI_909
|
| 495 |
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fciO6_q2wk4_170
|
| 496 |
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GGTOvP9OaXI_30
|
| 497 |
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eqn9IX4aKmc_409
|
| 498 |
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P72n97ONayA_30
|
| 499 |
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RH5K2P6pH9Y_730
|
| 500 |
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RpNrYMA2y6c_350
|
| 501 |
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hSbaRwmJ5AA_675
|
| 502 |
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1whJPpizoDA_238
|
| 503 |
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XiPamwUKnEo_48
|
| 504 |
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aieThfuvmtY_406
|
| 505 |
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_74aGilhTGU_3265
|
| 506 |
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Fq8kqMmSl-c_320
|
| 507 |
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Fq8kqMmSl-c_70
|
| 508 |
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J2PYwi8fy-M_48
|
| 509 |
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6DHUZ1Jt4wo_510
|
| 510 |
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glZ5cH82ycE_240
|
| 511 |
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hX1dECWoEoc_21
|
| 512 |
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OWN_J9FGZ5I_100
|
| 513 |
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TETd0Q2wnbY_131
|
| 514 |
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qWpImMW4DHI_1441
|
| 515 |
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Fq8kqMmSl-c_410
|
| 516 |
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RbFEpkuFCjI_319
|
| 517 |
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yhFN_xVmNsI_320
|
| 518 |
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SCiA9KmQIEw_140
|
| 519 |
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RbFEpkuFCjI_378
|
| 520 |
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_74aGilhTGU_2744
|
| 521 |
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7ZVYcIsEeHo_370
|
| 522 |
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samc7Y4r3fg_2227
|
| 523 |
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hSbaRwmJ5AA_1749
|
| 524 |
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HiaNsIscHPY_220
|
| 525 |
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lz4TkjaNVPY_94
|
| 526 |
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RH5K2P6pH9Y_510
|
| 527 |
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L2Tv5v__9m4_107
|
| 528 |
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_74aGilhTGU_3168
|
| 529 |
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hX1dECWoEoc_41
|
| 530 |
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UG3nqEzgq00_520
|
| 531 |
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CBMUhxJC6TU_450
|
| 532 |
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QqMf0qWsCYM_187
|
| 533 |
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q2DXQeG55N0_170
|
| 534 |
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AyVtAJzOJlE_783
|
| 535 |
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yhFN_xVmNsI_140
|
| 536 |
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yhFN_xVmNsI_250
|
| 537 |
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eqn9IX4aKmc_509
|
| 538 |
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7ZVYcIsEeHo_350
|
| 539 |
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zK3mQlK9ZVo_40
|
| 540 |
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DGtWuPemYc4_360
|
| 541 |
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UG3nqEzgq00_400
|
| 542 |
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hSbaRwmJ5AA_1991
|
| 543 |
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qWpImMW4DHI_198
|
| 544 |
+
kSyessjQYeA_2160
|
| 545 |
+
zWkaEsCIg5Q_312
|
| 546 |
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Y8BLz-u0u7c_447
|
| 547 |
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_74aGilhTGU_1626
|
| 548 |
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Eeg_WJTTRX0_10
|
| 549 |
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AaculwvmaTA_2008
|
| 550 |
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qvtEdv1WlUw_380
|
| 551 |
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UG3nqEzgq00_640
|
| 552 |
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kSyessjQYeA_1332
|
| 553 |
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6DHUZ1Jt4wo_1370
|
| 554 |
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RH5K2P6pH9Y_410
|
| 555 |
+
fhuwLnHsH5U_722
|
| 556 |
+
UG3nqEzgq00_700
|
| 557 |
+
bul6AM9JaDQ_541
|
| 558 |
+
RH5K2P6pH9Y_170
|
| 559 |
+
j2PE0mccihM_22
|
| 560 |
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hSbaRwmJ5AA_1647
|
| 561 |
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V8UBNttMWJo_55
|
| 562 |
+
qWpImMW4DHI_1535
|
| 563 |
+
fciO6_q2wk4_50
|
| 564 |
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Eeg_WJTTRX0_70
|
| 565 |
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kSyessjQYeA_1846
|
| 566 |
+
MHjYjOXxx-E_300
|
| 567 |
+
aieThfuvmtY_1381
|
| 568 |
+
nDu57CGqbLM_28
|
| 569 |
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9X2wM6HD_og_272
|
| 570 |
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Y8BLz-u0u7c_121
|
| 571 |
+
-3GumCmyAIk_301
|
| 572 |
+
samc7Y4r3fg_23
|
| 573 |
+
eqn9IX4aKmc_69
|
| 574 |
+
XiPamwUKnEo_222
|
| 575 |
+
SCiA9KmQIEw_150
|
| 576 |
+
aM9v-6LKKhE_180
|
| 577 |
+
bul6AM9JaDQ_114
|
| 578 |
+
zK3mQlK9ZVo_80
|
| 579 |
+
OLBCzxzvBZM_38
|
| 580 |
+
Fq8kqMmSl-c_270
|
| 581 |
+
UG3nqEzgq00_450
|
| 582 |
+
MHjYjOXxx-E_240
|
| 583 |
+
WU6WFEyfeH4_730
|
| 584 |
+
fhuwLnHsH5U_576
|
| 585 |
+
CBMUhxJC6TU_340
|
| 586 |
+
pxf-4iLOUVA_1018
|
| 587 |
+
aieThfuvmtY_396
|
| 588 |
+
93eAayq6GO0_90
|
| 589 |
+
WU6WFEyfeH4_350
|
| 590 |
+
Y7YBDESILgY_1023
|
| 591 |
+
LSeJeKHsUkw_71
|
| 592 |
+
hm65SlpTXZo_50
|
| 593 |
+
_74aGilhTGU_2071
|
| 594 |
+
pC2WmY6bkB4_590
|
| 595 |
+
YXMbB_oVcgw_124
|
| 596 |
+
bul6AM9JaDQ_395
|
| 597 |
+
_74aGilhTGU_481
|
| 598 |
+
qWpImMW4DHI_1261
|
| 599 |
+
lRiyTbH0D24_140
|
| 600 |
+
9X2wM6HD_og_835
|
| 601 |
+
yhFN_xVmNsI_430
|
| 602 |
+
aieThfuvmtY_16
|
| 603 |
+
qWpImMW4DHI_1918
|
| 604 |
+
Wc_gzO9i38k_437
|
| 605 |
+
samc7Y4r3fg_640
|
| 606 |
+
eqn9IX4aKmc_193
|
| 607 |
+
pC2WmY6bkB4_317
|
| 608 |
+
wmL6FiKKqvQ_221
|
| 609 |
+
93eAayq6GO0_290
|
| 610 |
+
RH5K2P6pH9Y_210
|
| 611 |
+
RpNrYMA2y6c_80
|
| 612 |
+
6DHUZ1Jt4wo_240
|
| 613 |
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OLBCzxzvBZM_17
|
| 614 |
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qvtEdv1WlUw_60
|
| 615 |
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G-XZhKqQAHU_129
|
| 616 |
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KVvDejzzQjM_158
|
| 617 |
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RpNrYMA2y6c_900
|
| 618 |
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KrEHdKxlNDQ_28
|
| 619 |
+
u-Hpf2_wzB8_450
|
| 620 |
+
RpNrYMA2y6c_450
|
| 621 |
+
_css5l3_vpY_214
|
| 622 |
+
_74aGilhTGU_663
|
| 623 |
+
TKPZf_P5_18_10
|
| 624 |
+
4C2hPdCmtbc_70
|
| 625 |
+
aM9v-6LKKhE_750
|
| 626 |
+
bul6AM9JaDQ_678
|
| 627 |
+
DcMh9zgZbSg_390
|
| 628 |
+
6DHUZ1Jt4wo_1090
|
| 629 |
+
YFGgXLvsEGc_1922
|
| 630 |
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hm65SlpTXZo_60
|
| 631 |
+
GmtUEtUCX8o_196
|
| 632 |
+
Y8BLz-u0u7c_474
|
| 633 |
+
b6L0bCePL0c_340
|
| 634 |
+
Y7YBDESILgY_2252
|
| 635 |
+
oOLW1t9vpVQ_270
|
| 636 |
+
fQukntBmFvY_200
|
| 637 |
+
lOJBGAd0mSw_270
|
| 638 |
+
yhFN_xVmNsI_330
|
| 639 |
+
AaculwvmaTA_1256
|
| 640 |
+
Y8BLz-u0u7c_267
|
| 641 |
+
hSbaRwmJ5AA_964
|
| 642 |
+
6DHUZ1Jt4wo_440
|
| 643 |
+
aM9v-6LKKhE_760
|
| 644 |
+
OWN_J9FGZ5I_247
|
| 645 |
+
SCiA9KmQIEw_110
|
| 646 |
+
_74aGilhTGU_2081
|
| 647 |
+
hSbaRwmJ5AA_3356
|
| 648 |
+
Pz4HjQhZDmk_158
|
| 649 |
+
6DHUZ1Jt4wo_1120
|
| 650 |
+
zUGBl9WEJY8_1006
|
| 651 |
+
xiPfXsNhgIc_210
|
| 652 |
+
5WQ87UIJHQU_132
|
| 653 |
+
V5IVN81wYrI_70
|
| 654 |
+
gyFx147_35Q_208
|
| 655 |
+
fhuwLnHsH5U_291
|
| 656 |
+
GGTOvP9OaXI_90
|
| 657 |
+
q2DXQeG55N0_780
|
| 658 |
+
Wc_gzO9i38k_240
|
| 659 |
+
DGtWuPemYc4_762
|
| 660 |
+
UG3nqEzgq00_410
|
| 661 |
+
kSyessjQYeA_1834
|
| 662 |
+
eE5oue9yeFQ_160
|
| 663 |
+
eqn9IX4aKmc_266
|
| 664 |
+
pC2WmY6bkB4_227
|
| 665 |
+
lRiyTbH0D24_60
|
| 666 |
+
yhFN_xVmNsI_130
|
| 667 |
+
P72n97ONayA_20
|
| 668 |
+
WU6WFEyfeH4_230
|
| 669 |
+
kSyessjQYeA_1148
|
| 670 |
+
dQaNzwqCUAA_573
|
| 671 |
+
BZ0yzt_-gtM_5
|
| 672 |
+
hSbaRwmJ5AA_992
|
| 673 |
+
6DHUZ1Jt4wo_430
|
| 674 |
+
aieThfuvmtY_274
|
| 675 |
+
_74aGilhTGU_3329
|
| 676 |
+
I_M0f1c59oc_46
|
| 677 |
+
JUN314mwb90_325
|
| 678 |
+
hSbaRwmJ5AA_1774
|
| 679 |
+
_74aGilhTGU_2552
|
| 680 |
+
KVvDejzzQjM_148
|
| 681 |
+
pC2WmY6bkB4_875
|
| 682 |
+
KVvDejzzQjM_263
|
| 683 |
+
WU6WFEyfeH4_340
|
| 684 |
+
AaculwvmaTA_783
|
| 685 |
+
u-Hpf2_wzB8_80
|
| 686 |
+
Wc_gzO9i38k_300
|
| 687 |
+
LQrZLRdjqww_250
|
| 688 |
+
RH5K2P6pH9Y_140
|
| 689 |
+
TETd0Q2wnbY_411
|
| 690 |
+
RH5K2P6pH9Y_580
|
| 691 |
+
6DHUZ1Jt4wo_950
|
| 692 |
+
LQrZLRdjqww_360
|
| 693 |
+
WQzEsz-lfIc_410
|
| 694 |
+
KVvDejzzQjM_247
|
| 695 |
+
dQaNzwqCUAA_281
|
| 696 |
+
V8UBNttMWJo_96
|
| 697 |
+
dQaNzwqCUAA_848
|
| 698 |
+
WU6WFEyfeH4_100
|
| 699 |
+
fhuwLnHsH5U_541
|
| 700 |
+
_74aGilhTGU_2894
|
| 701 |
+
kMZSoni0etA_100
|
| 702 |
+
sYeeLyTrTSI_123
|
| 703 |
+
aM9v-6LKKhE_150
|
| 704 |
+
6DHUZ1Jt4wo_1190
|
| 705 |
+
AaculwvmaTA_280
|
| 706 |
+
_74aGilhTGU_1381
|
| 707 |
+
aieThfuvmtY_416
|
| 708 |
+
Y8BLz-u0u7c_505
|
| 709 |
+
CBMUhxJC6TU_290
|
| 710 |
+
Y7YBDESILgY_1276
|
| 711 |
+
_74aGilhTGU_2572
|
| 712 |
+
yhFN_xVmNsI_560
|
| 713 |
+
zUGBl9WEJY8_851
|
| 714 |
+
rBKCBiIU72w_40
|
| 715 |
+
_css5l3_vpY_198
|
| 716 |
+
aM9v-6LKKhE_730
|
| 717 |
+
_yNwzbv3PeI_67
|
| 718 |
+
tt02LzCbIcU_60
|
| 719 |
+
WU6WFEyfeH4_560
|
| 720 |
+
f2kvR5I8s3c_140
|
| 721 |
+
aM9v-6LKKhE_610
|
| 722 |
+
RH5K2P6pH9Y_700
|
| 723 |
+
_74aGilhTGU_3027
|
| 724 |
+
j2PE0mccihM_37
|
| 725 |
+
Y7YBDESILgY_1083
|
| 726 |
+
RbFEpkuFCjI_277
|
| 727 |
+
6DHUZ1Jt4wo_720
|
| 728 |
+
samc7Y4r3fg_1195
|
| 729 |
+
nWlQWH7qP34_36
|
| 730 |
+
VvXNTF68hdE_400
|
| 731 |
+
qWpImMW4DHI_273
|
| 732 |
+
dQaNzwqCUAA_524
|
| 733 |
+
Fq8kqMmSl-c_280
|
| 734 |
+
JUN314mwb90_196
|
| 735 |
+
WU6WFEyfeH4_160
|
| 736 |
+
Fq8kqMmSl-c_40
|
| 737 |
+
6DHUZ1Jt4wo_1220
|
| 738 |
+
_74aGilhTGU_3409
|
| 739 |
+
QO-pWw4_z8Y_130
|
| 740 |
+
pC2WmY6bkB4_662
|
| 741 |
+
yhFN_xVmNsI_20
|
| 742 |
+
qWpImMW4DHI_1574
|
| 743 |
+
6DHUZ1Jt4wo_1160
|
| 744 |
+
GmtUEtUCX8o_149
|
| 745 |
+
RpNrYMA2y6c_660
|
| 746 |
+
I_M0f1c59oc_127
|
| 747 |
+
glZ5cH82ycE_590
|
| 748 |
+
_74aGilhTGU_1592
|
| 749 |
+
93eAayq6GO0_380
|
| 750 |
+
zja_kP413FM_103
|
| 751 |
+
CBMUhxJC6TU_480
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Eeg_WJTTRX0_110
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WU6WFEyfeH4_120
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AyVtAJzOJlE_1188
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| 1087 |
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HiaNsIscHPY_210
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| 1088 |
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yhFN_xVmNsI_540
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6DHUZ1Jt4wo_200
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MHjYjOXxx-E_160
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pC2WmY6bkB4_497
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Y8BLz-u0u7c_485
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Y8BLz-u0u7c_97
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GGTOvP9OaXI_130
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rBKCBiIU72w_110
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yhFN_xVmNsI_480
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zja_kP413FM_113
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bul6AM9JaDQ_240
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GmtUEtUCX8o_813
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rYKxKYUBcjo_371
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grWuEPQKFAs_150
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rBKCBiIU72w_50
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xiPfXsNhgIc_220
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qWpImMW4DHI_1514
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oOLW1t9vpVQ_250
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kMZSoni0etA_120
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Eeg_WJTTRX0_470
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bul6AM9JaDQ_206
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| 1110 |
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AaculwvmaTA_66
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H6rMi6s5lRQ_20
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QO-pWw4_z8Y_250
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| 1113 |
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WQzEsz-lfIc_330
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lOJBGAd0mSw_470
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yhFN_xVmNsI_240
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9X2wM6HD_og_696
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pC2WmY6bkB4_748
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RpNrYMA2y6c_840
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bGnivk-jepU_73
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ZBXiIs_4H6M_41
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VvXNTF68hdE_660
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fhuwLnHsH5U_866
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fhuwLnHsH5U_732
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bfHVJJKqZUg_296
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aM9v-6LKKhE_770
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eqn9IX4aKmc_152
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lRiyTbH0D24_130
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AaculwvmaTA_1845
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MHjYjOXxx-E_80
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qWpImMW4DHI_1797
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hSbaRwmJ5AA_1738
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HT-N_iI3jug_40
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JUN314mwb90_270
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9X2wM6HD_og_933
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f2kvR5I8s3c_20
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zK3mQlK9ZVo_120
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MHjYjOXxx-E_110
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PVQiHhIVa48_524
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UG3nqEzgq00_530
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RH5K2P6pH9Y_280
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Wc_gzO9i38k_126
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rBKCBiIU72w_30
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aieThfuvmtY_937
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pC2WmY6bkB4_484
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WN4g4INMbIw_210
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6DHUZ1Jt4wo_100
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Eeg_WJTTRX0_160
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lRiyTbH0D24_360
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9X2wM6HD_og_1068
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o5ILhtm2-Aw_88
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lRiyTbH0D24_350
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n91RZ57a3mI_790
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RpNrYMA2y6c_540
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JxMFgRCZuo0_160
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RH5K2P6pH9Y_570
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WQzEsz-lfIc_500
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AaculwvmaTA_191
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93eAayq6GO0_200
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yhFN_xVmNsI_280
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Hmlec3vVbq8_267
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Y7YBDESILgY_904
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aM9v-6LKKhE_380
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hSbaRwmJ5AA_605
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yhFN_xVmNsI_60
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RpNrYMA2y6c_90
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WQzEsz-lfIc_660
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WU6WFEyfeH4_440
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6DHUZ1Jt4wo_340
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zUGBl9WEJY8_585
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LQrZLRdjqww_350
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bul6AM9JaDQ_382
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| 1198 |
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PVQiHhIVa48_509
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| 1199 |
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DcMh9zgZbSg_100
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| 1200 |
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Wc_gzO9i38k_284
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| 1201 |
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wmL6FiKKqvQ_53
|
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rYKxKYUBcjo_249
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grWuEPQKFAs_260
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M8AHmUYaYbI_90
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6DHUZ1Jt4wo_690
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Y7YBDESILgY_919
|
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ZBesGWBVkeY_101
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V8UBNttMWJo_73
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RH5K2P6pH9Y_790
|
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Fq8kqMmSl-c_60
|
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gyFx147_35Q_13
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6DHUZ1Jt4wo_910
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RpNrYMA2y6c_170
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RbFEpkuFCjI_161
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| 1215 |
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kSyessjQYeA_339
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qWpImMW4DHI_865
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pC2WmY6bkB4_758
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qvtEdv1WlUw_140
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VvXNTF68hdE_520
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qWpImMW4DHI_1322
|
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7ZVYcIsEeHo_200
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Hmlec3vVbq8_304
|
| 1223 |
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aM9v-6LKKhE_640
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| 1224 |
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OWN_J9FGZ5I_120
|
| 1225 |
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b6L0bCePL0c_250
|
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eqn9IX4aKmc_451
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| 1227 |
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kMZSoni0etA_20
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| 1228 |
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WU6WFEyfeH4_270
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| 1229 |
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kSyessjQYeA_1551
|
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RH5K2P6pH9Y_150
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kSyessjQYeA_956
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WQzEsz-lfIc_530
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samc7Y4r3fg_262
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grWuEPQKFAs_40
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GVhSOeTOYag_1619
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6DHUZ1Jt4wo_830
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RpNrYMA2y6c_290
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Y7YBDESILgY_877
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lOJBGAd0mSw_170
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hm65SlpTXZo_100
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WU6WFEyfeH4_710
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Y7YBDESILgY_3501
|
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7ZVYcIsEeHo_60
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KvSsYaoSJGI_139
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6DHUZ1Jt4wo_400
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LSeJeKHsUkw_108
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kMZSoni0etA_80
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CBMUhxJC6TU_590
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pxf-4iLOUVA_1111
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yhFN_xVmNsI_410
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qWpImMW4DHI_56
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YXMbB_oVcgw_83
|
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glZ5cH82ycE_280
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grWuEPQKFAs_60
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oOLW1t9vpVQ_280
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fciO6_q2wk4_220
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yhFN_xVmNsI_40
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qWpImMW4DHI_1307
|
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6DHUZ1Jt4wo_250
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| 1261 |
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q2DXQeG55N0_840
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| 1262 |
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JUN314mwb90_356
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| 1263 |
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_yNwzbv3PeI_122
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kSyessjQYeA_1601
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| 1265 |
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n91RZ57a3mI_490
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| 1266 |
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zUGBl9WEJY8_1065
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RbFEpkuFCjI_410
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| 1268 |
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glZ5cH82ycE_580
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bfHVJJKqZUg_99
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6DHUZ1Jt4wo_1480
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| 1271 |
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RH5K2P6pH9Y_520
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| 1272 |
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fQukntBmFvY_110
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| 1273 |
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RH5K2P6pH9Y_720
|
| 1274 |
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WQzEsz-lfIc_520
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| 1275 |
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6DHUZ1Jt4wo_920
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| 1276 |
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Y7YBDESILgY_493
|
| 1277 |
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dQaNzwqCUAA_556
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| 1278 |
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zK3mQlK9ZVo_60
|
| 1279 |
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eqn9IX4aKmc_365
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| 1280 |
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WU6WFEyfeH4_10
|
| 1281 |
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q2DXQeG55N0_420
|
| 1282 |
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grWuEPQKFAs_240
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| 1283 |
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eqn9IX4aKmc_278
|
| 1284 |
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WU6WFEyfeH4_740
|
| 1285 |
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WQzEsz-lfIc_610
|
| 1286 |
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hSbaRwmJ5AA_1243
|
| 1287 |
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93eAayq6GO0_170
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| 1288 |
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VvXNTF68hdE_180
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| 1289 |
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7ZVYcIsEeHo_280
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| 1290 |
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RpNrYMA2y6c_630
|
| 1291 |
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bfHVJJKqZUg_441
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| 1292 |
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hSbaRwmJ5AA_2758
|
| 1293 |
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HT-N_iI3jug_20
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UfGDEXV2F60_128
|
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kSyessjQYeA_1680
|
| 1296 |
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fhuwLnHsH5U_227
|
| 1297 |
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qvtEdv1WlUw_210
|
| 1298 |
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zWkaEsCIg5Q_291
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| 1299 |
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fhuwLnHsH5U_921
|
| 1300 |
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hSbaRwmJ5AA_692
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| 1301 |
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zja_kP413FM_90
|
| 1302 |
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WU6WFEyfeH4_470
|
| 1303 |
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lOJBGAd0mSw_100
|
| 1304 |
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2XhYnQ5QC4E_168
|
| 1305 |
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tt02LzCbIcU_80
|
| 1306 |
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QO-pWw4_z8Y_730
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| 1307 |
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6DHUZ1Jt4wo_1510
|
| 1308 |
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RbDBfWg_6QU_88
|
| 1309 |
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2XhYnQ5QC4E_51
|
| 1310 |
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HiaNsIscHPY_330
|
| 1311 |
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RH5K2P6pH9Y_490
|
| 1312 |
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yhFN_xVmNsI_170
|
| 1313 |
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hX1dECWoEoc_51
|
| 1314 |
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6DHUZ1Jt4wo_600
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| 1315 |
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_74aGilhTGU_21
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| 1316 |
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6DHUZ1Jt4wo_560
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| 1317 |
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qWpImMW4DHI_1853
|
| 1318 |
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Y7YBDESILgY_264
|
| 1319 |
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qvtEdv1WlUw_130
|
| 1320 |
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RpNrYMA2y6c_640
|
| 1321 |
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UfGDEXV2F60_106
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| 1322 |
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hm65SlpTXZo_40
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| 1323 |
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QO-pWw4_z8Y_340
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| 1324 |
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Fq8kqMmSl-c_330
|
| 1325 |
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Y7YBDESILgY_1311
|
| 1326 |
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YXMbB_oVcgw_54
|
| 1327 |
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AaculwvmaTA_228
|
| 1328 |
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qWpImMW4DHI_1634
|
| 1329 |
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AaculwvmaTA_241
|
| 1330 |
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bul6AM9JaDQ_127
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| 1331 |
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pxf-4iLOUVA_0
|
| 1332 |
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Eeg_WJTTRX0_280
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| 1333 |
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Wc_gzO9i38k_15
|
| 1334 |
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93eAayq6GO0_230
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| 1335 |
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hSbaRwmJ5AA_2934
|
| 1336 |
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93eAayq6GO0_210
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| 1337 |
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Y7YBDESILgY_838
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| 1338 |
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L2Tv5v__9m4_14
|
| 1339 |
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oOLW1t9vpVQ_140
|
| 1340 |
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WU6WFEyfeH4_480
|
| 1341 |
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oOLW1t9vpVQ_210
|
| 1342 |
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dqZ2CiRm7f4_111
|
| 1343 |
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9X2wM6HD_og_170
|
| 1344 |
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pxf-4iLOUVA_846
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| 1345 |
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_yNwzbv3PeI_90
|
| 1346 |
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lOJBGAd0mSw_320
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| 1347 |
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PVQiHhIVa48_1061
|
| 1348 |
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Fq8kqMmSl-c_370
|
| 1349 |
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pC2WmY6bkB4_142
|
| 1350 |
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WQzEsz-lfIc_570
|
| 1351 |
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fciO6_q2wk4_190
|
| 1352 |
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6DHUZ1Jt4wo_1340
|
| 1353 |
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H6rMi6s5lRQ_140
|
| 1354 |
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6DHUZ1Jt4wo_470
|
| 1355 |
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aM9v-6LKKhE_390
|
| 1356 |
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AaculwvmaTA_410
|
| 1357 |
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_74aGilhTGU_557
|
| 1358 |
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93eAayq6GO0_180
|
| 1359 |
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DcMh9zgZbSg_270
|
| 1360 |
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xiPfXsNhgIc_150
|
| 1361 |
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UG3nqEzgq00_110
|
| 1362 |
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WU6WFEyfeH4_680
|
| 1363 |
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RbFEpkuFCjI_388
|
| 1364 |
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HiaNsIscHPY_130
|
| 1365 |
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WU6WFEyfeH4_360
|
| 1366 |
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kMZSoni0etA_90
|
| 1367 |
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qWpImMW4DHI_1843
|
| 1368 |
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DGtWuPemYc4_1491
|
| 1369 |
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P72n97ONayA_40
|
| 1370 |
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yhFN_xVmNsI_220
|
| 1371 |
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_74aGilhTGU_229
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| 1372 |
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aM9v-6LKKhE_400
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| 1373 |
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HiaNsIscHPY_380
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| 1374 |
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hSbaRwmJ5AA_2541
|
| 1375 |
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-3GumCmyAIk_82
|
| 1376 |
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hSbaRwmJ5AA_2481
|
| 1377 |
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kSyessjQYeA_2208
|
| 1378 |
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Wc_gzO9i38k_380
|
| 1379 |
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glZ5cH82ycE_740
|
| 1380 |
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9X2wM6HD_og_66
|
| 1381 |
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1whJPpizoDA_27
|
| 1382 |
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oOLW1t9vpVQ_300
|
| 1383 |
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6DHUZ1Jt4wo_840
|
| 1384 |
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JxMFgRCZuo0_220
|
| 1385 |
+
AaculwvmaTA_455
|
| 1386 |
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fhuwLnHsH5U_303
|
| 1387 |
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hm65SlpTXZo_150
|
| 1388 |
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lz4TkjaNVPY_78
|
| 1389 |
+
WU6WFEyfeH4_390
|
| 1390 |
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H6rMi6s5lRQ_40
|
| 1391 |
+
dQaNzwqCUAA_858
|
| 1392 |
+
qvtEdv1WlUw_500
|
| 1393 |
+
LQrZLRdjqww_420
|
| 1394 |
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lRiyTbH0D24_330
|
| 1395 |
+
2XhYnQ5QC4E_92
|
| 1396 |
+
RH5K2P6pH9Y_180
|
| 1397 |
+
Y7YBDESILgY_3555
|
| 1398 |
+
Y7YBDESILgY_392
|
| 1399 |
+
HiaNsIscHPY_230
|
| 1400 |
+
RbDBfWg_6QU_186
|
| 1401 |
+
KVvDejzzQjM_6
|
| 1402 |
+
oOLW1t9vpVQ_440
|
| 1403 |
+
Y7YBDESILgY_1103
|
| 1404 |
+
yhFN_xVmNsI_290
|
| 1405 |
+
QO-pWw4_z8Y_640
|
| 1406 |
+
UG3nqEzgq00_100
|
| 1407 |
+
_74aGilhTGU_31
|
| 1408 |
+
WQzEsz-lfIc_480
|
| 1409 |
+
fhuwLnHsH5U_614
|
| 1410 |
+
93eAayq6GO0_20
|
| 1411 |
+
CBMUhxJC6TU_390
|
| 1412 |
+
ZBXiIs_4H6M_67
|
| 1413 |
+
fQukntBmFvY_210
|
| 1414 |
+
QO-pWw4_z8Y_770
|
| 1415 |
+
V5IVN81wYrI_90
|
| 1416 |
+
hSbaRwmJ5AA_3156
|
| 1417 |
+
RbFEpkuFCjI_140
|
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|
| 1751 |
+
zK3mQlK9ZVo_140
|
| 1752 |
+
CBMUhxJC6TU_230
|
| 1753 |
+
_74aGilhTGU_1639
|
| 1754 |
+
v5f-G9Uu5dE_60
|
| 1755 |
+
Y7YBDESILgY_1265
|
| 1756 |
+
aM9v-6LKKhE_440
|
| 1757 |
+
oOLW1t9vpVQ_130
|
| 1758 |
+
pC2WmY6bkB4_101
|
| 1759 |
+
Y7YBDESILgY_2948
|
| 1760 |
+
_74aGilhTGU_2822
|
| 1761 |
+
u-Hpf2_wzB8_130
|
| 1762 |
+
_css5l3_vpY_187
|
| 1763 |
+
Eeg_WJTTRX0_410
|
| 1764 |
+
GmtUEtUCX8o_519
|
| 1765 |
+
QO-pWw4_z8Y_140
|
| 1766 |
+
aieThfuvmtY_690
|
| 1767 |
+
CBMUhxJC6TU_240
|
| 1768 |
+
UG3nqEzgq00_240
|
| 1769 |
+
UG3nqEzgq00_650
|
| 1770 |
+
n91RZ57a3mI_910
|
| 1771 |
+
GGTOvP9OaXI_110
|
| 1772 |
+
WU6WFEyfeH4_510
|
| 1773 |
+
KvSsYaoSJGI_233
|
| 1774 |
+
_74aGilhTGU_3067
|
| 1775 |
+
93eAayq6GO0_390
|
| 1776 |
+
qvtEdv1WlUw_260
|
| 1777 |
+
6DHUZ1Jt4wo_480
|
| 1778 |
+
Hmlec3vVbq8_278
|
| 1779 |
+
OWN_J9FGZ5I_55
|
| 1780 |
+
QO-pWw4_z8Y_650
|
| 1781 |
+
WU6WFEyfeH4_690
|
| 1782 |
+
WU6WFEyfeH4_540
|
| 1783 |
+
aM9v-6LKKhE_520
|
| 1784 |
+
qWpImMW4DHI_1009
|
| 1785 |
+
n91RZ57a3mI_230
|
| 1786 |
+
aIQnFp5sSc8_246
|
| 1787 |
+
WU6WFEyfeH4_210
|
| 1788 |
+
qWpImMW4DHI_2243
|
| 1789 |
+
WQzEsz-lfIc_350
|
| 1790 |
+
fhuwLnHsH5U_767
|
| 1791 |
+
ZBXiIs_4H6M_30
|
| 1792 |
+
GmtUEtUCX8o_496
|
| 1793 |
+
eqn9IX4aKmc_292
|
| 1794 |
+
eqn9IX4aKmc_613
|
| 1795 |
+
p5Ady9RJyhU_130
|
| 1796 |
+
yhFN_xVmNsI_120
|
| 1797 |
+
pRaDY4sIHhU_17
|
| 1798 |
+
93eAayq6GO0_240
|
| 1799 |
+
WQzEsz-lfIc_10
|
| 1800 |
+
oOLW1t9vpVQ_520
|
| 1801 |
+
RbFEpkuFCjI_421
|
| 1802 |
+
JUN314mwb90_100
|
| 1803 |
+
eqn9IX4aKmc_351
|
| 1804 |
+
-3GumCmyAIk_254
|
| 1805 |
+
glZ5cH82ycE_100
|
| 1806 |
+
6DHUZ1Jt4wo_640
|
| 1807 |
+
fhuwLnHsH5U_673
|
| 1808 |
+
RbDBfWg_6QU_165
|
| 1809 |
+
grWuEPQKFAs_80
|
| 1810 |
+
6DHUZ1Jt4wo_590
|
| 1811 |
+
OLBCzxzvBZM_86
|
| 1812 |
+
lRiyTbH0D24_200
|
| 1813 |
+
nDu57CGqbLM_38
|
| 1814 |
+
93eAayq6GO0_480
|
| 1815 |
+
GGTOvP9OaXI_50
|
| 1816 |
+
QO-pWw4_z8Y_310
|
| 1817 |
+
tt02LzCbIcU_90
|
| 1818 |
+
zK3mQlK9ZVo_100
|
| 1819 |
+
Y7YBDESILgY_1403
|
| 1820 |
+
xiPfXsNhgIc_170
|
| 1821 |
+
bul6AM9JaDQ_196
|
| 1822 |
+
fhuwLnHsH5U_75
|
| 1823 |
+
pC2WmY6bkB4_737
|
| 1824 |
+
AaculwvmaTA_1665
|
| 1825 |
+
7ZVYcIsEeHo_50
|
| 1826 |
+
JUN314mwb90_314
|
| 1827 |
+
aieThfuvmtY_1090
|
| 1828 |
+
93eAayq6GO0_330
|
| 1829 |
+
MHjYjOXxx-E_180
|
| 1830 |
+
RbFEpkuFCjI_79
|
| 1831 |
+
AaculwvmaTA_270
|
| 1832 |
+
JEbPgn3clPk_38
|
| 1833 |
+
pxf-4iLOUVA_658
|
| 1834 |
+
6DHUZ1Jt4wo_1470
|
| 1835 |
+
hSbaRwmJ5AA_2949
|
| 1836 |
+
bA_7toCijrk_29
|
| 1837 |
+
qvtEdv1WlUw_280
|
| 1838 |
+
bul6AM9JaDQ_227
|
| 1839 |
+
OLBCzxzvBZM_27
|
| 1840 |
+
qWpImMW4DHI_887
|
| 1841 |
+
u-Hpf2_wzB8_240
|
| 1842 |
+
grWuEPQKFAs_50
|
| 1843 |
+
UG3nqEzgq00_150
|
| 1844 |
+
KVvDejzzQjM_55
|
| 1845 |
+
eE5oue9yeFQ_93
|
| 1846 |
+
XiPamwUKnEo_174
|
| 1847 |
+
kSyessjQYeA_905
|
| 1848 |
+
6DHUZ1Jt4wo_1310
|
| 1849 |
+
o5ILhtm2-Aw_122
|
| 1850 |
+
bfHVJJKqZUg_452
|
| 1851 |
+
_74aGilhTGU_3222
|
| 1852 |
+
Y7YBDESILgY_516
|
| 1853 |
+
samc7Y4r3fg_1328
|
| 1854 |
+
-3GumCmyAIk_57
|
| 1855 |
+
AaculwvmaTA_1696
|
| 1856 |
+
hSbaRwmJ5AA_1611
|
| 1857 |
+
RH5K2P6pH9Y_190
|
| 1858 |
+
_74aGilhTGU_967
|
| 1859 |
+
Pz4HjQhZDmk_172
|
| 1860 |
+
WU6WFEyfeH4_20
|
| 1861 |
+
bfHVJJKqZUg_631
|
| 1862 |
+
5WrI-nS59kA_610
|
| 1863 |
+
pC2WmY6bkB4_32
|
| 1864 |
+
WU6WFEyfeH4_450
|
| 1865 |
+
fciO6_q2wk4_20
|
| 1866 |
+
LQrZLRdjqww_240
|
| 1867 |
+
LQrZLRdjqww_120
|
| 1868 |
+
9X2wM6HD_og_943
|
| 1869 |
+
_74aGilhTGU_845
|
| 1870 |
+
fQukntBmFvY_100
|
| 1871 |
+
exjMJHYEssE_82
|
| 1872 |
+
UG3nqEzgq00_600
|
| 1873 |
+
OWN_J9FGZ5I_88
|
| 1874 |
+
1whJPpizoDA_296
|
| 1875 |
+
GmtUEtUCX8o_873
|
| 1876 |
+
p5Ady9RJyhU_120
|
| 1877 |
+
RpNrYMA2y6c_230
|
| 1878 |
+
bul6AM9JaDQ_35
|
| 1879 |
+
OWN_J9FGZ5I_182
|
| 1880 |
+
KvSsYaoSJGI_20
|
| 1881 |
+
M8AHmUYaYbI_50
|
| 1882 |
+
VvXNTF68hdE_160
|
| 1883 |
+
3GSTGzYkHks_70
|
| 1884 |
+
RpNrYMA2y6c_270
|
| 1885 |
+
93eAayq6GO0_500
|
| 1886 |
+
WQzEsz-lfIc_390
|
| 1887 |
+
RH5K2P6pH9Y_310
|
| 1888 |
+
bul6AM9JaDQ_352
|
| 1889 |
+
UG3nqEzgq00_430
|
| 1890 |
+
Eeg_WJTTRX0_210
|
| 1891 |
+
glZ5cH82ycE_550
|
| 1892 |
+
6DHUZ1Jt4wo_980
|
| 1893 |
+
HiaNsIscHPY_240
|
| 1894 |
+
lRiyTbH0D24_320
|
| 1895 |
+
6DHUZ1Jt4wo_130
|
| 1896 |
+
QO-pWw4_z8Y_750
|
| 1897 |
+
Pz4HjQhZDmk_192
|
| 1898 |
+
QO-pWw4_z8Y_150
|
| 1899 |
+
hSbaRwmJ5AA_116
|
| 1900 |
+
tOJ6CGr-iho_210
|
| 1901 |
+
u-Hpf2_wzB8_310
|
| 1902 |
+
PVQiHhIVa48_134
|
| 1903 |
+
SCiA9KmQIEw_90
|
| 1904 |
+
q2DXQeG55N0_190
|
| 1905 |
+
VvXNTF68hdE_600
|
| 1906 |
+
KVvDejzzQjM_230
|
| 1907 |
+
7ZVYcIsEeHo_360
|
| 1908 |
+
H6rMi6s5lRQ_160
|
| 1909 |
+
lRiyTbH0D24_30
|
| 1910 |
+
WQzEsz-lfIc_190
|
| 1911 |
+
oOLW1t9vpVQ_240
|
| 1912 |
+
JUN314mwb90_342
|
| 1913 |
+
GmtUEtUCX8o_456
|
| 1914 |
+
0FB9jMXMP8A_52
|
| 1915 |
+
So9RUFpdPFU_22
|
| 1916 |
+
_74aGilhTGU_2463
|
| 1917 |
+
eqn9IX4aKmc_555
|
| 1918 |
+
qvtEdv1WlUw_400
|
| 1919 |
+
VvXNTF68hdE_320
|
| 1920 |
+
ZBXiIs_4H6M_52
|
| 1921 |
+
Eeg_WJTTRX0_200
|
| 1922 |
+
Wc_gzO9i38k_335
|
| 1923 |
+
93eAayq6GO0_490
|
| 1924 |
+
WQzEsz-lfIc_210
|
| 1925 |
+
WU6WFEyfeH4_150
|
| 1926 |
+
qvtEdv1WlUw_440
|
| 1927 |
+
9X2wM6HD_og_313
|
| 1928 |
+
CBMUhxJC6TU_610
|
| 1929 |
+
Wc_gzO9i38k_108
|
| 1930 |
+
pC2WmY6bkB4_472
|
| 1931 |
+
qWpImMW4DHI_1504
|
| 1932 |
+
hSbaRwmJ5AA_1948
|
| 1933 |
+
aM9v-6LKKhE_690
|
| 1934 |
+
hSbaRwmJ5AA_1970
|
| 1935 |
+
Y7YBDESILgY_1093
|
| 1936 |
+
CBMUhxJC6TU_550
|
| 1937 |
+
xMVdww-5394_370
|
| 1938 |
+
yhFN_xVmNsI_380
|
| 1939 |
+
aieThfuvmtY_1022
|
| 1940 |
+
pC2WmY6bkB4_862
|
| 1941 |
+
_yNwzbv3PeI_184
|
| 1942 |
+
WQzEsz-lfIc_360
|
| 1943 |
+
hSbaRwmJ5AA_1714
|
| 1944 |
+
DcMh9zgZbSg_710
|
| 1945 |
+
UG3nqEzgq00_490
|
| 1946 |
+
Y7YBDESILgY_2721
|
| 1947 |
+
grWuEPQKFAs_90
|
| 1948 |
+
lRiyTbH0D24_70
|
| 1949 |
+
wmL6FiKKqvQ_23
|
| 1950 |
+
QO-pWw4_z8Y_10
|
| 1951 |
+
5WrI-nS59kA_190
|
| 1952 |
+
AaculwvmaTA_855
|
| 1953 |
+
_74aGilhTGU_3133
|
| 1954 |
+
samc7Y4r3fg_2136
|
| 1955 |
+
_74aGilhTGU_3155
|
| 1956 |
+
bul6AM9JaDQ_502
|
| 1957 |
+
3GSTGzYkHks_80
|
| 1958 |
+
Fq8kqMmSl-c_440
|
| 1959 |
+
fhuwLnHsH5U_698
|
| 1960 |
+
qWpImMW4DHI_1729
|
| 1961 |
+
RpNrYMA2y6c_120
|
| 1962 |
+
Wc_gzO9i38k_28
|
| 1963 |
+
WQzEsz-lfIc_680
|
| 1964 |
+
WQzEsz-lfIc_30
|
| 1965 |
+
YFGgXLvsEGc_941
|
| 1966 |
+
93eAayq6GO0_340
|
| 1967 |
+
fP0NllADuo0_20
|
| 1968 |
+
RH5K2P6pH9Y_60
|
| 1969 |
+
Wc_gzO9i38k_184
|
| 1970 |
+
Eeg_WJTTRX0_190
|
| 1971 |
+
qWpImMW4DHI_568
|
| 1972 |
+
_74aGilhTGU_601
|
| 1973 |
+
aM9v-6LKKhE_680
|
| 1974 |
+
UG3nqEzgq00_580
|
| 1975 |
+
fQukntBmFvY_190
|
| 1976 |
+
QO-pWw4_z8Y_430
|
| 1977 |
+
RH5K2P6pH9Y_710
|
| 1978 |
+
93eAayq6GO0_80
|
| 1979 |
+
bGnivk-jepU_203
|
| 1980 |
+
qWpImMW4DHI_156
|
| 1981 |
+
Fq8kqMmSl-c_50
|
| 1982 |
+
Eeg_WJTTRX0_170
|
| 1983 |
+
dQaNzwqCUAA_585
|
| 1984 |
+
lRiyTbH0D24_240
|
| 1985 |
+
qvtEdv1WlUw_480
|
| 1986 |
+
6DHUZ1Jt4wo_730
|
| 1987 |
+
aM9v-6LKKhE_780
|
| 1988 |
+
dQaNzwqCUAA_891
|
| 1989 |
+
eqn9IX4aKmc_488
|
| 1990 |
+
rYKxKYUBcjo_347
|
| 1991 |
+
0FB9jMXMP8A_152
|
| 1992 |
+
HiaNsIscHPY_160
|
| 1993 |
+
VQAGxC8mSzA_77
|
| 1994 |
+
JUN314mwb90_291
|
| 1995 |
+
rYKxKYUBcjo_20
|
| 1996 |
+
1whJPpizoDA_37
|
| 1997 |
+
RH5K2P6pH9Y_600
|
| 1998 |
+
QO-pWw4_z8Y_210
|
| 1999 |
+
kMZSoni0etA_50
|
| 2000 |
+
_74aGilhTGU_1698
|
| 2001 |
+
aM9v-6LKKhE_670
|
| 2002 |
+
CBMUhxJC6TU_530
|
| 2003 |
+
93eAayq6GO0_150
|
| 2004 |
+
RpNrYMA2y6c_430
|
| 2005 |
+
glZ5cH82ycE_120
|
| 2006 |
+
93eAayq6GO0_450
|
| 2007 |
+
RH5K2P6pH9Y_880
|
| 2008 |
+
hSbaRwmJ5AA_1091
|
| 2009 |
+
qWpImMW4DHI_294
|
| 2010 |
+
93eAayq6GO0_260
|
| 2011 |
+
MHjYjOXxx-E_290
|
| 2012 |
+
AaculwvmaTA_1165
|
| 2013 |
+
93eAayq6GO0_570
|
| 2014 |
+
9X2wM6HD_og_181
|
| 2015 |
+
u-Hpf2_wzB8_260
|
| 2016 |
+
RpNrYMA2y6c_670
|
| 2017 |
+
ZBesGWBVkeY_3
|
| 2018 |
+
CBMUhxJC6TU_20
|
| 2019 |
+
kSyessjQYeA_822
|
| 2020 |
+
CBMUhxJC6TU_350
|
| 2021 |
+
n91RZ57a3mI_260
|
| 2022 |
+
u-Hpf2_wzB8_180
|
| 2023 |
+
Y7YBDESILgY_1010
|
| 2024 |
+
GmtUEtUCX8o_1073
|
| 2025 |
+
zUGBl9WEJY8_557
|
| 2026 |
+
WN4g4INMbIw_200
|
| 2027 |
+
L2Tv5v__9m4_24
|
| 2028 |
+
n91RZ57a3mI_200
|
| 2029 |
+
Wc_gzO9i38k_361
|
| 2030 |
+
fhuwLnHsH5U_1137
|
| 2031 |
+
grWuEPQKFAs_110
|
| 2032 |
+
CBMUhxJC6TU_560
|
| 2033 |
+
91jpE2P8SPM_144
|
| 2034 |
+
tmO6N6TBXoE_84
|
| 2035 |
+
WQzEsz-lfIc_560
|
| 2036 |
+
XiPamwUKnEo_149
|
| 2037 |
+
TETd0Q2wnbY_278
|
| 2038 |
+
fhuwLnHsH5U_755
|
| 2039 |
+
xiPfXsNhgIc_120
|
| 2040 |
+
6DHUZ1Jt4wo_180
|
| 2041 |
+
9X2wM6HD_og_1048
|
| 2042 |
+
vPOh8bauanA_25
|
| 2043 |
+
5WQ87UIJHQU_118
|
| 2044 |
+
RH5K2P6pH9Y_270
|
| 2045 |
+
kSyessjQYeA_1342
|
| 2046 |
+
b6L0bCePL0c_50
|
| 2047 |
+
f2kvR5I8s3c_50
|
| 2048 |
+
WQzEsz-lfIc_470
|
| 2049 |
+
OWN_J9FGZ5I_289
|
| 2050 |
+
_74aGilhTGU_2542
|
| 2051 |
+
qvtEdv1WlUw_460
|
| 2052 |
+
v5f-G9Uu5dE_16
|
| 2053 |
+
CBMUhxJC6TU_260
|
| 2054 |
+
RH5K2P6pH9Y_130
|
| 2055 |
+
GmtUEtUCX8o_942
|
| 2056 |
+
yhFN_xVmNsI_350
|
| 2057 |
+
MHjYjOXxx-E_150
|
| 2058 |
+
CBMUhxJC6TU_540
|
| 2059 |
+
MHjYjOXxx-E_190
|
| 2060 |
+
yhFN_xVmNsI_370
|
| 2061 |
+
QqMf0qWsCYM_221
|
| 2062 |
+
RH5K2P6pH9Y_390
|
| 2063 |
+
PVQiHhIVa48_785
|
| 2064 |
+
bul6AM9JaDQ_165
|
| 2065 |
+
qWpImMW4DHI_74
|
| 2066 |
+
u-Hpf2_wzB8_280
|
| 2067 |
+
eE5oue9yeFQ_183
|
| 2068 |
+
xiPfXsNhgIc_20
|
| 2069 |
+
fl-rc2-fb4Y_114
|
| 2070 |
+
_74aGilhTGU_1681
|
| 2071 |
+
fhuwLnHsH5U_936
|
| 2072 |
+
QO-pWw4_z8Y_520
|
| 2073 |
+
zWkaEsCIg5Q_45
|
| 2074 |
+
HT-N_iI3jug_50
|
| 2075 |
+
AaculwvmaTA_1998
|
| 2076 |
+
oOLW1t9vpVQ_120
|
| 2077 |
+
glZ5cH82ycE_720
|
| 2078 |
+
uuzlaAPBXYs_216
|
| 2079 |
+
3GSTGzYkHks_100
|
| 2080 |
+
UG3nqEzgq00_590
|
| 2081 |
+
fciO6_q2wk4_150
|
| 2082 |
+
zWkaEsCIg5Q_134
|
| 2083 |
+
AaculwvmaTA_1468
|
| 2084 |
+
Fq8kqMmSl-c_300
|
| 2085 |
+
yhFN_xVmNsI_590
|
| 2086 |
+
5WrI-nS59kA_420
|
| 2087 |
+
u-Hpf2_wzB8_170
|
| 2088 |
+
HiaNsIscHPY_250
|
| 2089 |
+
kSyessjQYeA_1884
|
| 2090 |
+
xiPfXsNhgIc_270
|
| 2091 |
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cqb-1gHYJHgl_170
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|
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V_To4k9AJXcl_190
|
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6u9WL3KfIZUl_20
|
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V_To4k9AJXcl_150
|
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8iTTf1exkdMl_60
|
| 3056 |
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V_To4k9AJXcl_50
|
| 3057 |
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PuekW6d_0yEl_30
|
| 3058 |
+
PuekW6d_0yEl_110
|
| 3059 |
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cqb-1gHYJHgl_150
|
| 3060 |
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cqb-1gHYJHgl_10
|
| 3061 |
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8iTTf1exkdMl_20
|
| 3062 |
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8iTTf1exkdMl_150
|
| 3063 |
+
V_To4k9AJXcl_140
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Data Cleaning
|
| 2 |
+
|
| 3 |
+
|
| 4 |
+
|
| 5 |
+
- [Data Cleaning](#data-cleaning)
|
| 6 |
+
- [Silent Filtering](#silent-filtering)
|
| 7 |
+
- [Static Frame Filtering](#static-frame-filtering)
|
| 8 |
+
- [Audio-Visual Matching Filtering](#audio-visual-matching-filtering)
|
| 9 |
+
- [Voice Detection Filtering](#voice-detection-filtering)
|
| 10 |
+
|
| 11 |
+
|
| 12 |
+
## Silent Filtering
|
| 13 |
+
|
| 14 |
+
**Path:** [toolset/clean/silent/check_new_silent.py](../toolset/crawl/core/download/download_list.py)
|
| 15 |
+
|
| 16 |
+
**Description:** Filters out audio clips where dBFS remains below -35 for over 90% of the duration. (Parameters are adjustable)
|
| 17 |
+
|
| 18 |
+
**Usage Instructions:**
|
| 19 |
+
|
| 20 |
+
1. Modify the input_directory and output_txt_file parameters in [check_new_silent.py](../toolset/crawl/core/download/download_list.py).
|
| 21 |
+
2. Run: `python check_new_silent.py`.
|
| 22 |
+
|
| 23 |
+
## Static Frame Filtering
|
| 24 |
+
|
| 25 |
+
**Path:** [toolset/clean/static/check_static_ffmpeg.py](../toolset/crawl/core/download/download_list.py)
|
| 26 |
+
|
| 27 |
+
**Description:** Samples 2 frames per second. Consecutive frames are converted to grayscale and compared using MSE - frames with MSE <5 are considered static. Videos with over 85% static frames are filtered. (Parameters are adjustable)
|
| 28 |
+
|
| 29 |
+
**Usage Instructions:**
|
| 30 |
+
|
| 31 |
+
1. Set the folder_path parameter in [check_static_ffmpeg.py](../toolset/crawl/core/download/download_list.py).
|
| 32 |
+
2. Execute: `python check_static_ffmpeg.py`.
|
| 33 |
+
|
| 34 |
+
## Audio-Visual Matching Filtering
|
| 35 |
+
|
| 36 |
+
**Path:** [toolset/clean/ImageBind/test.py](../toolset/clean/ImageBind/test.py)
|
| 37 |
+
|
| 38 |
+
**Description:** Uses [ImageBind](https://github.com/facebookresearch/ImageBind) to evaluate the match between video content and audio.
|
| 39 |
+
|
| 40 |
+
**Usage Instructions:**
|
| 41 |
+
|
| 42 |
+
1. Clone the [ImageBind](https://github.com/facebookresearch/ImageBind) repository into `toolset/clean/ImageBind/` and configure python environment.
|
| 43 |
+
2. (Optional) Configure CUDA settings in `test.py`.
|
| 44 |
+
3. Run: `python test.py`.
|
| 45 |
+
|
| 46 |
+
## Voice Detection Filtering
|
| 47 |
+
|
| 48 |
+
**Path:** [toolset/clean/SenseVoice/check_voice.py](../toolset/clean/SenseVoice/check_voice.py), [toolset/clean/SenseVoice/char_count.py](../toolset/clean/SenseVoice/char_count.py)
|
| 49 |
+
|
| 50 |
+
**Description:** Uses SenseVoice for voice detection and analysis.
|
| 51 |
+
|
| 52 |
+
**Usage Instructions:**
|
| 53 |
+
|
| 54 |
+
1. Clone the [SenseVoice](https://github.com/FunAudioLLM/SenseVoice) repository into `toolset/clean/SenseVoice/` and configure python environment.
|
| 55 |
+
2. Configure `audio_folder` in [check_voice.py](../toolset/clean/SenseVoice/check_voice.py).
|
| 56 |
+
3. Run [check_voice.py](../toolset/clean/SenseVoice/check_voice.py) to output recognized speech text
|
| 57 |
+
4. Execute [char_count.py]((../toolset/clean/SenseVoice/char_count.py)) for speech character analysis
|
docs/crawl.md
ADDED
|
@@ -0,0 +1,141 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Data Crawling
|
| 2 |
+
|
| 3 |
+
|
| 4 |
+
|
| 5 |
+
|
| 6 |
+
|
| 7 |
+
- [Data Crawling](#data-crawling)
|
| 8 |
+
- [Search](#search)
|
| 9 |
+
- [Channel-Based Crawling](#channel-based-crawling)
|
| 10 |
+
- [Analyze channels based on search results](#analyze-channels-based-on-search-results)
|
| 11 |
+
- [Get Video IDs for channels](#get-video-ids-for-channels)
|
| 12 |
+
- [Get test video metadata](#get-test-video-metadata)
|
| 13 |
+
- [Download test videos \& Check](#download-test-videos--check)
|
| 14 |
+
- [Get Video IDs based on Channel IDs](#get-video-ids-based-on-channel-ids)
|
| 15 |
+
- [Download](#download)
|
| 16 |
+
- [Video-Based Crawling](#video-based-crawling)
|
| 17 |
+
- [Filter by Blacklist](#filter-by-blacklist)
|
| 18 |
+
- [Download Test Videos \& Verification \& Full Download](#download-test-videos--verification--full-download)
|
| 19 |
+
- [Download](#download-1)
|
| 20 |
+
- [Full Video Download](#full-video-download)
|
| 21 |
+
- [Batch Download Function](#batch-download-function)
|
| 22 |
+
|
| 23 |
+
|
| 24 |
+
## Search
|
| 25 |
+
|
| 26 |
+
**Path:** [toolset/crawl/search/search.sh](../toolset/crawl/search/search.sh)
|
| 27 |
+
|
| 28 |
+
**Description:** This script uses the YouTube API to search for 360-degree videos based on a predefined list of keywords and suffix terms. Note that the retrieved videos are confirmed as 360-degree videos but **do not guarantee support for Spatial Audio**. To filter videos that support Spatial Audio, use a downloader (e.g., `yt-dlp` with an audio channel count filter).
|
| 29 |
+
|
| 30 |
+
**Usage Instructions:**
|
| 31 |
+
|
| 32 |
+
1. Prepare a keyword list file (one keyword per line).
|
| 33 |
+
2. Modify the parameters in `search.sh`, such as `keyword_file`, `postfix`(i.e. the qualifying term), and `output_dir`. Refer to the code comments for detailed parameter descriptions.
|
| 34 |
+
3. Run `bash search.sh` to execute the search. Results are saved in CSV format under the `output_dir` directory, organized by keyword.
|
| 35 |
+
|
| 36 |
+
## Channel-Based Crawling
|
| 37 |
+
|
| 38 |
+
### Analyze channels based on search results
|
| 39 |
+
|
| 40 |
+
**Path:** [toolset/crawl/channel/channel_analyzer.py](../toolset/crawl/channel/channel_analyzer.py)
|
| 41 |
+
|
| 42 |
+
**Description:** Analyzes frequently appearing channels based on search results from the `search` module. Outputs in CSV format.
|
| 43 |
+
|
| 44 |
+
**Usage Instructions:**
|
| 45 |
+
|
| 46 |
+
```bash
|
| 47 |
+
python channel_analyzer.py -i [input-dir] -o [output-file]
|
| 48 |
+
```
|
| 49 |
+
|
| 50 |
+
### Get Video IDs for channels
|
| 51 |
+
|
| 52 |
+
**Path:** [toolset/crawl/channel/get_channel_vids.py](../toolset/crawl/channel/get_channel_vids.py)
|
| 53 |
+
|
| 54 |
+
**Description:** Retrieves all 360-degree video IDs from the most promising channels (those containing the most search results). The output directory contains CSV files named by Channel ID, each containing all 360-degree video IDs for the corresponding channel.
|
| 55 |
+
|
| 56 |
+
**Usage Instructions:**
|
| 57 |
+
|
| 58 |
+
```bash
|
| 59 |
+
python get_channel_vids.py -i [input-csv] -o [out-dir] -t [threshold]
|
| 60 |
+
```
|
| 61 |
+
|
| 62 |
+
Where `threshold` specifies the minimum number of times a channel must appear in search results to be retained.
|
| 63 |
+
|
| 64 |
+
### Get test video metadata
|
| 65 |
+
|
| 66 |
+
**Path:** [toolset/crawl/channel/get_test_list.py](../toolset/crawl/channel/get_test_list.py)
|
| 67 |
+
|
| 68 |
+
**Description:** For each channel, randomly samples several video segments from the Channel ID's video ID information, and outputs in CSV format recognizable by download scripts.
|
| 69 |
+
|
| 70 |
+
**Usage Instructions:**
|
| 71 |
+
|
| 72 |
+
```bash
|
| 73 |
+
python get_test_list.py -i [in-dir] -o [out-dir] [-n [sample-size]]
|
| 74 |
+
```
|
| 75 |
+
|
| 76 |
+
Here `in-dir` contains the CSV files named by Channel ID obtained from the previous module, and `out-dir` will contain CSV files named by each Channel ID, with each file containing up to 10 Video IDs for the corresponding channel.
|
| 77 |
+
|
| 78 |
+
### Download test videos & Check
|
| 79 |
+
|
| 80 |
+
Use your preferred downloader or scripts from the `Download` section to download test segments, then perform manual verification or use the cleaning pipeline from the `Data Cleaning` section to verify channel quality, filtering out usable and unusable Channel IDs (both can be included in the Channel Black List).
|
| 81 |
+
|
| 82 |
+
### Get Video IDs based on Channel IDs
|
| 83 |
+
|
| 84 |
+
**Path:** [toolset/crawl/channel/get_channels_vids.py](../toolset/crawl/channel/get_channels_vids.py)
|
| 85 |
+
|
| 86 |
+
**Description:** Retrieves video IDs to be downloaded based on a list of available Channel IDs. All resulting Video IDs are guaranteed to be 360-degree videos. Due to API limitations, Spatial Audio support is verified during the download phase rather than this stage.
|
| 87 |
+
|
| 88 |
+
**Usage Instructions:**
|
| 89 |
+
|
| 90 |
+
```bash
|
| 91 |
+
python get_channels_vids.py -i [input-csv] -o [output-csv]
|
| 92 |
+
```
|
| 93 |
+
|
| 94 |
+
### Download
|
| 95 |
+
|
| 96 |
+
Use your preferred downloader or scripts from the `Download` section for video downloading.
|
| 97 |
+
|
| 98 |
+
## Video-Based Crawling
|
| 99 |
+
|
| 100 |
+
### Filter by Blacklist
|
| 101 |
+
|
| 102 |
+
**Path:** [toolset/crawl/filter/filter_exist.py](../toolset/crawl/filter/filter_exist.py)
|
| 103 |
+
|
| 104 |
+
**Description:**
|
| 105 |
+
|
| 106 |
+
Utilizes the established video and channel blacklists from Channel-Based Crawling to filter out confirmed unnecessary video entries from search results, generating a smaller-scale list for manual review.
|
| 107 |
+
|
| 108 |
+
**Usage Instructions:**
|
| 109 |
+
|
| 110 |
+
1. Prepare the Video ID blacklist database and Channel ID blacklist database (including all manually verified usable/unusable video or channel IDs). Modify `video_db_path` and `channel_db_path` in the script.
|
| 111 |
+
2. Update the search results path `folder_path` (output from the `Search` module) and output file path `output_csv` in the script.
|
| 112 |
+
3. Run `python filter_exist.py` to execute the filtering.
|
| 113 |
+
|
| 114 |
+
### Download Test Videos & Verification & Full Download
|
| 115 |
+
|
| 116 |
+
Use a downloader of choice to fetch video clips for screening. After verification, proceed with full downloads of usable videos.
|
| 117 |
+
|
| 118 |
+
## Download
|
| 119 |
+
|
| 120 |
+
### Full Video Download
|
| 121 |
+
|
| 122 |
+
**Path:** [toolset/crawl/download/download_list.sh](../toolset/crawl/download/download_list.sh)
|
| 123 |
+
|
| 124 |
+
**Description:** Downloads all videos based on Video IDs provided in a CSV file. Supports multi-process downloading. Results are logged in `success_list.txt` and `fail_list.txt` in the current directory.
|
| 125 |
+
|
| 126 |
+
**Usage Instructions:**
|
| 127 |
+
|
| 128 |
+
Modify relevant parameters in [download_list.sh](../toolset/crawl/download/download_list.sh), then execute:
|
| 129 |
+
|
| 130 |
+
```bash
|
| 131 |
+
bash download_list.sh
|
| 132 |
+
```
|
| 133 |
+
|
| 134 |
+
### Batch Download Function
|
| 135 |
+
|
| 136 |
+
The `download_list_360` function in [toolset/crawl/core/download/download_list.py](../toolset/crawl/core/download/download_list.py) enables batch downloading. Refer to the function documentation for usage. Common configurations include:
|
| 137 |
+
|
| 138 |
+
- **Clip Downloading**: Use `specify_start` and `time_interval` parameters (see function docs for details).
|
| 139 |
+
- **Multi-process Downloading**: Set the number of parallel downloads via the `jobs` parameter.
|
| 140 |
+
- **Custom Cookies**: Specify cookies using the `cookie` parameter.
|
| 141 |
+
- **Proxy Configuration**: Configure proxy servers via the `proxy` parameter.
|
docs/img/clean.png
ADDED
|
Git LFS Details
|
docs/img/crawl.png
ADDED
|
Git LFS Details
|
toolset/clean/ImageBind/test.py
ADDED
|
@@ -0,0 +1,147 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
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|
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|
|
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|
|
|
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|
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|
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|
|
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|
|
|
|
|
|
|
|
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|
|
|
|
|
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|
|
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|
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|
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|
|
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|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
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|
|
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|
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|
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|
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
| 1 |
+
import torch
|
| 2 |
+
import os
|
| 3 |
+
import csv
|
| 4 |
+
from tqdm import tqdm
|
| 5 |
+
from imagebind import data
|
| 6 |
+
from imagebind.models import imagebind_model
|
| 7 |
+
from imagebind.models.imagebind_model import ModalityType
|
| 8 |
+
from pathlib import Path
|
| 9 |
+
import pandas as pd
|
| 10 |
+
import random
|
| 11 |
+
import torch.nn.functional as F
|
| 12 |
+
|
| 13 |
+
# Set device: Use GPU if available, otherwise CPU
|
| 14 |
+
device = ""
|
| 15 |
+
|
| 16 |
+
# Load ImageBind model
|
| 17 |
+
try:
|
| 18 |
+
model = imagebind_model.imagebind_huge(pretrained=True)
|
| 19 |
+
model.eval()
|
| 20 |
+
model.to(device)
|
| 21 |
+
except Exception as e:
|
| 22 |
+
print(f"Error loading the model: {e}")
|
| 23 |
+
exit(1) # Exit if model loading fails
|
| 24 |
+
|
| 25 |
+
# Set audio and video folder paths
|
| 26 |
+
audio_folder = ""
|
| 27 |
+
video_folder = ""
|
| 28 |
+
|
| 29 |
+
# Read CSV file
|
| 30 |
+
csv_file = ''
|
| 31 |
+
try:
|
| 32 |
+
df = pd.read_csv(csv_file)
|
| 33 |
+
except Exception as e:
|
| 34 |
+
print(f"Error reading CSV file {csv_file}: {e}")
|
| 35 |
+
exit(1)
|
| 36 |
+
|
| 37 |
+
# Prepare output CSV and error log files
|
| 38 |
+
output_csv = 'output.csv'
|
| 39 |
+
error_log_file = 'test.log'
|
| 40 |
+
|
| 41 |
+
# Track processed files by reading existing output (if any)
|
| 42 |
+
processed_files = set()
|
| 43 |
+
if os.path.exists(output_csv):
|
| 44 |
+
try:
|
| 45 |
+
with open(output_csv, mode='r') as file:
|
| 46 |
+
reader = csv.reader(file)
|
| 47 |
+
for row in reader:
|
| 48 |
+
file_name = row[0] # Full filename
|
| 49 |
+
processed_files.add(file_name) # Record processed files
|
| 50 |
+
except Exception as e:
|
| 51 |
+
print(f"Error reading the output CSV file {output_csv}: {e}")
|
| 52 |
+
exit(1)
|
| 53 |
+
|
| 54 |
+
# Initialize lists for matched audio-video pairs
|
| 55 |
+
paired_audio_paths = []
|
| 56 |
+
paired_video_paths = []
|
| 57 |
+
|
| 58 |
+
# Open error log for writing
|
| 59 |
+
with open(error_log_file, mode='a') as error_log:
|
| 60 |
+
# Process each file_id, skipping already processed files
|
| 61 |
+
for file_id in df['file_id']:
|
| 62 |
+
audio_file = f"{file_id}.flac"
|
| 63 |
+
video_file = f"000040.jpg"
|
| 64 |
+
|
| 65 |
+
video_path = os.path.join(video_folder, file_id, video_file)
|
| 66 |
+
audio_path = os.path.join(audio_folder, audio_file)
|
| 67 |
+
|
| 68 |
+
# Get basenames without extensions
|
| 69 |
+
video_name = os.path.basename(video_path)
|
| 70 |
+
audio_name = os.path.basename(audio_path)
|
| 71 |
+
video_name_no_ext = os.path.splitext(video_name)[0]
|
| 72 |
+
audio_name_no_ext = os.path.splitext(audio_name)[0]
|
| 73 |
+
|
| 74 |
+
# Skip if already processed
|
| 75 |
+
if video_name_no_ext in processed_files or audio_name_no_ext in processed_files:
|
| 76 |
+
continue
|
| 77 |
+
|
| 78 |
+
# Validate file existence
|
| 79 |
+
if not os.path.exists(video_path):
|
| 80 |
+
error_log.write(f"Video directory not found: {video_path}\n")
|
| 81 |
+
continue
|
| 82 |
+
|
| 83 |
+
if not os.path.exists(audio_path):
|
| 84 |
+
error_log.write(f"Audio file not found: {audio_path}\n")
|
| 85 |
+
continue
|
| 86 |
+
|
| 87 |
+
paired_audio_paths.append(audio_path)
|
| 88 |
+
paired_video_paths.append(video_path)
|
| 89 |
+
|
| 90 |
+
print(f"Successfully matched {len(paired_audio_paths)} audio-video pairs.")
|
| 91 |
+
|
| 92 |
+
# Batch processing configuration
|
| 93 |
+
batch_size = 16
|
| 94 |
+
num_batches = len(paired_video_paths) // batch_size + 1
|
| 95 |
+
|
| 96 |
+
# Process and write results
|
| 97 |
+
try:
|
| 98 |
+
with open(output_csv, mode='a', newline='') as file:
|
| 99 |
+
writer = csv.writer(file)
|
| 100 |
+
|
| 101 |
+
with torch.no_grad():
|
| 102 |
+
for i in tqdm(range(num_batches), desc="Processing Batches"):
|
| 103 |
+
start_idx = i * batch_size
|
| 104 |
+
end_idx = min((i + 1) * batch_size, len(paired_video_paths))
|
| 105 |
+
|
| 106 |
+
# Get current batch paths
|
| 107 |
+
video_batch_paths = paired_video_paths[start_idx:end_idx]
|
| 108 |
+
audio_batch_paths = paired_audio_paths[start_idx:end_idx]
|
| 109 |
+
|
| 110 |
+
try:
|
| 111 |
+
# Load batch data
|
| 112 |
+
video_batch = data.load_and_transform_vision_data(video_batch_paths, device)
|
| 113 |
+
audio_batch = data.load_and_transform_audio_data(audio_batch_paths, device)
|
| 114 |
+
except RuntimeError as e:
|
| 115 |
+
print(f"Error loading video data in batch {i}: {e}")
|
| 116 |
+
continue
|
| 117 |
+
except Exception as e:
|
| 118 |
+
print(f"Unexpected error in batch {i}: {e}")
|
| 119 |
+
continue
|
| 120 |
+
|
| 121 |
+
try:
|
| 122 |
+
# Model inference
|
| 123 |
+
inputs = {
|
| 124 |
+
ModalityType.VISION: video_batch,
|
| 125 |
+
ModalityType.AUDIO: audio_batch,
|
| 126 |
+
}
|
| 127 |
+
|
| 128 |
+
embeddings = model(inputs)
|
| 129 |
+
|
| 130 |
+
# Calculate similarity
|
| 131 |
+
audio_embedding = embeddings[ModalityType.AUDIO]
|
| 132 |
+
video_embedding = embeddings[ModalityType.VISION]
|
| 133 |
+
batch_similarity = F.cosine_similarity(video_embedding, audio_embedding) * 10
|
| 134 |
+
|
| 135 |
+
# Write results
|
| 136 |
+
for video_path, similarity in zip(video_batch_paths, batch_similarity.tolist()):
|
| 137 |
+
video_name = os.path.basename(os.path.dirname(video_path))
|
| 138 |
+
writer.writerow([video_name, similarity])
|
| 139 |
+
except Exception as e:
|
| 140 |
+
print(f"Error processing batch {i}: {e}")
|
| 141 |
+
continue
|
| 142 |
+
except Exception as e:
|
| 143 |
+
print(f"Error writing to the output CSV file {output_csv}: {e}")
|
| 144 |
+
exit(1)
|
| 145 |
+
|
| 146 |
+
print(f"Similarity scores have been saved to {output_csv}.")
|
| 147 |
+
print(f"Any missing files have been logged in {error_log_file}.")
|
toolset/clean/SenseVoice/check_voice.py
ADDED
|
@@ -0,0 +1,81 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import os
|
| 2 |
+
import csv
|
| 3 |
+
from tqdm import tqdm # For progress bar display
|
| 4 |
+
from funasr import AutoModel
|
| 5 |
+
from funasr.utils.postprocess_utils import rich_transcription_postprocess
|
| 6 |
+
|
| 7 |
+
# Define model path
|
| 8 |
+
model_dir = "iic/SenseVoiceSmall"
|
| 9 |
+
|
| 10 |
+
# Initialize model
|
| 11 |
+
model = AutoModel(
|
| 12 |
+
model=model_dir,
|
| 13 |
+
trust_remote_code=True,
|
| 14 |
+
remote_code="./model.py",
|
| 15 |
+
vad_model="fsmn-vad",
|
| 16 |
+
vad_kwargs={"max_single_segment_time": 30000},
|
| 17 |
+
device="cuda:0",
|
| 18 |
+
)
|
| 19 |
+
|
| 20 |
+
# Define audio folder path
|
| 21 |
+
audio_folder = ""
|
| 22 |
+
|
| 23 |
+
# Output CSV file path
|
| 24 |
+
output_csv = "./recognition_results.csv"
|
| 25 |
+
|
| 26 |
+
# Get all .flac files in audio folder
|
| 27 |
+
audio_files = [f for f in os.listdir(audio_folder) if f.endswith(".flac")]
|
| 28 |
+
|
| 29 |
+
# Prepare CSV file and write header (if file is empty)
|
| 30 |
+
if not os.path.exists(output_csv) or os.path.getsize(output_csv) == 0:
|
| 31 |
+
with open(output_csv, mode="w", newline="", encoding="utf-8") as file:
|
| 32 |
+
writer = csv.writer(file)
|
| 33 |
+
writer.writerow(["Audio File", "Transcription"]) # CSV column headers
|
| 34 |
+
|
| 35 |
+
# Get existing processed audio files to avoid reprocessing
|
| 36 |
+
existing_files = set()
|
| 37 |
+
with open(output_csv, mode="r", newline="", encoding="utf-8") as file:
|
| 38 |
+
reader = csv.reader(file)
|
| 39 |
+
next(reader) # Skip header row
|
| 40 |
+
for row in reader:
|
| 41 |
+
existing_files.add(row[0]) # Add processed files to set
|
| 42 |
+
|
| 43 |
+
# Process all .flac files in audio folder
|
| 44 |
+
with open(output_csv, mode="a", newline="", encoding="utf-8") as file:
|
| 45 |
+
writer = csv.writer(file)
|
| 46 |
+
|
| 47 |
+
# Show progress bar using tqdm
|
| 48 |
+
for audio_file in tqdm(audio_files, desc="Processing", unit="file"):
|
| 49 |
+
# Skip if file already processed
|
| 50 |
+
if audio_file in existing_files:
|
| 51 |
+
continue
|
| 52 |
+
|
| 53 |
+
audio_path = os.path.join(audio_folder, audio_file)
|
| 54 |
+
|
| 55 |
+
try:
|
| 56 |
+
# Perform speech recognition
|
| 57 |
+
res = model.generate(
|
| 58 |
+
input=audio_path,
|
| 59 |
+
cache={},
|
| 60 |
+
language="auto", # Auto-detect language
|
| 61 |
+
use_itn=True,
|
| 62 |
+
batch_size_s=60,
|
| 63 |
+
merge_vad=True,
|
| 64 |
+
merge_length_s=15,
|
| 65 |
+
)
|
| 66 |
+
|
| 67 |
+
# Get transcription with post-processing
|
| 68 |
+
transcription = rich_transcription_postprocess(res[0]["text"])
|
| 69 |
+
|
| 70 |
+
# Mark as "none!" if transcription is empty
|
| 71 |
+
if not transcription.strip():
|
| 72 |
+
transcription = "none!"
|
| 73 |
+
|
| 74 |
+
except Exception as e:
|
| 75 |
+
# Record error if recognition fails
|
| 76 |
+
transcription = f"Error: {str(e)}"
|
| 77 |
+
|
| 78 |
+
# Write filename and transcription to CSV
|
| 79 |
+
writer.writerow([audio_file, transcription])
|
| 80 |
+
|
| 81 |
+
print("Recognition completed and saved to CSV.")
|
toolset/clean/requirements.txt
ADDED
|
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
funasr==1.1.16
|
| 2 |
+
imagebind==0.1.0
|
| 3 |
+
numpy==2.2.4
|
| 4 |
+
opencv_python==4.10.0.84
|
| 5 |
+
pandas==2.2.3
|
| 6 |
+
pydub==0.25.1
|
| 7 |
+
torch==1.13.1
|
| 8 |
+
tqdm==4.67.1
|
toolset/clean/silent/check_new_silent.py
ADDED
|
@@ -0,0 +1,69 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import os
|
| 2 |
+
import asyncio
|
| 3 |
+
from pydub import AudioSegment
|
| 4 |
+
from tqdm import tqdm
|
| 5 |
+
import numpy as np
|
| 6 |
+
|
| 7 |
+
# Async load single audio file
|
| 8 |
+
async def load_audio_file(audio_path):
|
| 9 |
+
try:
|
| 10 |
+
return AudioSegment.from_file(audio_path)
|
| 11 |
+
except Exception as e:
|
| 12 |
+
print(f"Error loading {audio_path}: {e}")
|
| 13 |
+
return None
|
| 14 |
+
|
| 15 |
+
# Detect if audio is silent
|
| 16 |
+
def is_silent(audio, silence_threshold=-35, chunk_size=20):
|
| 17 |
+
silence_count = 0
|
| 18 |
+
total_chunks = len(audio) // chunk_size
|
| 19 |
+
|
| 20 |
+
for i in range(total_chunks):
|
| 21 |
+
chunk = audio[i * chunk_size:(i + 1) * chunk_size]
|
| 22 |
+
|
| 23 |
+
# Convert multi-channel audio to numpy array and process each channel
|
| 24 |
+
channels = chunk.split_to_mono() # Split audio into mono channels
|
| 25 |
+
max_dbfs = float('-inf') # Initialize max value as negative infinity
|
| 26 |
+
|
| 27 |
+
for channel in channels:
|
| 28 |
+
# Get dBFS amplitude for each channel
|
| 29 |
+
max_dbfs = max(max_dbfs, channel.dBFS)
|
| 30 |
+
|
| 31 |
+
# Consider silent if max dBFS is below threshold
|
| 32 |
+
if max_dbfs < silence_threshold:
|
| 33 |
+
silence_count += 1
|
| 34 |
+
|
| 35 |
+
silence_ratio = silence_count / total_chunks
|
| 36 |
+
return silence_ratio > 0.9 # Mark as silent if over 90% is silent
|
| 37 |
+
|
| 38 |
+
# Process all audio files in directory
|
| 39 |
+
async def process_directory(directory_path, output_file, silence_threshold=-35.0, chunk_size=20):
|
| 40 |
+
audio_files = [f for f in os.listdir(directory_path) if f.endswith('.flac')]
|
| 41 |
+
audio_paths = [os.path.join(directory_path, f) for f in audio_files]
|
| 42 |
+
|
| 43 |
+
silent_files = []
|
| 44 |
+
|
| 45 |
+
# Process files in batches
|
| 46 |
+
batch_size = 16 # Process 16 files per batch
|
| 47 |
+
for i in tqdm(range(0, len(audio_paths), batch_size), desc="Processing batches"):
|
| 48 |
+
batch_audio_paths = audio_paths[i:i+batch_size]
|
| 49 |
+
# Async load current batch
|
| 50 |
+
audio_list = await asyncio.gather(*[load_audio_file(path) for path in batch_audio_paths])
|
| 51 |
+
|
| 52 |
+
# Process each audio file
|
| 53 |
+
for audio, audio_path in zip(audio_list, batch_audio_paths):
|
| 54 |
+
if audio and is_silent(audio, silence_threshold, chunk_size):
|
| 55 |
+
silent_files.append(os.path.basename(audio_path))
|
| 56 |
+
|
| 57 |
+
# Write silent files to output
|
| 58 |
+
with open(output_file, 'w') as out_file:
|
| 59 |
+
for file_name in silent_files:
|
| 60 |
+
out_file.write(f"{file_name}\n")
|
| 61 |
+
|
| 62 |
+
|
| 63 |
+
if __name__ == "__main__":
|
| 64 |
+
# Set paths
|
| 65 |
+
input_directory = ""
|
| 66 |
+
output_txt_file = ""
|
| 67 |
+
|
| 68 |
+
# Run async task
|
| 69 |
+
asyncio.run(process_directory(input_directory, output_txt_file))
|
toolset/clean/static/check_static_ffmpeg.py
ADDED
|
@@ -0,0 +1,121 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import cv2
|
| 2 |
+
import numpy as np
|
| 3 |
+
import os
|
| 4 |
+
from tqdm import tqdm
|
| 5 |
+
import re
|
| 6 |
+
import concurrent.futures
|
| 7 |
+
|
| 8 |
+
def get_video_duration(stderr_output):
|
| 9 |
+
"""Get the duration of a video using ffmpeg."""
|
| 10 |
+
ffmpeg_output = stderr_output
|
| 11 |
+
match = re.search(r"Duration: (\d{2}):(\d{2}):(\d{2})\.(\d{2})", ffmpeg_output, re.IGNORECASE)
|
| 12 |
+
if match:
|
| 13 |
+
hours = int(match.group(1))
|
| 14 |
+
minutes = int(match.group(2))
|
| 15 |
+
seconds = int(match.group(3))
|
| 16 |
+
milliseconds = int(match.group(4))
|
| 17 |
+
total_seconds = hours * 3600 + minutes * 60 + seconds + milliseconds / 100
|
| 18 |
+
return total_seconds
|
| 19 |
+
else:
|
| 20 |
+
print("Duration not found in ffmpeg output.")
|
| 21 |
+
return 0
|
| 22 |
+
|
| 23 |
+
def get_video_dimensions(stderr_output):
|
| 24 |
+
"""Extract video width and height from ffmpeg stderr output."""
|
| 25 |
+
match = re.search(r'(\d{3,4})x(\d{3,4})', stderr_output)
|
| 26 |
+
if match:
|
| 27 |
+
width = int(match.group(1))
|
| 28 |
+
height = int(match.group(2))
|
| 29 |
+
return width, height
|
| 30 |
+
return None, None
|
| 31 |
+
|
| 32 |
+
def get_video_fps(stderr_output):
|
| 33 |
+
"""Extract video frame rate from ffmpeg stderr output."""
|
| 34 |
+
match = re.search(r'(\d+(\.\d+)?) fps', stderr_output)
|
| 35 |
+
if match:
|
| 36 |
+
fps = float(match.group(1))
|
| 37 |
+
return fps
|
| 38 |
+
return None
|
| 39 |
+
|
| 40 |
+
def calculate_mse(frame1, frame2):
|
| 41 |
+
"""Calculate Mean Squared Error between two frames."""
|
| 42 |
+
frame1 = cv2.resize(frame1, (frame2.shape[1], frame2.shape[0])) # Ensure consistent dimensions
|
| 43 |
+
mse = np.sum((frame1 - frame2) ** 2) / float(frame1.size) # Compute MSE
|
| 44 |
+
return mse
|
| 45 |
+
|
| 46 |
+
def is_static(mse, threshold=5): # Using slightly lower threshold
|
| 47 |
+
"""Determine if frame is static based on MSE threshold."""
|
| 48 |
+
return mse < threshold # Frame considered static if MSE below threshold
|
| 49 |
+
|
| 50 |
+
def load_frame(frame_path):
|
| 51 |
+
"""Load a frame and convert to grayscale."""
|
| 52 |
+
frame = cv2.imread(frame_path)
|
| 53 |
+
if frame is None:
|
| 54 |
+
return None # Return None if frame loading fails
|
| 55 |
+
return cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
|
| 56 |
+
|
| 57 |
+
def detect_static_video(frame_path, frame_count=20):
|
| 58 |
+
"""Detect if video is static by analyzing frame differences."""
|
| 59 |
+
try:
|
| 60 |
+
static_frame_count = 0
|
| 61 |
+
sample_count = 0
|
| 62 |
+
|
| 63 |
+
# Generate frame file paths
|
| 64 |
+
frame_paths = [os.path.join(frame_path, f'{frame_index*4:06d}.jpg')
|
| 65 |
+
for frame_index in range(1, frame_count + 1)]
|
| 66 |
+
|
| 67 |
+
# Parallel frame loading using multithreading
|
| 68 |
+
with concurrent.futures.ThreadPoolExecutor() as executor:
|
| 69 |
+
frames = list(executor.map(load_frame, frame_paths))
|
| 70 |
+
|
| 71 |
+
# Filter out failed frame loads
|
| 72 |
+
frames = [frame for frame in frames if frame is not None]
|
| 73 |
+
|
| 74 |
+
# Require minimum 2 frames for analysis
|
| 75 |
+
if len(frames) < 2:
|
| 76 |
+
return False # Insufficient frames for static detection
|
| 77 |
+
|
| 78 |
+
# Count static frames
|
| 79 |
+
prev_frame = frames[0]
|
| 80 |
+
for gray_frame in frames[1:]:
|
| 81 |
+
mse = calculate_mse(prev_frame, gray_frame)
|
| 82 |
+
if is_static(mse):
|
| 83 |
+
static_frame_count += 1
|
| 84 |
+
prev_frame = gray_frame # Update previous frame
|
| 85 |
+
|
| 86 |
+
# Calculate static frame ratio
|
| 87 |
+
sample_count = len(frames) # Actual processed frame count
|
| 88 |
+
static_ratio = static_frame_count / sample_count if sample_count > 0 else 0
|
| 89 |
+
|
| 90 |
+
# Video considered static if >85% frames are static
|
| 91 |
+
return static_ratio > 0.85
|
| 92 |
+
|
| 93 |
+
except Exception as e:
|
| 94 |
+
print(f"Error processing video: {frame_path}, Error: {e}")
|
| 95 |
+
return None # Return None to indicate error
|
| 96 |
+
|
| 97 |
+
def process_video_folder(folder_path, output_file, error_log):
|
| 98 |
+
"""Batch process video folders for static detection."""
|
| 99 |
+
video_files = [f for f in os.listdir(folder_path)
|
| 100 |
+
if re.search(r'^[a-zA-Z0-9_-]*_.\d*0$', f)]
|
| 101 |
+
|
| 102 |
+
with open(output_file, 'w') as output:
|
| 103 |
+
for idx, video_file in enumerate(tqdm(video_files, desc="Processing Videos", unit="file")):
|
| 104 |
+
frame_path = os.path.join(folder_path, video_file)
|
| 105 |
+
result = detect_static_video(frame_path)
|
| 106 |
+
|
| 107 |
+
if result is None:
|
| 108 |
+
# Log failed processing attempts
|
| 109 |
+
with open(error_log, 'a') as error_output:
|
| 110 |
+
error_output.write(f"Error processing: {video_file}\n")
|
| 111 |
+
elif result:
|
| 112 |
+
output.write(f"{video_file}\n") # Record static video filename
|
| 113 |
+
print(f"{video_file} is static")
|
| 114 |
+
|
| 115 |
+
# Example usage
|
| 116 |
+
if __name__ == "__main__":
|
| 117 |
+
folder_path = '' # Video frame directory
|
| 118 |
+
output_file = './static_new.txt' # Static video output list
|
| 119 |
+
error_log = './static_new_err.txt' # Error log file
|
| 120 |
+
|
| 121 |
+
process_video_folder(folder_path, output_file, error_log)
|
toolset/crawl/channel/channel_analyzer.py
ADDED
|
@@ -0,0 +1,127 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import csv
|
| 2 |
+
import os
|
| 3 |
+
from collections import Counter
|
| 4 |
+
from itertools import islice
|
| 5 |
+
import sys
|
| 6 |
+
sys.path.append('..')
|
| 7 |
+
from core import build
|
| 8 |
+
|
| 9 |
+
youtube = build.build_youtube()
|
| 10 |
+
|
| 11 |
+
def batch(iterable, size):
|
| 12 |
+
"""
|
| 13 |
+
Split an iterable into chunks of specified size.
|
| 14 |
+
"""
|
| 15 |
+
it = iter(iterable)
|
| 16 |
+
while True:
|
| 17 |
+
chunk = list(islice(it, size))
|
| 18 |
+
if not chunk:
|
| 19 |
+
break
|
| 20 |
+
yield chunk
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
def get_channel_info_batch(video_ids):
|
| 24 |
+
"""
|
| 25 |
+
Batch retrieve channel IDs and names using video IDs.
|
| 26 |
+
"""
|
| 27 |
+
channel_info = []
|
| 28 |
+
try:
|
| 29 |
+
response = (
|
| 30 |
+
youtube.videos()
|
| 31 |
+
.list(part="snippet", id=",".join(video_ids))
|
| 32 |
+
.execute()
|
| 33 |
+
)
|
| 34 |
+
for item in response.get("items", []):
|
| 35 |
+
snippet = item["snippet"]
|
| 36 |
+
channel_info.append((snippet["channelId"], snippet["channelTitle"]))
|
| 37 |
+
except Exception as e:
|
| 38 |
+
print(f"Error fetching data for video_ids {video_ids}: {e}")
|
| 39 |
+
return channel_info
|
| 40 |
+
|
| 41 |
+
|
| 42 |
+
def process_single_csv(input_file):
|
| 43 |
+
"""
|
| 44 |
+
Process a single CSV file to:
|
| 45 |
+
1. Extract video IDs
|
| 46 |
+
2. Query YouTube API for channel info
|
| 47 |
+
3. Count channel occurrences
|
| 48 |
+
4. Return sorted results
|
| 49 |
+
"""
|
| 50 |
+
video_ids = []
|
| 51 |
+
with open(input_file, "r", encoding="utf-8") as infile:
|
| 52 |
+
reader = csv.DictReader(infile)
|
| 53 |
+
for row in reader:
|
| 54 |
+
video_ids.append(row["video_id"]) # Assuming CSV has video_id column
|
| 55 |
+
|
| 56 |
+
# Batch process channel info
|
| 57 |
+
channel_counter = Counter()
|
| 58 |
+
channel_details = {}
|
| 59 |
+
|
| 60 |
+
for video_batch in batch(video_ids, 50): # Process 50 video IDs per batch
|
| 61 |
+
channel_info_batch = get_channel_info_batch(video_batch)
|
| 62 |
+
for channel_id, channel_title in channel_info_batch:
|
| 63 |
+
channel_counter[channel_id] += 1
|
| 64 |
+
channel_details[channel_id] = channel_title
|
| 65 |
+
|
| 66 |
+
# Sort by occurrence count
|
| 67 |
+
sorted_channels = channel_counter.most_common()
|
| 68 |
+
|
| 69 |
+
return sorted_channels, channel_details
|
| 70 |
+
|
| 71 |
+
|
| 72 |
+
def process_folder(folder_path, output_file):
|
| 73 |
+
"""
|
| 74 |
+
Process all CSV files in a folder to:
|
| 75 |
+
1. Aggregate video IDs
|
| 76 |
+
2. Collect channel statistics
|
| 77 |
+
3. Merge results
|
| 78 |
+
4. Output sorted results to CSV
|
| 79 |
+
"""
|
| 80 |
+
all_channel_counter = Counter()
|
| 81 |
+
all_channel_details = {}
|
| 82 |
+
|
| 83 |
+
# Process each CSV file in folder
|
| 84 |
+
for filename in os.listdir(folder_path):
|
| 85 |
+
if filename.endswith(".csv"):
|
| 86 |
+
input_file = os.path.join(folder_path, filename)
|
| 87 |
+
print(f"Processing file: {input_file}")
|
| 88 |
+
|
| 89 |
+
# Process individual CSV
|
| 90 |
+
sorted_channels, channel_details = process_single_csv(input_file)
|
| 91 |
+
|
| 92 |
+
# Aggregate results
|
| 93 |
+
for channel_id, count in sorted_channels:
|
| 94 |
+
all_channel_counter[channel_id] += count
|
| 95 |
+
all_channel_details.update(channel_details)
|
| 96 |
+
|
| 97 |
+
# Write final results to CSV
|
| 98 |
+
with open(output_file, "w", encoding="utf-8", newline="") as outfile:
|
| 99 |
+
writer = csv.writer(outfile, quotechar='"', quoting=csv.QUOTE_ALL)
|
| 100 |
+
writer.writerow(["channel_id", "channel_name", "count"])
|
| 101 |
+
for channel_id, count in all_channel_counter.most_common():
|
| 102 |
+
writer.writerow(
|
| 103 |
+
[channel_id, all_channel_details[channel_id], count]
|
| 104 |
+
)
|
| 105 |
+
|
| 106 |
+
|
| 107 |
+
# Example execution
|
| 108 |
+
if __name__ == "__main__":
|
| 109 |
+
import argparse
|
| 110 |
+
|
| 111 |
+
parser = argparse.ArgumentParser()
|
| 112 |
+
parser.add_argument(
|
| 113 |
+
"-i",
|
| 114 |
+
"--input-dir",
|
| 115 |
+
help="Path to folder containing CSV files",
|
| 116 |
+
required=True,
|
| 117 |
+
)
|
| 118 |
+
parser.add_argument(
|
| 119 |
+
"-o",
|
| 120 |
+
"--output-csv",
|
| 121 |
+
help="Output CSV file path",
|
| 122 |
+
default="output.csv",
|
| 123 |
+
)
|
| 124 |
+
args = parser.parse_args()
|
| 125 |
+
folder_path = args.input_dir # CSV files directory
|
| 126 |
+
output_csv = args.output_csv # Output file path
|
| 127 |
+
process_folder(folder_path, output_csv)
|
toolset/crawl/channel/get_channel_vids.py
ADDED
|
@@ -0,0 +1,80 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""
|
| 2 |
+
Retrieve all 360-degree video IDs from channels with count >= threshold,
|
| 3 |
+
and output to corresponding directory.
|
| 4 |
+
"""
|
| 5 |
+
import os
|
| 6 |
+
import sys
|
| 7 |
+
import csv
|
| 8 |
+
from tqdm import tqdm
|
| 9 |
+
sys.path.append("..")
|
| 10 |
+
from core import build, channel
|
| 11 |
+
|
| 12 |
+
if __name__ == "__main__":
|
| 13 |
+
# Argument parsing
|
| 14 |
+
parser = argparse.ArgumentParser(
|
| 15 |
+
description="Extract 360-degree videos from qualified channels"
|
| 16 |
+
)
|
| 17 |
+
parser.add_argument(
|
| 18 |
+
"-i", "--input-csv",
|
| 19 |
+
type=str,
|
| 20 |
+
required=True,
|
| 21 |
+
help="Input CSV file containing channel statistics"
|
| 22 |
+
)
|
| 23 |
+
parser.add_argument(
|
| 24 |
+
"-o", "--output-dir",
|
| 25 |
+
type=str,
|
| 26 |
+
required=True,
|
| 27 |
+
help="Output directory for video ID files"
|
| 28 |
+
)
|
| 29 |
+
parser.add_argument(
|
| 30 |
+
"-t", "--threshold",
|
| 31 |
+
type=int,
|
| 32 |
+
default=3,
|
| 33 |
+
help="Minimum count threshold for channel inclusion"
|
| 34 |
+
)
|
| 35 |
+
parser.add_argument(
|
| 36 |
+
"-d", "--database",
|
| 37 |
+
type=str,
|
| 38 |
+
default=None,
|
| 39 |
+
help="Optional database CSV for channel filtering"
|
| 40 |
+
)
|
| 41 |
+
args = parser.parse_args()
|
| 42 |
+
|
| 43 |
+
# Initialize YouTube API client
|
| 44 |
+
youtube = build.build_youtube()
|
| 45 |
+
os.makedirs(args.output_dir, exist_ok=True)
|
| 46 |
+
|
| 47 |
+
# Load database channel IDs if provided
|
| 48 |
+
database = set()
|
| 49 |
+
if args.database:
|
| 50 |
+
with open(args.database, "r") as f:
|
| 51 |
+
reader = csv.DictReader(f)
|
| 52 |
+
database = {row["channel_id"] for row in reader}
|
| 53 |
+
|
| 54 |
+
# Filter channels by threshold and database
|
| 55 |
+
qualified_channels = []
|
| 56 |
+
with open(args.input_csv, "r") as f:
|
| 57 |
+
reader = csv.DictReader(f)
|
| 58 |
+
for row in reader:
|
| 59 |
+
if int(row["count"]) >= args.threshold:
|
| 60 |
+
if row["channel_id"] not in database:
|
| 61 |
+
qualified_channels.append(row["channel_id"])
|
| 62 |
+
else:
|
| 63 |
+
print(f"Skipping {row['channel_name']}[{row['channel_id']}]")
|
| 64 |
+
|
| 65 |
+
# Process qualified channels
|
| 66 |
+
for channel_id in tqdm(qualified_channels, desc="Processing channels"):
|
| 67 |
+
output_file = os.path.join(args.output_dir, f"{channel_id}.csv")
|
| 68 |
+
|
| 69 |
+
# Skip if already processed
|
| 70 |
+
if os.path.exists(output_file):
|
| 71 |
+
print(f"Skipping existing: {channel_id}")
|
| 72 |
+
continue
|
| 73 |
+
|
| 74 |
+
# Get 360-degree video IDs
|
| 75 |
+
video_ids = channel.get_channel_video_ids_360(youtube, channel_id)
|
| 76 |
+
|
| 77 |
+
# Write to CSV
|
| 78 |
+
with open(output_file, "w") as f:
|
| 79 |
+
f.write("video_id\n")
|
| 80 |
+
f.writelines(f"{vid}\n" for vid in video_ids)
|
toolset/crawl/channel/get_channels_vids.py
ADDED
|
@@ -0,0 +1,52 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""
|
| 2 |
+
Collect all 360-degree video IDs from specified channels and output to CSV
|
| 3 |
+
"""
|
| 4 |
+
import os
|
| 5 |
+
import sys
|
| 6 |
+
import csv
|
| 7 |
+
import argparse
|
| 8 |
+
from tqdm import tqdm
|
| 9 |
+
|
| 10 |
+
sys.path.append("..")
|
| 11 |
+
import core
|
| 12 |
+
from core import build, channel
|
| 13 |
+
|
| 14 |
+
if __name__ == "__main__":
|
| 15 |
+
# Set up argument parser
|
| 16 |
+
parser = argparse.ArgumentParser(
|
| 17 |
+
description="Collect 360-degree videos from YouTube channels"
|
| 18 |
+
)
|
| 19 |
+
parser.add_argument(
|
| 20 |
+
"-i", "--input-csv",
|
| 21 |
+
type=str,
|
| 22 |
+
required=True,
|
| 23 |
+
help="Input CSV file containing channel IDs"
|
| 24 |
+
)
|
| 25 |
+
parser.add_argument(
|
| 26 |
+
"-o", "--output-csv",
|
| 27 |
+
type=str,
|
| 28 |
+
required=True,
|
| 29 |
+
help="Output CSV file for 360-degree video IDs"
|
| 30 |
+
)
|
| 31 |
+
args = parser.parse_args()
|
| 32 |
+
|
| 33 |
+
# Initialize YouTube API client
|
| 34 |
+
youtube = build.build_youtube()
|
| 35 |
+
|
| 36 |
+
# Get channel IDs from input file
|
| 37 |
+
channel_ids = core.filelist.get_channel_ids(args.input_csv)
|
| 38 |
+
|
| 39 |
+
# Collect all 360-degree video IDs
|
| 40 |
+
video_ids = []
|
| 41 |
+
for channel_id in tqdm(channel_ids, desc="Processing channels"):
|
| 42 |
+
cur_video_ids = channel.get_channel_video_ids_360(youtube, channel_id)
|
| 43 |
+
print(f"Channel {channel_id}: Found {len(cur_video_ids)} 360-degree videos")
|
| 44 |
+
video_ids.extend(cur_video_ids)
|
| 45 |
+
|
| 46 |
+
# Write results to CSV
|
| 47 |
+
with open(args.output_csv, "w", newline="", encoding="utf-8") as f:
|
| 48 |
+
writer = csv.writer(f)
|
| 49 |
+
writer.writerow(["video_id"])
|
| 50 |
+
writer.writerows([[vid] for vid in video_ids])
|
| 51 |
+
|
| 52 |
+
print(f"\nCompleted. Saved {len(video_ids)} 360-degree video IDs to {args.output_csv}")
|
toolset/crawl/channel/get_test_list.py
ADDED
|
@@ -0,0 +1,79 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import os
|
| 2 |
+
import pandas as pd
|
| 3 |
+
import random
|
| 4 |
+
import argparse
|
| 5 |
+
|
| 6 |
+
def process_csv(input_folder, output_folder, sample_size=10):
|
| 7 |
+
"""
|
| 8 |
+
Process CSV files in the input folder and randomly select a specified number of video_ids.
|
| 9 |
+
|
| 10 |
+
Args:
|
| 11 |
+
input_folder: Path to folder containing input CSV files
|
| 12 |
+
output_folder: Path to folder where processed files will be saved
|
| 13 |
+
sample_size: Number of video_ids to randomly select (default: 10)
|
| 14 |
+
"""
|
| 15 |
+
# Get all CSV files in input folder
|
| 16 |
+
csv_files = [f for f in os.listdir(input_folder) if f.endswith('.csv')]
|
| 17 |
+
|
| 18 |
+
# Process each CSV file
|
| 19 |
+
for csv_file in csv_files:
|
| 20 |
+
# Build input and output file paths
|
| 21 |
+
input_file_path = os.path.join(input_folder, csv_file)
|
| 22 |
+
output_file_path = os.path.join(output_folder, csv_file)
|
| 23 |
+
|
| 24 |
+
# Read CSV file
|
| 25 |
+
df = pd.read_csv(input_file_path)
|
| 26 |
+
|
| 27 |
+
# Check if 'video_id' column exists
|
| 28 |
+
if 'video_id' not in df.columns:
|
| 29 |
+
print(f"Warning: 'video_id' column not found in {csv_file}. Skipping...")
|
| 30 |
+
continue
|
| 31 |
+
|
| 32 |
+
# Randomly select specified number of video_ids
|
| 33 |
+
all_video_ids = df['video_id'].tolist()
|
| 34 |
+
if len(all_video_ids) > sample_size:
|
| 35 |
+
selected_video_ids = random.sample(all_video_ids, sample_size)
|
| 36 |
+
else:
|
| 37 |
+
selected_video_ids = all_video_ids
|
| 38 |
+
|
| 39 |
+
selected_file_ids = [video_id + '_5' for video_id in selected_video_ids]
|
| 40 |
+
|
| 41 |
+
# Create new DataFrame with selected file_ids
|
| 42 |
+
selected_df = pd.DataFrame({'file_id': selected_file_ids})
|
| 43 |
+
|
| 44 |
+
# Save results to output folder
|
| 45 |
+
selected_df.to_csv(output_file_path, index=False)
|
| 46 |
+
|
| 47 |
+
print(f"Processed {csv_file}, selected {len(selected_video_ids)} video_ids, saved to {output_file_path}")
|
| 48 |
+
|
| 49 |
+
def main():
|
| 50 |
+
# Create argument parser
|
| 51 |
+
parser = argparse.ArgumentParser(
|
| 52 |
+
description="Process CSV files and randomly select video_ids."
|
| 53 |
+
)
|
| 54 |
+
|
| 55 |
+
# Add command line arguments
|
| 56 |
+
parser.add_argument('-i', '--input-folder',
|
| 57 |
+
type=str,
|
| 58 |
+
help="Input folder containing CSV files",
|
| 59 |
+
required=True)
|
| 60 |
+
parser.add_argument('-o', '--output-folder',
|
| 61 |
+
type=str,
|
| 62 |
+
help="Output folder to save the result CSV files",
|
| 63 |
+
required=True)
|
| 64 |
+
parser.add_argument('-n', '--sample-size',
|
| 65 |
+
type=int,
|
| 66 |
+
default=10,
|
| 67 |
+
help="Number of video_ids to randomly select (default: 10)")
|
| 68 |
+
|
| 69 |
+
# Parse arguments
|
| 70 |
+
args = parser.parse_args()
|
| 71 |
+
|
| 72 |
+
# Create output folder if it doesn't exist
|
| 73 |
+
os.makedirs(args.output_folder, exist_ok=True)
|
| 74 |
+
|
| 75 |
+
# Process CSV files
|
| 76 |
+
process_csv(args.input_folder, args.output_folder, args.sample_size)
|
| 77 |
+
|
| 78 |
+
if __name__ == '__main__':
|
| 79 |
+
main()
|
toolset/crawl/core/__init__.py
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
from . import build, filters, channel, search, filelist
|
toolset/crawl/core/build.py
ADDED
|
@@ -0,0 +1,43 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
from googleapiclient.discovery import build
|
| 2 |
+
import os
|
| 3 |
+
import requests
|
| 4 |
+
from googleapiclient.http import HttpRequest
|
| 5 |
+
import httplib2
|
| 6 |
+
|
| 7 |
+
__API_KEY = "YOUR_YOUTUBE_API_KEY_HERE" # Enter your YouTube API key here
|
| 8 |
+
|
| 9 |
+
def build_youtube(api_key=None, proxy_host=None, proxy_port=None):
|
| 10 |
+
"""Initialize and configure the YouTube API client
|
| 11 |
+
|
| 12 |
+
Args:
|
| 13 |
+
api_key (str, optional): YouTube Data API key. Uses default if not provided.
|
| 14 |
+
proxy_host (str, optional): Proxy server host address
|
| 15 |
+
proxy_port (int, optional): Proxy server port number
|
| 16 |
+
|
| 17 |
+
Returns:
|
| 18 |
+
googleapiclient.discovery.Resource: Configured YouTube API client instance
|
| 19 |
+
"""
|
| 20 |
+
if api_key is None:
|
| 21 |
+
api_key = __API_KEY
|
| 22 |
+
|
| 23 |
+
# Configure proxy settings
|
| 24 |
+
http = httplib2.Http(
|
| 25 |
+
proxy_info=httplib2.ProxyInfo(
|
| 26 |
+
proxy_type=httplib2.socks.PROXY_TYPE_HTTP,
|
| 27 |
+
proxy_host=proxy_host,
|
| 28 |
+
proxy_port=proxy_port,
|
| 29 |
+
)
|
| 30 |
+
)
|
| 31 |
+
|
| 32 |
+
YOUTUBE_API_SERVICE_NAME = "youtube"
|
| 33 |
+
YOUTUBE_API_VERSION = "v3"
|
| 34 |
+
|
| 35 |
+
# Initialize YouTube API client
|
| 36 |
+
youtube = build(
|
| 37 |
+
YOUTUBE_API_SERVICE_NAME,
|
| 38 |
+
YOUTUBE_API_VERSION,
|
| 39 |
+
developerKey=api_key,
|
| 40 |
+
http=http,
|
| 41 |
+
)
|
| 42 |
+
|
| 43 |
+
return youtube
|
toolset/crawl/core/channel.py
ADDED
|
@@ -0,0 +1,91 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import os
|
| 2 |
+
import json
|
| 3 |
+
|
| 4 |
+
|
| 5 |
+
def get_channel_video_ids(youtube, channel_id, output_tmp=False):
|
| 6 |
+
"""
|
| 7 |
+
Retrieve all video IDs from a specified YouTube channel.
|
| 8 |
+
|
| 9 |
+
Args:
|
| 10 |
+
youtube: Initialized YouTube API client
|
| 11 |
+
channel_id: YouTube channel ID
|
| 12 |
+
output_tmp: Whether to save temporary JSON outputs
|
| 13 |
+
Returns:
|
| 14 |
+
List of video IDs
|
| 15 |
+
"""
|
| 16 |
+
video_ids = []
|
| 17 |
+
|
| 18 |
+
# Get channel's upload playlist ID
|
| 19 |
+
request = youtube.channels().list(part="contentDetails", id=channel_id)
|
| 20 |
+
response = request.execute()
|
| 21 |
+
|
| 22 |
+
if output_tmp:
|
| 23 |
+
os.makedirs("tmp", exist_ok=True)
|
| 24 |
+
with open("tmp/get_playlist.json", "w", encoding="utf-8") as f:
|
| 25 |
+
json.dump(response, f, indent=2)
|
| 26 |
+
|
| 27 |
+
upload_playlist_id = response["items"][0]["contentDetails"][
|
| 28 |
+
"relatedPlaylists"
|
| 29 |
+
]["uploads"]
|
| 30 |
+
|
| 31 |
+
# Get all videos from upload playlist
|
| 32 |
+
next_page_token = None
|
| 33 |
+
while True:
|
| 34 |
+
playlist_request = youtube.playlistItems().list(
|
| 35 |
+
part="snippet",
|
| 36 |
+
playlistId=upload_playlist_id,
|
| 37 |
+
maxResults=50, # Max 50 videos per request
|
| 38 |
+
pageToken=next_page_token,
|
| 39 |
+
)
|
| 40 |
+
|
| 41 |
+
playlist_response = playlist_request.execute()
|
| 42 |
+
|
| 43 |
+
if output_tmp:
|
| 44 |
+
token_str = next_page_token if next_page_token else "first_page"
|
| 45 |
+
with open(
|
| 46 |
+
f"tmp/get_video_next_{token_str}.json",
|
| 47 |
+
"w",
|
| 48 |
+
encoding="utf-8",
|
| 49 |
+
) as f:
|
| 50 |
+
json.dump(playlist_response, f, indent=2)
|
| 51 |
+
|
| 52 |
+
# Extract video IDs
|
| 53 |
+
for item in playlist_response["items"]:
|
| 54 |
+
video_ids.append(item["snippet"]["resourceId"]["videoId"])
|
| 55 |
+
|
| 56 |
+
# Check for more pages
|
| 57 |
+
next_page_token = playlist_response.get("nextPageToken")
|
| 58 |
+
if not next_page_token:
|
| 59 |
+
break
|
| 60 |
+
|
| 61 |
+
return video_ids
|
| 62 |
+
|
| 63 |
+
|
| 64 |
+
def get_channel_video_ids_360(youtube, channel_id, output_tmp=False):
|
| 65 |
+
"""Get only 360-degree video IDs from a channel"""
|
| 66 |
+
from . import filters
|
| 67 |
+
|
| 68 |
+
video_ids = get_channel_video_ids(youtube, channel_id, output_tmp)
|
| 69 |
+
return filters.filter_360(youtube, video_ids, output_tmp)
|
| 70 |
+
|
| 71 |
+
|
| 72 |
+
if __name__ == "__main__":
|
| 73 |
+
import argparse
|
| 74 |
+
|
| 75 |
+
parser = argparse.ArgumentParser(
|
| 76 |
+
description="Retrieve video IDs from YouTube channel"
|
| 77 |
+
)
|
| 78 |
+
parser.add_argument(
|
| 79 |
+
"--channel-id",
|
| 80 |
+
type=str,
|
| 81 |
+
required=True,
|
| 82 |
+
help="YouTube channel ID to process"
|
| 83 |
+
)
|
| 84 |
+
args = parser.parse_args()
|
| 85 |
+
|
| 86 |
+
import build
|
| 87 |
+
youtube = build.build_youtube()
|
| 88 |
+
|
| 89 |
+
# Test functionality
|
| 90 |
+
video_ids = get_channel_video_ids(youtube, args.channel_id, True)
|
| 91 |
+
print(video_ids)
|
toolset/crawl/core/download/__init__.py
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
from . import download_list
|
toolset/crawl/core/download/download_list.py
ADDED
|
@@ -0,0 +1,1073 @@
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|
| 1 |
+
import csv
|
| 2 |
+
import os
|
| 3 |
+
from tqdm import tqdm
|
| 4 |
+
import subprocess
|
| 5 |
+
import sys
|
| 6 |
+
from multiprocessing import Pool, Lock
|
| 7 |
+
from typing import List, Dict, Any, Optional
|
| 8 |
+
|
| 9 |
+
|
| 10 |
+
class DownloadError(Exception):
|
| 11 |
+
def __init__(self, args: Dict[str, Any]):
|
| 12 |
+
self.items = args["items"]
|
| 13 |
+
self.result = args["result"]
|
| 14 |
+
|
| 15 |
+
|
| 16 |
+
def _check_size(check_files: List[str], size=1024, remove: bool = True):
|
| 17 |
+
"""
|
| 18 |
+
check if all files is larger than the limit,
|
| 19 |
+
:param remove: if True, remove files that less than that size.
|
| 20 |
+
"""
|
| 21 |
+
|
| 22 |
+
check_success = True
|
| 23 |
+
for file_name in check_files:
|
| 24 |
+
if not os.path.exists(file_name):
|
| 25 |
+
check_success = False
|
| 26 |
+
continue
|
| 27 |
+
if os.path.getsize(file_name) < size:
|
| 28 |
+
check_success = False
|
| 29 |
+
if remove:
|
| 30 |
+
os.remove(file_name)
|
| 31 |
+
else:
|
| 32 |
+
break
|
| 33 |
+
return check_success
|
| 34 |
+
|
| 35 |
+
def download_video_process(args: Dict):
|
| 36 |
+
return download_video(**args)
|
| 37 |
+
|
| 38 |
+
|
| 39 |
+
def download_video_segments_process(args: Dict):
|
| 40 |
+
return download_video_segments(**args)
|
| 41 |
+
|
| 42 |
+
|
| 43 |
+
def download_4ch_segments_process(args: Dict):
|
| 44 |
+
return download_4ch_segments(**args)
|
| 45 |
+
|
| 46 |
+
def download_360_segments_process(args: Dict):
|
| 47 |
+
return download_360_segments(**args)
|
| 48 |
+
|
| 49 |
+
def download_360_process(args: Dict):
|
| 50 |
+
return download_360(**args)
|
| 51 |
+
|
| 52 |
+
def download_video(
|
| 53 |
+
video_id: str,
|
| 54 |
+
output_folder: str,
|
| 55 |
+
ext: str = None,
|
| 56 |
+
proxy: str = None,
|
| 57 |
+
try_time: int = 2,
|
| 58 |
+
format_code: str = "bv+ba",
|
| 59 |
+
check_size: bool = True,
|
| 60 |
+
skip_exists: bool = True,
|
| 61 |
+
time_out: int = 30,
|
| 62 |
+
) -> List[str]:
|
| 63 |
+
"""
|
| 64 |
+
:param skip_exists: whether to skip the existing files. If True, ext should be specified.
|
| 65 |
+
:param ext: extension of the output file without dot.
|
| 66 |
+
:return: List of success file_ids
|
| 67 |
+
"""
|
| 68 |
+
# Check format code with ext
|
| 69 |
+
if ext is not None:
|
| 70 |
+
if format_code.find("[ext=") != -1:
|
| 71 |
+
if format_code.find(f"[ext={ext}]") == -1:
|
| 72 |
+
raise ValueError(
|
| 73 |
+
f"Format code {format_code} does not match the extension {ext}"
|
| 74 |
+
)
|
| 75 |
+
else:
|
| 76 |
+
format_code += f"[ext={ext}]"
|
| 77 |
+
|
| 78 |
+
file_items = [video_id]
|
| 79 |
+
file_path_base = os.path.join(output_folder, video_id)
|
| 80 |
+
if skip_exists:
|
| 81 |
+
if ext is None:
|
| 82 |
+
raise ValueError("ext should be specified when skip_exists is True")
|
| 83 |
+
if os.path.exists(file_path_base + "." + ext):
|
| 84 |
+
print(f"{video_id} already exists")
|
| 85 |
+
return file_items
|
| 86 |
+
|
| 87 |
+
# specify command
|
| 88 |
+
cmd = [
|
| 89 |
+
"yt-dlp",
|
| 90 |
+
"-f",
|
| 91 |
+
format_code,
|
| 92 |
+
f"https://www.youtube.com/watch?v={video_id}",
|
| 93 |
+
"-o",
|
| 94 |
+
f"{file_path_base}.%(ext)s",
|
| 95 |
+
"--socket-timeout",
|
| 96 |
+
str(time_out),
|
| 97 |
+
"--abort-on-error",
|
| 98 |
+
"--abort-on-unavailable-fragments",
|
| 99 |
+
"-N",
|
| 100 |
+
"4",
|
| 101 |
+
]
|
| 102 |
+
|
| 103 |
+
if proxy is not None:
|
| 104 |
+
cmd += ["--proxy", proxy]
|
| 105 |
+
|
| 106 |
+
try_id = 0
|
| 107 |
+
success = False
|
| 108 |
+
result = None
|
| 109 |
+
while try_id < try_time and not success:
|
| 110 |
+
print(f"Downloading video {video_id}...")
|
| 111 |
+
result = subprocess.run(
|
| 112 |
+
cmd,
|
| 113 |
+
capture_output=True,
|
| 114 |
+
text=True,
|
| 115 |
+
)
|
| 116 |
+
# result = subprocess.run(cmd)
|
| 117 |
+
if result.returncode == 0:
|
| 118 |
+
if check_size:
|
| 119 |
+
file_names = [
|
| 120 |
+
os.path.join(output_folder, file_item + "." + ext)
|
| 121 |
+
for file_item in file_items
|
| 122 |
+
]
|
| 123 |
+
success = _check_size(file_names, remove=True)
|
| 124 |
+
else:
|
| 125 |
+
success = True
|
| 126 |
+
if not success:
|
| 127 |
+
print(
|
| 128 |
+
f"[WARNING] Failed to download video items {video_id}, retrying...({try_id + 1}/{try_time})"
|
| 129 |
+
)
|
| 130 |
+
try_id += 1
|
| 131 |
+
|
| 132 |
+
if not success:
|
| 133 |
+
raise DownloadError(
|
| 134 |
+
{
|
| 135 |
+
"items": file_items,
|
| 136 |
+
"result": result,
|
| 137 |
+
}
|
| 138 |
+
)
|
| 139 |
+
return file_items
|
| 140 |
+
|
| 141 |
+
|
| 142 |
+
def download_4ch_segments(
|
| 143 |
+
video_id: str,
|
| 144 |
+
output_folder: str,
|
| 145 |
+
start_times: List[int],
|
| 146 |
+
time_interval: int = 10,
|
| 147 |
+
proxy: str = None,
|
| 148 |
+
try_time: int = 4,
|
| 149 |
+
check_size: bool = True,
|
| 150 |
+
skip_exists: bool = True,
|
| 151 |
+
time_out: int = 30,
|
| 152 |
+
):
|
| 153 |
+
"""
|
| 154 |
+
:param skip_exists: whether to skip the existing files. If True, ext should be specified.
|
| 155 |
+
:param check_size: whether to check file size. If True, remove files that less than 1024 bytes and ext should be specified.
|
| 156 |
+
:param ext: extension of the output file without dot.
|
| 157 |
+
:return: List of success file_ids
|
| 158 |
+
"""
|
| 159 |
+
format_code = "ba*[audio_channels=4]"
|
| 160 |
+
ext = "webm"
|
| 161 |
+
|
| 162 |
+
origin_file_items = [
|
| 163 |
+
video_id + "_" + str(start_time) for start_time in start_times
|
| 164 |
+
]
|
| 165 |
+
file_path_base = os.path.join(output_folder, video_id)
|
| 166 |
+
if skip_exists:
|
| 167 |
+
original_start_times = start_times
|
| 168 |
+
start_times = []
|
| 169 |
+
for st in original_start_times:
|
| 170 |
+
if os.path.exists(file_path_base + "_" + str(st) + "." + ext):
|
| 171 |
+
print(f"{video_id}_{st} already exists")
|
| 172 |
+
else:
|
| 173 |
+
start_times.append(st)
|
| 174 |
+
|
| 175 |
+
if len(start_times) == 0:
|
| 176 |
+
return origin_file_items
|
| 177 |
+
|
| 178 |
+
end_times = [t + time_interval for t in start_times]
|
| 179 |
+
|
| 180 |
+
file_items = [
|
| 181 |
+
video_id + "_" + str(start_time) for start_time in start_times
|
| 182 |
+
]
|
| 183 |
+
|
| 184 |
+
# specify command
|
| 185 |
+
cmd = [
|
| 186 |
+
"yt-dlp",
|
| 187 |
+
"-f",
|
| 188 |
+
format_code,
|
| 189 |
+
f"https://www.youtube.com/watch?v={video_id}",
|
| 190 |
+
"-o",
|
| 191 |
+
f"{file_path_base}_%(section_start)d.%(ext)s",
|
| 192 |
+
"--socket-timeout",
|
| 193 |
+
str(time_out),
|
| 194 |
+
"--abort-on-error",
|
| 195 |
+
"--abort-on-unavailable-fragments",
|
| 196 |
+
"-N",
|
| 197 |
+
"4",
|
| 198 |
+
"--force-keyframes-at-cuts",
|
| 199 |
+
"--extractor-args",
|
| 200 |
+
"youtube:player_client=all",
|
| 201 |
+
"--merge-output-format",
|
| 202 |
+
"webm",
|
| 203 |
+
]
|
| 204 |
+
|
| 205 |
+
if proxy is not None:
|
| 206 |
+
cmd += ["--proxy", proxy]
|
| 207 |
+
|
| 208 |
+
if start_times is not None:
|
| 209 |
+
for start_time, end_time in zip(start_times, end_times):
|
| 210 |
+
cmd += [
|
| 211 |
+
"--download-sections",
|
| 212 |
+
f"*{start_time}-{end_time}",
|
| 213 |
+
]
|
| 214 |
+
|
| 215 |
+
try_id = 0
|
| 216 |
+
success = False
|
| 217 |
+
result = None
|
| 218 |
+
while try_id < try_time and not success:
|
| 219 |
+
print(f"Downloading video items {video_id}...")
|
| 220 |
+
result = subprocess.run(
|
| 221 |
+
cmd,
|
| 222 |
+
capture_output=True,
|
| 223 |
+
text=True,
|
| 224 |
+
)
|
| 225 |
+
if result.returncode == 0:
|
| 226 |
+
if check_size:
|
| 227 |
+
file_names = [
|
| 228 |
+
os.path.join(output_folder, file_item + "." + ext)
|
| 229 |
+
for file_item in file_items
|
| 230 |
+
]
|
| 231 |
+
success = _check_size(file_names, remove=True)
|
| 232 |
+
else:
|
| 233 |
+
success = True
|
| 234 |
+
if not success:
|
| 235 |
+
print(
|
| 236 |
+
f"[WARNING] Failed to download video items {video_id}, retrying...({try_id + 1}/{try_time})"
|
| 237 |
+
)
|
| 238 |
+
try_id += 1
|
| 239 |
+
|
| 240 |
+
if not success:
|
| 241 |
+
raise DownloadError(
|
| 242 |
+
{
|
| 243 |
+
"items": file_items,
|
| 244 |
+
"result": result,
|
| 245 |
+
}
|
| 246 |
+
)
|
| 247 |
+
return file_items
|
| 248 |
+
|
| 249 |
+
def download_360(
|
| 250 |
+
video_id: str,
|
| 251 |
+
output_folder: str,
|
| 252 |
+
proxy: str = None,
|
| 253 |
+
try_time: int = 2,
|
| 254 |
+
check_size: bool = True,
|
| 255 |
+
skip_exists: bool = True,
|
| 256 |
+
time_out: int = 30,
|
| 257 |
+
cookie=None
|
| 258 |
+
) -> List[str]:
|
| 259 |
+
"""
|
| 260 |
+
:param skip_exists: whether to skip the existing files. If True, ext should be specified.
|
| 261 |
+
:param ext: extension of the output file without dot.
|
| 262 |
+
:return: List of success file_ids
|
| 263 |
+
"""
|
| 264 |
+
# Check format code with ext
|
| 265 |
+
format_code = "bv[height<=1080]+ba[audio_channels=4]"
|
| 266 |
+
ext = "webm"
|
| 267 |
+
|
| 268 |
+
file_items = [video_id]
|
| 269 |
+
file_path_base = os.path.join(output_folder, video_id)
|
| 270 |
+
if skip_exists:
|
| 271 |
+
if ext is None:
|
| 272 |
+
raise ValueError("ext should be specified when skip_exists is True")
|
| 273 |
+
if os.path.exists(file_path_base + "." + ext):
|
| 274 |
+
print(f"{video_id} already exists")
|
| 275 |
+
return file_items
|
| 276 |
+
|
| 277 |
+
print(file_path_base)
|
| 278 |
+
# specify command
|
| 279 |
+
cmd = [
|
| 280 |
+
"yt-dlp",
|
| 281 |
+
"-f",
|
| 282 |
+
format_code,
|
| 283 |
+
f"https://www.youtube.com/watch?v={video_id}",
|
| 284 |
+
"-o",
|
| 285 |
+
f"{file_path_base}.%(ext)s",
|
| 286 |
+
"--socket-timeout",
|
| 287 |
+
str(time_out),
|
| 288 |
+
"--abort-on-error",
|
| 289 |
+
"--abort-on-unavailable-fragments",
|
| 290 |
+
"-N",
|
| 291 |
+
"4",
|
| 292 |
+
"--extractor-args",
|
| 293 |
+
"youtube:player_client=all",
|
| 294 |
+
"--merge-output-format",
|
| 295 |
+
ext,
|
| 296 |
+
]
|
| 297 |
+
|
| 298 |
+
if proxy is not None:
|
| 299 |
+
cmd += ["--proxy", proxy]
|
| 300 |
+
|
| 301 |
+
if cookie is not None:
|
| 302 |
+
cmd += ["--cookies", cookie]
|
| 303 |
+
|
| 304 |
+
try_id = 0
|
| 305 |
+
success = False
|
| 306 |
+
result = None
|
| 307 |
+
while try_id < try_time and not success:
|
| 308 |
+
print(f"Downloading video {video_id}...")
|
| 309 |
+
result = subprocess.run(
|
| 310 |
+
cmd,
|
| 311 |
+
capture_output=True,
|
| 312 |
+
text=True,
|
| 313 |
+
)
|
| 314 |
+
# result = subprocess.run(cmd)
|
| 315 |
+
if result.returncode == 0:
|
| 316 |
+
if check_size:
|
| 317 |
+
file_names = [
|
| 318 |
+
os.path.join(output_folder, file_item + "." + ext)
|
| 319 |
+
for file_item in file_items
|
| 320 |
+
]
|
| 321 |
+
success = _check_size(file_names, remove=True)
|
| 322 |
+
else:
|
| 323 |
+
success = True
|
| 324 |
+
if not success:
|
| 325 |
+
print(
|
| 326 |
+
f"[WARNING] Failed to download video items {video_id}, retrying...({try_id + 1}/{try_time})"
|
| 327 |
+
)
|
| 328 |
+
try_id += 1
|
| 329 |
+
|
| 330 |
+
if not success:
|
| 331 |
+
raise DownloadError(
|
| 332 |
+
{
|
| 333 |
+
"items": file_items,
|
| 334 |
+
"result": result,
|
| 335 |
+
}
|
| 336 |
+
)
|
| 337 |
+
return file_items
|
| 338 |
+
|
| 339 |
+
|
| 340 |
+
def download_360_segments(
|
| 341 |
+
video_id: str,
|
| 342 |
+
output_folder: str,
|
| 343 |
+
start_times: List[int],
|
| 344 |
+
time_interval: int = 10,
|
| 345 |
+
proxy: str = None,
|
| 346 |
+
try_time: int = 2,
|
| 347 |
+
check_size: bool = True,
|
| 348 |
+
skip_exists: bool = True,
|
| 349 |
+
time_out: int = 30,
|
| 350 |
+
cookie=None,
|
| 351 |
+
):
|
| 352 |
+
"""
|
| 353 |
+
:param skip_exists: whether to skip the existing files. If True, ext should be specified.
|
| 354 |
+
:param check_size: whether to check file size. If True, remove files that less than 1024 bytes and ext should be specified.
|
| 355 |
+
:param ext: extension of the output file without dot.
|
| 356 |
+
:return: List of success file_ids
|
| 357 |
+
"""
|
| 358 |
+
format_code = "bv[height<=1440]+ba[audio_channels=4]"
|
| 359 |
+
ext = "webm"
|
| 360 |
+
|
| 361 |
+
origin_file_items = [
|
| 362 |
+
video_id + "_" + str(start_time) for start_time in start_times
|
| 363 |
+
]
|
| 364 |
+
file_path_base = os.path.join(output_folder, video_id)
|
| 365 |
+
if skip_exists:
|
| 366 |
+
original_start_times = start_times
|
| 367 |
+
start_times = []
|
| 368 |
+
for st in original_start_times:
|
| 369 |
+
if os.path.exists(file_path_base + "_" + str(st) + "." + ext):
|
| 370 |
+
print(f"{video_id}_{st} already exists")
|
| 371 |
+
else:
|
| 372 |
+
start_times.append(st)
|
| 373 |
+
|
| 374 |
+
if len(start_times) == 0:
|
| 375 |
+
return origin_file_items
|
| 376 |
+
|
| 377 |
+
end_times = [t + time_interval for t in start_times]
|
| 378 |
+
|
| 379 |
+
file_items = [
|
| 380 |
+
video_id + "_" + str(start_time) for start_time in start_times
|
| 381 |
+
]
|
| 382 |
+
|
| 383 |
+
# specify command
|
| 384 |
+
cmd = [
|
| 385 |
+
"yt-dlp",
|
| 386 |
+
"-f",
|
| 387 |
+
format_code,
|
| 388 |
+
f"https://www.youtube.com/watch?v={video_id}",
|
| 389 |
+
"-o",
|
| 390 |
+
f"{file_path_base}_%(section_start)d.%(ext)s",
|
| 391 |
+
"--socket-timeout",
|
| 392 |
+
str(time_out),
|
| 393 |
+
"--abort-on-error",
|
| 394 |
+
"--abort-on-unavailable-fragments",
|
| 395 |
+
"-N",
|
| 396 |
+
"4",
|
| 397 |
+
"--force-keyframes-at-cuts",
|
| 398 |
+
"--extractor-args",
|
| 399 |
+
"youtube:player_client=all",
|
| 400 |
+
"--merge-output-format",
|
| 401 |
+
"webm",
|
| 402 |
+
]
|
| 403 |
+
|
| 404 |
+
if proxy is not None:
|
| 405 |
+
cmd += ["--proxy", proxy]
|
| 406 |
+
|
| 407 |
+
if cookie is not None:
|
| 408 |
+
cmd += ["--cookies", cookie]
|
| 409 |
+
|
| 410 |
+
if start_times is not None:
|
| 411 |
+
for start_time, end_time in zip(start_times, end_times):
|
| 412 |
+
cmd += [
|
| 413 |
+
"--download-sections",
|
| 414 |
+
f"*{start_time}-{end_time}",
|
| 415 |
+
]
|
| 416 |
+
|
| 417 |
+
try_id = 0
|
| 418 |
+
success = False
|
| 419 |
+
result = None
|
| 420 |
+
while try_id < try_time and not success:
|
| 421 |
+
print(f"Downloading video items {video_id}...")
|
| 422 |
+
result = subprocess.run(
|
| 423 |
+
cmd,
|
| 424 |
+
capture_output=True,
|
| 425 |
+
text=True,
|
| 426 |
+
)
|
| 427 |
+
if result.returncode == 0:
|
| 428 |
+
if check_size:
|
| 429 |
+
file_names = [
|
| 430 |
+
os.path.join(output_folder, file_item + "." + ext)
|
| 431 |
+
for file_item in file_items
|
| 432 |
+
]
|
| 433 |
+
success = _check_size(file_names, remove=True)
|
| 434 |
+
else:
|
| 435 |
+
success = True
|
| 436 |
+
if not success:
|
| 437 |
+
stderr = result.stderr
|
| 438 |
+
if stderr.find("format is not available") != -1:
|
| 439 |
+
print(
|
| 440 |
+
f"[WARNING] Skip {video_id} since format not available({try_id + 1}/{try_time})"
|
| 441 |
+
)
|
| 442 |
+
break
|
| 443 |
+
print(
|
| 444 |
+
f"[WARNING] Failed to download video items {video_id}, retrying...({try_id + 1}/{try_time})"
|
| 445 |
+
)
|
| 446 |
+
try_id += 1
|
| 447 |
+
|
| 448 |
+
if not success:
|
| 449 |
+
raise DownloadError(
|
| 450 |
+
{
|
| 451 |
+
"items": file_items,
|
| 452 |
+
"result": result,
|
| 453 |
+
}
|
| 454 |
+
)
|
| 455 |
+
return file_items
|
| 456 |
+
|
| 457 |
+
|
| 458 |
+
def download_video_segments(
|
| 459 |
+
video_id: str,
|
| 460 |
+
output_folder: str,
|
| 461 |
+
start_times: List[int],
|
| 462 |
+
ext: str = None,
|
| 463 |
+
time_interval: int = 10,
|
| 464 |
+
proxy: str = None,
|
| 465 |
+
try_time: int = 2,
|
| 466 |
+
check_size: bool = True,
|
| 467 |
+
skip_exists: bool = True,
|
| 468 |
+
time_out: int = 30,
|
| 469 |
+
format_code: str = "bv+ba",
|
| 470 |
+
) -> List[str]:
|
| 471 |
+
"""
|
| 472 |
+
:param skip_exists: whether to skip the existing files. If True, ext should be specified.
|
| 473 |
+
:param check_size: whether to check file size. If True, remove files that less than 1024 bytes and ext should be specified.
|
| 474 |
+
:param ext: extension of the output file without dot.
|
| 475 |
+
:return: List of success file_ids
|
| 476 |
+
"""
|
| 477 |
+
# Check check_size with ext
|
| 478 |
+
if check_size and ext is None:
|
| 479 |
+
raise ValueError("ext should be specified when check_size is True")
|
| 480 |
+
|
| 481 |
+
# Check format code with ext
|
| 482 |
+
if ext is not None:
|
| 483 |
+
if format_code.find("[ext=") != -1:
|
| 484 |
+
if format_code.find(f"[ext={ext}]") == -1:
|
| 485 |
+
raise ValueError(
|
| 486 |
+
f"Format code {format_code} does not match the extension {ext}"
|
| 487 |
+
)
|
| 488 |
+
else:
|
| 489 |
+
format_code += f"[ext={ext}]"
|
| 490 |
+
|
| 491 |
+
origin_file_items = [
|
| 492 |
+
video_id + "_" + str(start_time) for start_time in start_times
|
| 493 |
+
]
|
| 494 |
+
file_path_base = os.path.join(output_folder, video_id)
|
| 495 |
+
if skip_exists:
|
| 496 |
+
if ext is None:
|
| 497 |
+
raise ValueError("ext should be specified when skip_exists is True")
|
| 498 |
+
original_start_times = start_times
|
| 499 |
+
start_times = []
|
| 500 |
+
for st in original_start_times:
|
| 501 |
+
if os.path.exists(file_path_base + "_" + str(st) + "." + ext):
|
| 502 |
+
print(f"{video_id}_{st} already exists")
|
| 503 |
+
else:
|
| 504 |
+
start_times.append(st)
|
| 505 |
+
|
| 506 |
+
if len(start_times) == 0:
|
| 507 |
+
return origin_file_items
|
| 508 |
+
|
| 509 |
+
end_times = [t + time_interval for t in start_times]
|
| 510 |
+
|
| 511 |
+
file_items = [
|
| 512 |
+
video_id + "_" + str(start_time) for start_time in start_times
|
| 513 |
+
]
|
| 514 |
+
|
| 515 |
+
# Specify command
|
| 516 |
+
cmd = [
|
| 517 |
+
"yt-dlp",
|
| 518 |
+
"-f",
|
| 519 |
+
format_code,
|
| 520 |
+
f"https://www.youtube.com/watch?v={video_id}",
|
| 521 |
+
"-o",
|
| 522 |
+
f"{file_path_base}_%(section_start)d.%(ext)s",
|
| 523 |
+
"--socket-timeout",
|
| 524 |
+
str(time_out),
|
| 525 |
+
"--abort-on-error",
|
| 526 |
+
"--abort-on-unavailable-fragments",
|
| 527 |
+
"-N",
|
| 528 |
+
"4",
|
| 529 |
+
"--force-keyframes-at-cuts",
|
| 530 |
+
]
|
| 531 |
+
|
| 532 |
+
if proxy is not None:
|
| 533 |
+
cmd += ["--proxy", proxy]
|
| 534 |
+
|
| 535 |
+
if start_times is not None:
|
| 536 |
+
for start_time, end_time in zip(start_times, end_times):
|
| 537 |
+
cmd += [
|
| 538 |
+
"--download-sections",
|
| 539 |
+
f"*{start_time}-{end_time}",
|
| 540 |
+
]
|
| 541 |
+
|
| 542 |
+
try_id = 0
|
| 543 |
+
success = False
|
| 544 |
+
result = None
|
| 545 |
+
while try_id < try_time and not success:
|
| 546 |
+
print(f"Downloading video items {video_id}...")
|
| 547 |
+
result = subprocess.run(
|
| 548 |
+
cmd,
|
| 549 |
+
# capture_output=True,
|
| 550 |
+
# text=True,
|
| 551 |
+
)
|
| 552 |
+
if result.returncode == 0:
|
| 553 |
+
if check_size:
|
| 554 |
+
file_names = [
|
| 555 |
+
os.path.join(output_folder, file_item + "." + ext)
|
| 556 |
+
for file_item in file_items
|
| 557 |
+
]
|
| 558 |
+
success = _check_size(file_names, remove=True)
|
| 559 |
+
else:
|
| 560 |
+
success = True
|
| 561 |
+
if not success:
|
| 562 |
+
print(
|
| 563 |
+
f"[WARNING] Failed to download video items {video_id}, retrying...({try_id + 1}/{try_time})"
|
| 564 |
+
)
|
| 565 |
+
try_id += 1
|
| 566 |
+
|
| 567 |
+
if not success:
|
| 568 |
+
raise DownloadError(
|
| 569 |
+
{
|
| 570 |
+
"items": file_items,
|
| 571 |
+
"result": result,
|
| 572 |
+
}
|
| 573 |
+
)
|
| 574 |
+
return file_items
|
| 575 |
+
|
| 576 |
+
|
| 577 |
+
def get_video_ids(input_file: str):
|
| 578 |
+
video_ids = []
|
| 579 |
+
if input_file.endswith(".csv"): # CSV file
|
| 580 |
+
with open(input_file, "r") as file:
|
| 581 |
+
csvreader = csv.DictReader(file)
|
| 582 |
+
for row in csvreader:
|
| 583 |
+
video_ids.append(row["video_id"])
|
| 584 |
+
else: # Default format
|
| 585 |
+
with open(input_file, "r") as file:
|
| 586 |
+
lines = file.readlines()
|
| 587 |
+
for line in lines:
|
| 588 |
+
video_ids.append(line.strip())
|
| 589 |
+
|
| 590 |
+
return video_ids
|
| 591 |
+
|
| 592 |
+
|
| 593 |
+
def get_video_ids_and_start_times(input_file: str):
|
| 594 |
+
video_ids = []
|
| 595 |
+
start_times = []
|
| 596 |
+
lines = []
|
| 597 |
+
if input_file.endswith(".csv"): # CSV file
|
| 598 |
+
with open(input_file, "r") as file:
|
| 599 |
+
csvreader = csv.DictReader(file)
|
| 600 |
+
for row in csvreader:
|
| 601 |
+
lines.append(row["file_id"])
|
| 602 |
+
else: # Default format
|
| 603 |
+
with open(input_file, "r") as file:
|
| 604 |
+
lines = file.readlines()
|
| 605 |
+
|
| 606 |
+
for line in lines:
|
| 607 |
+
parts = line.rsplit("_", 1)
|
| 608 |
+
if len(parts) != 2:
|
| 609 |
+
continue
|
| 610 |
+
video_ids.append(parts[0])
|
| 611 |
+
start_times.append(int(parts[1]))
|
| 612 |
+
|
| 613 |
+
return video_ids, start_times
|
| 614 |
+
|
| 615 |
+
|
| 616 |
+
def get_video_ids_and_start_times_list(input_file: str):
|
| 617 |
+
file_ids = []
|
| 618 |
+
start_times_list = []
|
| 619 |
+
with open(input_file, "r") as file:
|
| 620 |
+
lines = file.readlines()
|
| 621 |
+
for line in lines:
|
| 622 |
+
parts = line.strip().split()
|
| 623 |
+
if len(parts) != 2:
|
| 624 |
+
continue
|
| 625 |
+
|
| 626 |
+
file_ids.append(parts[0])
|
| 627 |
+
start_times = parts[1].split(",")
|
| 628 |
+
start_times_list.append([int(t) for t in start_times if t.isdigit()])
|
| 629 |
+
return file_ids, start_times_list
|
| 630 |
+
|
| 631 |
+
|
| 632 |
+
def download_list_4ch(
|
| 633 |
+
input_file,
|
| 634 |
+
output_folder,
|
| 635 |
+
start_index=None,
|
| 636 |
+
end_index=None,
|
| 637 |
+
specify_start: str = None,
|
| 638 |
+
proxy=None,
|
| 639 |
+
time_interval=None,
|
| 640 |
+
fail_list_name="fail_list.txt",
|
| 641 |
+
success_list_name="success_list.txt",
|
| 642 |
+
jobs=1,
|
| 643 |
+
):
|
| 644 |
+
"""
|
| 645 |
+
Download video items from a list of video ids. Can specify the start time of each video.
|
| 646 |
+
|
| 647 |
+
:param input_file: input file path. Can be a csv file with column 'video_id'/'file_id'(start time specified)
|
| 648 |
+
or a txt file with each line as a video id. See specify_start for more details about format.
|
| 649 |
+
:param output_folder: output folder path.
|
| 650 |
+
:param start_index: start index of the video list, None means the start of the list. The list will be slice by [start_index:end_index)
|
| 651 |
+
:param end_index: end index of the video list, None means the end of the list. The list will be slice by [start_index:end_index)
|
| 652 |
+
:param specify_start: If specified, time_interval should be specified as well.
|
| 653 |
+
None: (Default) not to specify the start time. Each item is a video_id.
|
| 654 |
+
"single": specify single start time for each video_id.
|
| 655 |
+
For non-csv file, format each line by f'{video_id}_{start_time}'.
|
| 656 |
+
For CSV file, title by 'file_id' and format the same.
|
| 657 |
+
"multiple": specify multiple start times for each video_id. Only non-csv file is supported in this mode.
|
| 658 |
+
Format each line as f'{video_id} {start_times}', where start_times is a list of start times separated by ','.
|
| 659 |
+
"""
|
| 660 |
+
if not os.path.exists(output_folder):
|
| 661 |
+
os.makedirs(output_folder)
|
| 662 |
+
|
| 663 |
+
print(f"speicify_start: {specify_start}")
|
| 664 |
+
if specify_start is not None:
|
| 665 |
+
if time_interval is None:
|
| 666 |
+
raise ValueError(
|
| 667 |
+
"time_interval should be specified when specify_start is not None."
|
| 668 |
+
)
|
| 669 |
+
if specify_start == "single":
|
| 670 |
+
video_ids, start_times = get_video_ids_and_start_times(input_file)
|
| 671 |
+
start_times_list = [[start_time] for start_time in start_times]
|
| 672 |
+
elif specify_start == "multiple":
|
| 673 |
+
video_ids, start_times_list = get_video_ids_and_start_times_list(
|
| 674 |
+
input_file
|
| 675 |
+
)
|
| 676 |
+
else:
|
| 677 |
+
raise ValueError("Invalid specify_start value.")
|
| 678 |
+
else:
|
| 679 |
+
video_ids = get_video_ids(input_file)
|
| 680 |
+
start_times_list = None
|
| 681 |
+
|
| 682 |
+
start_index = 0 if start_index is None else start_index
|
| 683 |
+
end_index = len(video_ids) if end_index is None else end_index
|
| 684 |
+
if start_index > 0:
|
| 685 |
+
print(f"Start from index:{start_index}")
|
| 686 |
+
if end_index != len(video_ids):
|
| 687 |
+
print(f"End to index:{end_index}")
|
| 688 |
+
video_ids = video_ids[start_index:end_index]
|
| 689 |
+
if specify_start:
|
| 690 |
+
start_times_list = start_times_list[start_index:end_index]
|
| 691 |
+
|
| 692 |
+
print(f"Downloading {len(video_ids)} videos into {output_folder}")
|
| 693 |
+
|
| 694 |
+
# create success & fail list
|
| 695 |
+
print(f"Success files written into {success_list_name}")
|
| 696 |
+
print(f"Fail files written into {fail_list_name}")
|
| 697 |
+
with open(success_list_name, "w") as f:
|
| 698 |
+
pass
|
| 699 |
+
with open(fail_list_name, "w") as f:
|
| 700 |
+
pass
|
| 701 |
+
|
| 702 |
+
pbar = tqdm(total=len(video_ids))
|
| 703 |
+
success_list = []
|
| 704 |
+
fail_list = []
|
| 705 |
+
(
|
| 706 |
+
pbar_lock,
|
| 707 |
+
success_lock,
|
| 708 |
+
fail_lock,
|
| 709 |
+
) = (
|
| 710 |
+
Lock(),
|
| 711 |
+
Lock(),
|
| 712 |
+
Lock(),
|
| 713 |
+
)
|
| 714 |
+
|
| 715 |
+
def download_success(file_ids):
|
| 716 |
+
nonlocal pbar, success_list_name, success_list, success_list, pbar_lock
|
| 717 |
+
with pbar_lock:
|
| 718 |
+
pbar.update(1)
|
| 719 |
+
with success_lock:
|
| 720 |
+
for file_id in file_ids:
|
| 721 |
+
success_list.append(file_id)
|
| 722 |
+
with open(success_list_name, "a") as f:
|
| 723 |
+
f.write(f"{file_id}\n")
|
| 724 |
+
|
| 725 |
+
def download_fail(
|
| 726 |
+
error: DownloadError,
|
| 727 |
+
):
|
| 728 |
+
nonlocal pbar, fail_list_name, fail_list, fail_lock, pbar_lock
|
| 729 |
+
with pbar_lock:
|
| 730 |
+
pbar.update(1)
|
| 731 |
+
if not isinstance(error, DownloadError):
|
| 732 |
+
print(f"[Error]: {error}")
|
| 733 |
+
raise error
|
| 734 |
+
file_ids = error.items
|
| 735 |
+
with fail_lock:
|
| 736 |
+
for file_id in file_ids:
|
| 737 |
+
fail_list.append(file_id)
|
| 738 |
+
with open(fail_list_name, "a") as f:
|
| 739 |
+
f.write(f"{file_id}\n")
|
| 740 |
+
|
| 741 |
+
# start downloading
|
| 742 |
+
if specify_start is None:
|
| 743 |
+
|
| 744 |
+
def arg_gen(video_ids):
|
| 745 |
+
for video_id in video_ids:
|
| 746 |
+
yield {
|
| 747 |
+
"video_id": video_id,
|
| 748 |
+
"output_folder": output_folder,
|
| 749 |
+
"proxy": proxy,
|
| 750 |
+
}
|
| 751 |
+
|
| 752 |
+
arg_iter = arg_gen(video_ids)
|
| 753 |
+
else:
|
| 754 |
+
|
| 755 |
+
def arg_gen(video_ids, start_times_list):
|
| 756 |
+
for video_id, start_times in zip(video_ids, start_times_list):
|
| 757 |
+
yield {
|
| 758 |
+
"video_id": video_id,
|
| 759 |
+
"start_times": start_times,
|
| 760 |
+
"output_folder": output_folder,
|
| 761 |
+
"proxy": proxy,
|
| 762 |
+
"time_interval": time_interval,
|
| 763 |
+
}
|
| 764 |
+
|
| 765 |
+
arg_iter = arg_gen(video_ids, start_times_list)
|
| 766 |
+
|
| 767 |
+
# for arg in arg_iter:
|
| 768 |
+
# try:
|
| 769 |
+
# result = (download_video_process if specify_start is None else download_video_segments_process)(arg)
|
| 770 |
+
# download_success(result)
|
| 771 |
+
# except DownloadError as e:
|
| 772 |
+
# download_fail(e)
|
| 773 |
+
|
| 774 |
+
p = Pool(jobs)
|
| 775 |
+
for arg in arg_iter:
|
| 776 |
+
p.apply_async(
|
| 777 |
+
download_4ch_segments_process,
|
| 778 |
+
args=(arg,),
|
| 779 |
+
callback=download_success,
|
| 780 |
+
error_callback=download_fail,
|
| 781 |
+
)
|
| 782 |
+
p.close()
|
| 783 |
+
p.join()
|
| 784 |
+
|
| 785 |
+
print("Finished downloading.")
|
| 786 |
+
|
| 787 |
+
# output fail status
|
| 788 |
+
success_list.sort()
|
| 789 |
+
with open(success_list_name, "w") as f:
|
| 790 |
+
for item in success_list:
|
| 791 |
+
f.write(f"{item}\n")
|
| 792 |
+
print(
|
| 793 |
+
f"{len(success_list)} success files written into {success_list_name}."
|
| 794 |
+
)
|
| 795 |
+
fail_list.sort()
|
| 796 |
+
with open(fail_list_name, "w") as f:
|
| 797 |
+
for item in fail_list:
|
| 798 |
+
f.write(f"{item}\n")
|
| 799 |
+
print(f"{len(fail_list)} fail files written into {fail_list_name}.")
|
| 800 |
+
|
| 801 |
+
def download_list_360(
|
| 802 |
+
input_file,
|
| 803 |
+
output_folder,
|
| 804 |
+
start_index=None,
|
| 805 |
+
end_index=None,
|
| 806 |
+
specify_start: str = None,
|
| 807 |
+
proxy=None,
|
| 808 |
+
time_interval=None,
|
| 809 |
+
fail_list_name="fail_list.txt",
|
| 810 |
+
success_list_name="success_list.txt",
|
| 811 |
+
jobs=1,
|
| 812 |
+
cookie=None,
|
| 813 |
+
):
|
| 814 |
+
"""
|
| 815 |
+
Download video items from a list of video ids. Can specify the start time of each video.
|
| 816 |
+
|
| 817 |
+
:param input_file: input file path. Can be a csv file with column 'video_id'/'file_id'(start time specified)
|
| 818 |
+
or a txt file with each line as a video id. See specify_start for more details about format.
|
| 819 |
+
:param output_folder: output folder path.
|
| 820 |
+
:param start_index: start index of the video list, None means the start of the list. The list will be slice by [start_index:end_index)
|
| 821 |
+
:param end_index: end index of the video list, None means the end of the list. The list will be slice by [start_index:end_index)
|
| 822 |
+
:param specify_start: If specified, time_interval should be specified as well.
|
| 823 |
+
None: (Default) not to specify the start time. Each item is a video_id.
|
| 824 |
+
"single": specify single start time for each video_id.
|
| 825 |
+
For non-csv file, format each line by f'{video_id}_{start_time}'.
|
| 826 |
+
For CSV file, title by 'file_id' and format the same.
|
| 827 |
+
"multiple": specify multiple start times for each video_id. Only non-csv file is supported in this mode.
|
| 828 |
+
Format each line as f'{video_id} {start_times}', where start_times is a list of start times separated by ','.
|
| 829 |
+
"""
|
| 830 |
+
if not os.path.exists(output_folder):
|
| 831 |
+
os.makedirs(output_folder)
|
| 832 |
+
|
| 833 |
+
print(f"speicify_start: {specify_start}")
|
| 834 |
+
if specify_start is not None:
|
| 835 |
+
if time_interval is None:
|
| 836 |
+
raise ValueError(
|
| 837 |
+
"time_interval should be specified when specify_start is not None."
|
| 838 |
+
)
|
| 839 |
+
if specify_start == "single":
|
| 840 |
+
video_ids, start_times = get_video_ids_and_start_times(input_file)
|
| 841 |
+
start_times_list = [[start_time] for start_time in start_times]
|
| 842 |
+
elif specify_start == "multiple":
|
| 843 |
+
video_ids, start_times_list = get_video_ids_and_start_times_list(
|
| 844 |
+
input_file
|
| 845 |
+
)
|
| 846 |
+
else:
|
| 847 |
+
raise ValueError("Invalid specify_start value.")
|
| 848 |
+
else:
|
| 849 |
+
video_ids = get_video_ids(input_file)
|
| 850 |
+
start_times_list = None
|
| 851 |
+
|
| 852 |
+
start_index = 0 if start_index is None else start_index
|
| 853 |
+
end_index = len(video_ids) if end_index is None else end_index
|
| 854 |
+
if start_index > 0:
|
| 855 |
+
print(f"Start from index:{start_index}")
|
| 856 |
+
if end_index != len(video_ids):
|
| 857 |
+
print(f"End to index:{end_index}")
|
| 858 |
+
video_ids = video_ids[start_index:end_index]
|
| 859 |
+
if specify_start:
|
| 860 |
+
start_times_list = start_times_list[start_index:end_index]
|
| 861 |
+
|
| 862 |
+
print(f"Downloading {len(video_ids)} videos into {output_folder}")
|
| 863 |
+
|
| 864 |
+
# create success & fail list
|
| 865 |
+
print(f"Success files written into {success_list_name}")
|
| 866 |
+
print(f"Fail files written into {fail_list_name}")
|
| 867 |
+
with open(success_list_name, "w") as f:
|
| 868 |
+
pass
|
| 869 |
+
with open(fail_list_name, "w") as f:
|
| 870 |
+
pass
|
| 871 |
+
|
| 872 |
+
pbar = tqdm(total=len(video_ids))
|
| 873 |
+
success_list = []
|
| 874 |
+
fail_list = []
|
| 875 |
+
(
|
| 876 |
+
pbar_lock,
|
| 877 |
+
success_lock,
|
| 878 |
+
fail_lock,
|
| 879 |
+
) = (
|
| 880 |
+
Lock(),
|
| 881 |
+
Lock(),
|
| 882 |
+
Lock(),
|
| 883 |
+
)
|
| 884 |
+
|
| 885 |
+
def download_success(file_ids):
|
| 886 |
+
nonlocal pbar, success_list_name, success_list, success_list, pbar_lock
|
| 887 |
+
with pbar_lock:
|
| 888 |
+
pbar.update(1)
|
| 889 |
+
with success_lock:
|
| 890 |
+
for file_id in file_ids:
|
| 891 |
+
success_list.append(file_id)
|
| 892 |
+
with open(success_list_name, "a") as f:
|
| 893 |
+
f.write(f"{file_id}\n")
|
| 894 |
+
|
| 895 |
+
def download_fail(
|
| 896 |
+
error: DownloadError,
|
| 897 |
+
):
|
| 898 |
+
nonlocal pbar, fail_list_name, fail_list, fail_lock, pbar_lock
|
| 899 |
+
with pbar_lock:
|
| 900 |
+
pbar.update(1)
|
| 901 |
+
if not isinstance(error, DownloadError):
|
| 902 |
+
print(f"[Error]: {error}")
|
| 903 |
+
raise error
|
| 904 |
+
file_ids = error.items
|
| 905 |
+
with fail_lock:
|
| 906 |
+
for file_id in file_ids:
|
| 907 |
+
fail_list.append(file_id)
|
| 908 |
+
with open(fail_list_name, "a") as f:
|
| 909 |
+
f.write(f"{file_id}\n")
|
| 910 |
+
print(f"Fail to download {file_id}: {error.result.stderr}")
|
| 911 |
+
|
| 912 |
+
# start downloading
|
| 913 |
+
if specify_start is None:
|
| 914 |
+
|
| 915 |
+
def arg_gen(video_ids):
|
| 916 |
+
for video_id in video_ids:
|
| 917 |
+
yield {
|
| 918 |
+
"video_id": video_id,
|
| 919 |
+
"output_folder": output_folder,
|
| 920 |
+
"proxy": proxy,
|
| 921 |
+
"cookie": cookie,
|
| 922 |
+
}
|
| 923 |
+
|
| 924 |
+
arg_iter = arg_gen(video_ids)
|
| 925 |
+
else:
|
| 926 |
+
|
| 927 |
+
def arg_gen(video_ids, start_times_list):
|
| 928 |
+
for video_id, start_times in zip(video_ids, start_times_list):
|
| 929 |
+
yield {
|
| 930 |
+
"video_id": video_id,
|
| 931 |
+
"start_times": start_times,
|
| 932 |
+
"output_folder": output_folder,
|
| 933 |
+
"proxy": proxy,
|
| 934 |
+
"time_interval": time_interval,
|
| 935 |
+
"cookie": cookie
|
| 936 |
+
}
|
| 937 |
+
|
| 938 |
+
arg_iter = arg_gen(video_ids, start_times_list)
|
| 939 |
+
|
| 940 |
+
# for arg in arg_iter:
|
| 941 |
+
# try:
|
| 942 |
+
# result = (download_video_process if specify_start is None else download_video_segments_process)(arg)
|
| 943 |
+
# download_success(result)
|
| 944 |
+
# except DownloadError as e:
|
| 945 |
+
# download_fail(e)
|
| 946 |
+
|
| 947 |
+
p = Pool(jobs)
|
| 948 |
+
for arg in arg_iter:
|
| 949 |
+
if specify_start is None:
|
| 950 |
+
p.apply_async(
|
| 951 |
+
download_360_process,
|
| 952 |
+
args=(arg,),
|
| 953 |
+
callback=download_success,
|
| 954 |
+
error_callback=download_fail,
|
| 955 |
+
)
|
| 956 |
+
else:
|
| 957 |
+
p.apply_async(
|
| 958 |
+
download_360_segments_process,
|
| 959 |
+
args=(arg,),
|
| 960 |
+
callback=download_success,
|
| 961 |
+
error_callback=download_fail,
|
| 962 |
+
)
|
| 963 |
+
p.close()
|
| 964 |
+
p.join()
|
| 965 |
+
|
| 966 |
+
print("Finished downloading.")
|
| 967 |
+
|
| 968 |
+
# output fail status
|
| 969 |
+
success_list.sort()
|
| 970 |
+
with open(success_list_name, "w") as f:
|
| 971 |
+
for item in success_list:
|
| 972 |
+
f.write(f"{item}\n")
|
| 973 |
+
print(
|
| 974 |
+
f"{len(success_list)} success files written into {success_list_name}."
|
| 975 |
+
)
|
| 976 |
+
fail_list.sort()
|
| 977 |
+
with open(fail_list_name, "w") as f:
|
| 978 |
+
for item in fail_list:
|
| 979 |
+
f.write(f"{item}\n")
|
| 980 |
+
print(f"{len(fail_list)} fail files written into {fail_list_name}.")
|
| 981 |
+
|
| 982 |
+
return success_list
|
| 983 |
+
|
| 984 |
+
|
| 985 |
+
if __name__ == "__main__":
|
| 986 |
+
import argparse
|
| 987 |
+
import pprint
|
| 988 |
+
|
| 989 |
+
parser = argparse.ArgumentParser()
|
| 990 |
+
parser.add_argument(
|
| 991 |
+
"-i",
|
| 992 |
+
"--input",
|
| 993 |
+
type=str,
|
| 994 |
+
required=True,
|
| 995 |
+
)
|
| 996 |
+
parser.add_argument(
|
| 997 |
+
"-o",
|
| 998 |
+
"--output",
|
| 999 |
+
type=str,
|
| 1000 |
+
default="downloads",
|
| 1001 |
+
)
|
| 1002 |
+
parser.add_argument(
|
| 1003 |
+
"-st",
|
| 1004 |
+
"--start-index",
|
| 1005 |
+
type=int,
|
| 1006 |
+
default=None,
|
| 1007 |
+
)
|
| 1008 |
+
parser.add_argument(
|
| 1009 |
+
"-ed",
|
| 1010 |
+
"--end-index",
|
| 1011 |
+
help="The next index of the last download item",
|
| 1012 |
+
type=int,
|
| 1013 |
+
default=None,
|
| 1014 |
+
)
|
| 1015 |
+
parser.add_argument(
|
| 1016 |
+
"-p",
|
| 1017 |
+
"--proxy",
|
| 1018 |
+
type=str,
|
| 1019 |
+
default=None,
|
| 1020 |
+
)
|
| 1021 |
+
parser.add_argument(
|
| 1022 |
+
"--fail-list-name",
|
| 1023 |
+
type=str,
|
| 1024 |
+
default="fail_list.txt",
|
| 1025 |
+
)
|
| 1026 |
+
parser.add_argument(
|
| 1027 |
+
"--success-list-name",
|
| 1028 |
+
type=str,
|
| 1029 |
+
default="success_list.txt",
|
| 1030 |
+
)
|
| 1031 |
+
parser.add_argument(
|
| 1032 |
+
"-j",
|
| 1033 |
+
"--jobs",
|
| 1034 |
+
type=int,
|
| 1035 |
+
default=1,
|
| 1036 |
+
help="Number of parallel jobs",
|
| 1037 |
+
)
|
| 1038 |
+
parser.add_argument(
|
| 1039 |
+
"--specify-start",
|
| 1040 |
+
type=str,
|
| 1041 |
+
default="multiple",
|
| 1042 |
+
choices=["single", "multiple", None],
|
| 1043 |
+
)
|
| 1044 |
+
parser.add_argument(
|
| 1045 |
+
"--time-interval",
|
| 1046 |
+
type=int,
|
| 1047 |
+
default=10,
|
| 1048 |
+
)
|
| 1049 |
+
args = parser.parse_args()
|
| 1050 |
+
input_file = args.input
|
| 1051 |
+
output_folder = args.output
|
| 1052 |
+
start_index = args.start_index
|
| 1053 |
+
end_index = args.end_index
|
| 1054 |
+
fail_list_name = args.fail_list_name
|
| 1055 |
+
success_list_name = args.success_list_name
|
| 1056 |
+
proxy = None if args.proxy is None else args.proxy.strip()
|
| 1057 |
+
jobs = args.jobs
|
| 1058 |
+
specify_start = args.specify_start
|
| 1059 |
+
time_interval = args.time_interval
|
| 1060 |
+
print(f"Using arguments:\n{pprint.pformat(vars(args))}")
|
| 1061 |
+
|
| 1062 |
+
download_list_360(
|
| 1063 |
+
input_file=input_file,
|
| 1064 |
+
output_folder=output_folder,
|
| 1065 |
+
start_index=start_index,
|
| 1066 |
+
end_index=end_index,
|
| 1067 |
+
proxy=proxy,
|
| 1068 |
+
fail_list_name=fail_list_name,
|
| 1069 |
+
success_list_name=success_list_name,
|
| 1070 |
+
jobs=jobs,
|
| 1071 |
+
specify_start=specify_start,
|
| 1072 |
+
time_interval=time_interval,
|
| 1073 |
+
)
|
toolset/crawl/core/filelist.py
ADDED
|
@@ -0,0 +1,164 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import csv
|
| 2 |
+
import os
|
| 3 |
+
|
| 4 |
+
def get_channel_ids(input_file: str):
|
| 5 |
+
channel_ids = []
|
| 6 |
+
if input_file.endswith(".csv"): # CSV file
|
| 7 |
+
with open(input_file, "r") as file:
|
| 8 |
+
csvreader = csv.DictReader(file)
|
| 9 |
+
for row in csvreader:
|
| 10 |
+
channel_ids.append(row["channel_id"])
|
| 11 |
+
else: # Default format
|
| 12 |
+
with open(input_file, "r") as file:
|
| 13 |
+
lines = file.readlines()
|
| 14 |
+
for line in lines:
|
| 15 |
+
channel_ids.append(line.strip())
|
| 16 |
+
|
| 17 |
+
return channel_ids
|
| 18 |
+
|
| 19 |
+
def get_video_ids(input_file: str):
|
| 20 |
+
video_ids = []
|
| 21 |
+
if input_file.endswith(".csv"): # CSV file
|
| 22 |
+
with open(input_file, "r") as file:
|
| 23 |
+
csvreader = csv.DictReader(file)
|
| 24 |
+
for row in csvreader:
|
| 25 |
+
video_ids.append(row["video_id"])
|
| 26 |
+
else: # Default format
|
| 27 |
+
with open(input_file, "r") as file:
|
| 28 |
+
lines = file.readlines()
|
| 29 |
+
for line in lines:
|
| 30 |
+
video_ids.append(line.strip())
|
| 31 |
+
|
| 32 |
+
return video_ids
|
| 33 |
+
|
| 34 |
+
def get_file_ids(input_file: str):
|
| 35 |
+
file_ids = []
|
| 36 |
+
if input_file.endswith(".csv"): # CSV file
|
| 37 |
+
with open(input_file, "r") as file:
|
| 38 |
+
csvreader = csv.reader(file)
|
| 39 |
+
# skip header
|
| 40 |
+
next(csvreader)
|
| 41 |
+
for row in csvreader:
|
| 42 |
+
file_ids.append(row[0])
|
| 43 |
+
else: # Default format
|
| 44 |
+
with open(input_file, "r") as file:
|
| 45 |
+
lines = file.readlines()
|
| 46 |
+
for line in lines:
|
| 47 |
+
file_ids.append(line.strip())
|
| 48 |
+
|
| 49 |
+
return file_ids
|
| 50 |
+
|
| 51 |
+
def get_video_ids_and_start_times(input_file: str):
|
| 52 |
+
video_ids = []
|
| 53 |
+
start_times = []
|
| 54 |
+
lines = []
|
| 55 |
+
if input_file.endswith(".csv"): # CSV file
|
| 56 |
+
with open(input_file, "r") as file:
|
| 57 |
+
csvreader = csv.DictReader(file)
|
| 58 |
+
for row in csvreader:
|
| 59 |
+
lines.append(row["file_id"])
|
| 60 |
+
else: # Default format
|
| 61 |
+
with open(input_file, "r") as file:
|
| 62 |
+
lines = file.readlines()
|
| 63 |
+
|
| 64 |
+
for line in lines:
|
| 65 |
+
parts = line.rsplit("_", 1)
|
| 66 |
+
if len(parts) != 2:
|
| 67 |
+
continue
|
| 68 |
+
video_ids.append(parts[0])
|
| 69 |
+
start_times.append(int(parts[1]))
|
| 70 |
+
|
| 71 |
+
return video_ids, start_times
|
| 72 |
+
|
| 73 |
+
def get_video_ids_and_start_times_list(input_file: str):
|
| 74 |
+
video_data = {} # Dictionary to store video_id and corresponding start_times_list
|
| 75 |
+
|
| 76 |
+
with open(input_file, "r") as file:
|
| 77 |
+
lines = file.readlines()
|
| 78 |
+
|
| 79 |
+
for line in lines:
|
| 80 |
+
parts = line.strip().split()
|
| 81 |
+
if len(parts) != 2:
|
| 82 |
+
continue
|
| 83 |
+
|
| 84 |
+
video_id = parts[0]
|
| 85 |
+
start_times = parts[1].split(",")
|
| 86 |
+
start_times_list = [int(t) for t in start_times if t.isdigit()]
|
| 87 |
+
|
| 88 |
+
# Merge start_times_list for same video_id
|
| 89 |
+
if video_id in video_data:
|
| 90 |
+
video_data[video_id].extend(start_times_list)
|
| 91 |
+
else:
|
| 92 |
+
video_data[video_id] = start_times_list
|
| 93 |
+
|
| 94 |
+
# Deduplicate and sort start_times_list for each video_id
|
| 95 |
+
for video_id in video_data:
|
| 96 |
+
video_data[video_id] = sorted(set(video_data[video_id]))
|
| 97 |
+
|
| 98 |
+
# Separate results into two lists
|
| 99 |
+
file_ids = list(video_data.keys())
|
| 100 |
+
start_times_list = list(video_data.values())
|
| 101 |
+
|
| 102 |
+
return file_ids, start_times_list
|
| 103 |
+
|
| 104 |
+
def get_video_ids_from_dir(input_dir: str, ext: str):
|
| 105 |
+
"""
|
| 106 |
+
Extract video IDs from filenames in the specified directory.
|
| 107 |
+
|
| 108 |
+
Args:
|
| 109 |
+
input_dir: Directory containing the files
|
| 110 |
+
ext: File extension to filter by (e.g., 'mp4')
|
| 111 |
+
|
| 112 |
+
Returns:
|
| 113 |
+
List of video IDs extracted from filenames
|
| 114 |
+
"""
|
| 115 |
+
if not ext.startswith("."):
|
| 116 |
+
ext = "." + ext
|
| 117 |
+
video_ids = []
|
| 118 |
+
for file in os.listdir(input_dir):
|
| 119 |
+
if file.endswith(ext):
|
| 120 |
+
video_ids.append(file.split(".")[0])
|
| 121 |
+
return video_ids
|
| 122 |
+
|
| 123 |
+
def get_video_ids_from_dir_and_start_times(input_dir: str, ext: str):
|
| 124 |
+
"""
|
| 125 |
+
Extract video IDs and start times from filenames in the specified directory.
|
| 126 |
+
|
| 127 |
+
Args:
|
| 128 |
+
input_dir: Directory containing the files
|
| 129 |
+
ext: File extension to filter by (e.g., 'mp4')
|
| 130 |
+
|
| 131 |
+
Returns:
|
| 132 |
+
Tuple of (video_ids, start_times) extracted from filenames
|
| 133 |
+
"""
|
| 134 |
+
if not ext.startswith("."):
|
| 135 |
+
ext = "." + ext
|
| 136 |
+
video_ids = []
|
| 137 |
+
start_times = []
|
| 138 |
+
for file in os.listdir(input_dir):
|
| 139 |
+
if file.endswith(ext):
|
| 140 |
+
parts = file.split(".")[0].rsplit("_", 1)
|
| 141 |
+
if len(parts) != 2:
|
| 142 |
+
continue
|
| 143 |
+
video_ids.append(parts[0])
|
| 144 |
+
start_times.append(int(parts[1]))
|
| 145 |
+
return video_ids, start_times
|
| 146 |
+
|
| 147 |
+
def get_file_ids_from_dir(input_dir: str, ext: str):
|
| 148 |
+
"""
|
| 149 |
+
Extract file IDs from filenames in the specified directory.
|
| 150 |
+
|
| 151 |
+
Args:
|
| 152 |
+
input_dir: Directory containing the files
|
| 153 |
+
ext: File extension to filter by (e.g., 'mp4')
|
| 154 |
+
|
| 155 |
+
Returns:
|
| 156 |
+
List of file IDs extracted from filenames
|
| 157 |
+
"""
|
| 158 |
+
if not ext.startswith("."):
|
| 159 |
+
ext = "." + ext
|
| 160 |
+
file_ids = []
|
| 161 |
+
for file in os.listdir(input_dir):
|
| 162 |
+
if file.endswith(ext):
|
| 163 |
+
file_ids.append(file.split(".")[0])
|
| 164 |
+
return file_ids
|
toolset/crawl/core/filters/__init__.py
ADDED
|
@@ -0,0 +1,2 @@
|
|
|
|
|
|
|
|
|
|
| 1 |
+
from .ytfilter import filter_360
|
| 2 |
+
from . import filefilter, ytfilter
|
toolset/crawl/core/filters/filefilter.py
ADDED
|
@@ -0,0 +1,99 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import os
|
| 2 |
+
import subprocess
|
| 3 |
+
from tqdm import tqdm
|
| 4 |
+
|
| 5 |
+
|
| 6 |
+
def filter_list(video_ids, filter_ids, block=False):
|
| 7 |
+
"""
|
| 8 |
+
Filter video IDs from a list based on specified criteria
|
| 9 |
+
|
| 10 |
+
:param video_ids: List containing video IDs to be filtered
|
| 11 |
+
:param filter_ids: List of video IDs to use as filter
|
| 12 |
+
:param block: If True, excludes specified video IDs. If False, includes only specified video IDs
|
| 13 |
+
:return: Filtered list of video IDs
|
| 14 |
+
"""
|
| 15 |
+
filter_ids = set(filter_ids)
|
| 16 |
+
if block:
|
| 17 |
+
return [vid for vid in video_ids if vid not in filter_ids]
|
| 18 |
+
else:
|
| 19 |
+
return [vid for vid in video_ids if vid in filter_ids]
|
| 20 |
+
|
| 21 |
+
|
| 22 |
+
def filter_size(file_dir, file_ids, ext, size_limit=1024, filter_less=True):
|
| 23 |
+
"""
|
| 24 |
+
Filter files in a directory based on file size
|
| 25 |
+
|
| 26 |
+
:param file_dir: Directory path containing files
|
| 27 |
+
:param file_ids: List of file IDs to check
|
| 28 |
+
:param ext: File extension (e.g. '.mp4', '.avi')
|
| 29 |
+
:param size_limit: Size threshold in bytes
|
| 30 |
+
:param filter_less: If True, keeps files >= size_limit. If False, keeps files < size_limit
|
| 31 |
+
:return: List of file IDs that meet the size criteria
|
| 32 |
+
"""
|
| 33 |
+
if not ext.endswith("."):
|
| 34 |
+
ext = "." + ext
|
| 35 |
+
output_file_ids = []
|
| 36 |
+
for file_id in file_ids:
|
| 37 |
+
file_path = os.path.join(file_dir, file_id + ext)
|
| 38 |
+
if not os.path.exists(file_path):
|
| 39 |
+
continue
|
| 40 |
+
file_size = os.path.getsize(file_path)
|
| 41 |
+
if filter_less and file_size >= size_limit:
|
| 42 |
+
output_file_ids.append(file_id)
|
| 43 |
+
elif not filter_less and file_size < size_limit:
|
| 44 |
+
output_file_ids.append(file_id)
|
| 45 |
+
return output_file_ids
|
| 46 |
+
|
| 47 |
+
|
| 48 |
+
def filter_audio_channels(file_dir, file_ids, ext, num_channels):
|
| 49 |
+
"""
|
| 50 |
+
Filter files based on number of audio channels using ffmpeg
|
| 51 |
+
|
| 52 |
+
:param file_dir: Directory containing files
|
| 53 |
+
:param file_ids: List of file IDs to check
|
| 54 |
+
:param ext: File extension (e.g. '.mp3', '.wav')
|
| 55 |
+
:param num_channels: Target number of audio channels
|
| 56 |
+
:return: List of file IDs matching the channel count criteria
|
| 57 |
+
"""
|
| 58 |
+
if not ext.startswith("."):
|
| 59 |
+
ext = "." + ext
|
| 60 |
+
|
| 61 |
+
matching_files = []
|
| 62 |
+
|
| 63 |
+
for file_id in tqdm(file_ids):
|
| 64 |
+
# Construct full file path
|
| 65 |
+
file_path = os.path.join(file_dir, f"{file_id}{ext}")
|
| 66 |
+
|
| 67 |
+
# Verify file exists
|
| 68 |
+
if not os.path.exists(file_path):
|
| 69 |
+
print(f"File not found: {file_path}")
|
| 70 |
+
continue
|
| 71 |
+
|
| 72 |
+
try:
|
| 73 |
+
# Use ffprobe to check audio channel count
|
| 74 |
+
cmd = [
|
| 75 |
+
"ffprobe",
|
| 76 |
+
"-v",
|
| 77 |
+
"error", # Suppress verbose output
|
| 78 |
+
"-select_streams",
|
| 79 |
+
"a:0", # Select first audio stream
|
| 80 |
+
"-show_entries",
|
| 81 |
+
"stream=channels", # Get channel count
|
| 82 |
+
"-of",
|
| 83 |
+
"csv=p=0", # Format output
|
| 84 |
+
file_path,
|
| 85 |
+
]
|
| 86 |
+
result = subprocess.run(
|
| 87 |
+
cmd, capture_output=True, text=True, check=True
|
| 88 |
+
)
|
| 89 |
+
|
| 90 |
+
# Get channel count
|
| 91 |
+
channels = int(result.stdout.strip())
|
| 92 |
+
if channels == num_channels:
|
| 93 |
+
matching_files.append(file_id)
|
| 94 |
+
except subprocess.CalledProcessError as e:
|
| 95 |
+
print(f"Error processing file {file_path}: {e}")
|
| 96 |
+
except ValueError as e:
|
| 97 |
+
print(f"Invalid channel count for file {file_path}: {e}")
|
| 98 |
+
|
| 99 |
+
return matching_files
|
toolset/crawl/core/filters/ytfilter.py
ADDED
|
@@ -0,0 +1,58 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import json
|
| 2 |
+
|
| 3 |
+
def filter_360(youtube, video_ids, output_tmp=False):
|
| 4 |
+
"""
|
| 5 |
+
Filters and returns only 360-degree video IDs from the input list
|
| 6 |
+
|
| 7 |
+
:param youtube: Initialized YouTube API client object
|
| 8 |
+
:param video_ids: List of video IDs to filter
|
| 9 |
+
:param output_tmp: If True, saves intermediate results to temporary files
|
| 10 |
+
:return: List containing only 360-degree video IDs
|
| 11 |
+
"""
|
| 12 |
+
vr_video_ids = [] # List to store 360-degree video IDs
|
| 13 |
+
|
| 14 |
+
# Process videos in batches of 50 (YouTube API limit)
|
| 15 |
+
for i in range(0, len(video_ids), 50):
|
| 16 |
+
batch_video_ids = video_ids[i:i + 50] # Get current batch of 50 video IDs
|
| 17 |
+
|
| 18 |
+
# Request video details in batch
|
| 19 |
+
request = youtube.videos().list(
|
| 20 |
+
part="contentDetails",
|
| 21 |
+
id=",".join(batch_video_ids), # Comma-separated video IDs
|
| 22 |
+
)
|
| 23 |
+
response = request.execute()
|
| 24 |
+
|
| 25 |
+
# Optionally save intermediate results
|
| 26 |
+
if output_tmp:
|
| 27 |
+
with open(f"tmp/get_video_detail_{i // 50}.json", "w", encoding="utf-8") as f:
|
| 28 |
+
json.dump(response, f, indent=2)
|
| 29 |
+
|
| 30 |
+
# Check projection type for each video
|
| 31 |
+
for item in response.get("items", []):
|
| 32 |
+
if item["contentDetails"].get("projection", "") == "360":
|
| 33 |
+
vr_video_ids.append(item["id"])
|
| 34 |
+
|
| 35 |
+
return vr_video_ids
|
| 36 |
+
|
| 37 |
+
|
| 38 |
+
# Test function
|
| 39 |
+
if __name__ == "__main__":
|
| 40 |
+
from build import build_youtube
|
| 41 |
+
|
| 42 |
+
# Initialize YouTube API client
|
| 43 |
+
youtube = build_youtube()
|
| 44 |
+
|
| 45 |
+
# Test video IDs (mix of regular and 360 videos)
|
| 46 |
+
test_video_ids = [ # example videos
|
| 47 |
+
"spYqJw3WpCI",
|
| 48 |
+
"8AEhFvFMwBo",
|
| 49 |
+
"XToK00VcBI8",
|
| 50 |
+
]
|
| 51 |
+
|
| 52 |
+
# Filter 360 videos
|
| 53 |
+
vr_videos = filter_360(youtube, test_video_ids, output_tmp=True)
|
| 54 |
+
|
| 55 |
+
# Print results
|
| 56 |
+
print("\n360-degree Video IDs:")
|
| 57 |
+
for vid in vr_videos:
|
| 58 |
+
print(f"- {vid}")
|
toolset/crawl/core/search.py
ADDED
|
@@ -0,0 +1,153 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import json
|
| 2 |
+
import os
|
| 3 |
+
|
| 4 |
+
def search_videos(
|
| 5 |
+
youtube_client,
|
| 6 |
+
query,
|
| 7 |
+
num_pages=1,
|
| 8 |
+
max_results_per_page=50,
|
| 9 |
+
output_tmp=False,
|
| 10 |
+
use_cache=False,
|
| 11 |
+
tmp_path=None,
|
| 12 |
+
):
|
| 13 |
+
"""
|
| 14 |
+
Search videos using YouTube API and return video IDs, titles and other metadata
|
| 15 |
+
|
| 16 |
+
:param youtube_client: Initialized YouTube API client object
|
| 17 |
+
:param query: Search query keywords
|
| 18 |
+
:param num_pages: Number of result pages to fetch
|
| 19 |
+
:param max_results_per_page: Maximum results per page
|
| 20 |
+
:return: List of dictionaries containing video IDs, titles and other metadata
|
| 21 |
+
"""
|
| 22 |
+
if output_tmp or use_cache:
|
| 23 |
+
if tmp_path is None:
|
| 24 |
+
tmp_path = "tmp"
|
| 25 |
+
if output_tmp:
|
| 26 |
+
os.makedirs(tmp_path, exist_ok=True)
|
| 27 |
+
|
| 28 |
+
if tmp_path is not None:
|
| 29 |
+
tmp_path = os.path.join(tmp_path, "search")
|
| 30 |
+
os.makedirs(tmp_path, exist_ok=True)
|
| 31 |
+
|
| 32 |
+
video_info_list = [] # Store search results
|
| 33 |
+
next_page_token = None # Initialize pageToken for next page
|
| 34 |
+
|
| 35 |
+
for i in range(num_pages):
|
| 36 |
+
# Try reading from cache
|
| 37 |
+
if use_cache:
|
| 38 |
+
try:
|
| 39 |
+
with open(os.path.join(tmp_path, f"search_{i}.json"), "r", encoding="utf-8") as f:
|
| 40 |
+
search_response = json.load(f)
|
| 41 |
+
print(f"Using cache {os.path.join(tmp_path, f'search_{i}.json')}")
|
| 42 |
+
except FileNotFoundError:
|
| 43 |
+
search_response = None
|
| 44 |
+
|
| 45 |
+
if search_response is None:
|
| 46 |
+
# Execute video search
|
| 47 |
+
search_request = youtube_client.search().list(
|
| 48 |
+
part="snippet",
|
| 49 |
+
q=query,
|
| 50 |
+
type="video", # Only return videos
|
| 51 |
+
maxResults=max_results_per_page, # Results per page
|
| 52 |
+
pageToken=next_page_token, # pageToken from previous page (None for first request)
|
| 53 |
+
)
|
| 54 |
+
search_response = search_request.execute()
|
| 55 |
+
|
| 56 |
+
# Parse response to get video IDs, titles and metadata
|
| 57 |
+
for item in search_response["items"]:
|
| 58 |
+
video_info = {
|
| 59 |
+
"video_id": item["id"]["videoId"],
|
| 60 |
+
"title": item["snippet"]["title"],
|
| 61 |
+
"channel_id": item["snippet"]["channelId"],
|
| 62 |
+
"channel_title": item["snippet"]["channelTitle"],
|
| 63 |
+
"description": item["snippet"]["description"],
|
| 64 |
+
"publish_time": item["snippet"]["publishedAt"],
|
| 65 |
+
}
|
| 66 |
+
video_info_list.append(video_info)
|
| 67 |
+
|
| 68 |
+
if output_tmp:
|
| 69 |
+
with open(os.path.join(tmp_path, f"search_{i}.json"), "w", encoding="utf-8") as f:
|
| 70 |
+
f.write(json.dumps(search_response, indent=2))
|
| 71 |
+
|
| 72 |
+
# Get next page token
|
| 73 |
+
next_page_token = search_response.get("nextPageToken")
|
| 74 |
+
|
| 75 |
+
# Exit early if no more pages
|
| 76 |
+
if not next_page_token:
|
| 77 |
+
break
|
| 78 |
+
|
| 79 |
+
video_ids = [video["video_id"] for video in video_info_list]
|
| 80 |
+
return video_ids, video_info_list
|
| 81 |
+
|
| 82 |
+
|
| 83 |
+
def search_videos_360(
|
| 84 |
+
youtube, query, num_pages=1, max_results_per_page=50, output_tmp=False, use_cache=False, tmp_path=None
|
| 85 |
+
):
|
| 86 |
+
"""
|
| 87 |
+
Search for 360-degree videos using YouTube API
|
| 88 |
+
|
| 89 |
+
:param youtube: Initialized YouTube API client object
|
| 90 |
+
:param query: Search query keywords
|
| 91 |
+
:param num_pages: Number of result pages to fetch
|
| 92 |
+
:param max_results_per_page: Maximum results per page
|
| 93 |
+
:return: List of 360-degree video IDs
|
| 94 |
+
"""
|
| 95 |
+
from .filters import filter_360
|
| 96 |
+
|
| 97 |
+
video_ids, video_info_list = search_videos(
|
| 98 |
+
youtube, query, num_pages, max_results_per_page, output_tmp, use_cache, tmp_path
|
| 99 |
+
)
|
| 100 |
+
|
| 101 |
+
video_ids = filter_360(youtube, video_ids, False)
|
| 102 |
+
|
| 103 |
+
# Filter info
|
| 104 |
+
video_info_dict = {
|
| 105 |
+
video["video_id"]: video for video in video_info_list
|
| 106 |
+
}
|
| 107 |
+
video_info_list = []
|
| 108 |
+
for video_id in video_ids:
|
| 109 |
+
video_info_list.append(video_info_dict[video_id])
|
| 110 |
+
|
| 111 |
+
return video_ids, video_info_list
|
| 112 |
+
|
| 113 |
+
|
| 114 |
+
if __name__ == "__main__":
|
| 115 |
+
import argparse
|
| 116 |
+
|
| 117 |
+
parser = argparse.ArgumentParser()
|
| 118 |
+
parser.add_argument(
|
| 119 |
+
"-k",
|
| 120 |
+
"--key",
|
| 121 |
+
type=str,
|
| 122 |
+
help="Search query",
|
| 123 |
+
default="Spatial Audio 360",
|
| 124 |
+
)
|
| 125 |
+
parser.add_argument(
|
| 126 |
+
"--num-pages",
|
| 127 |
+
type=int,
|
| 128 |
+
help="Number of pages to search",
|
| 129 |
+
default=2,
|
| 130 |
+
)
|
| 131 |
+
parser.add_argument(
|
| 132 |
+
"--max-results",
|
| 133 |
+
type=int,
|
| 134 |
+
help="Max results per page",
|
| 135 |
+
default=50,
|
| 136 |
+
)
|
| 137 |
+
args = parser.parse_args()
|
| 138 |
+
query = args.key
|
| 139 |
+
num_pages = args.num_pages
|
| 140 |
+
max_results_per_page = args.max_results
|
| 141 |
+
from build import build_youtube
|
| 142 |
+
|
| 143 |
+
youtube = build_youtube()
|
| 144 |
+
|
| 145 |
+
video_ids, video_info_list = search_videos_360(
|
| 146 |
+
youtube, query, num_pages, max_results_per_page, True
|
| 147 |
+
)
|
| 148 |
+
|
| 149 |
+
# Output results
|
| 150 |
+
for video_id in video_ids:
|
| 151 |
+
print(video_id)
|
| 152 |
+
for video_info in video_info_list:
|
| 153 |
+
print(str(video_info))
|
toolset/crawl/download/download_list.py
ADDED
|
@@ -0,0 +1,27 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import sys
|
| 2 |
+
sys.path.append("..")
|
| 3 |
+
import core
|
| 4 |
+
from core import download
|
| 5 |
+
|
| 6 |
+
if __name__ == "__main__":
|
| 7 |
+
import argparse
|
| 8 |
+
parser = argparse.ArgumentParser()
|
| 9 |
+
parser.add_argument(
|
| 10 |
+
"-i", "--input-csv", type=str, required=True
|
| 11 |
+
)
|
| 12 |
+
parser.add_argument(
|
| 13 |
+
"-o", "--output-dir", type=str, required=True, help="Output directory"
|
| 14 |
+
)
|
| 15 |
+
parser.add_argument(
|
| 16 |
+
"-j", "--jobs", type=int, default=8, help="Number of jobs"
|
| 17 |
+
)
|
| 18 |
+
args = parser.parse_args()
|
| 19 |
+
input_csv = args.input_csv
|
| 20 |
+
output_dir = args.output_dir
|
| 21 |
+
jobs = args.jobs
|
| 22 |
+
|
| 23 |
+
download.download_list.download_list_360(
|
| 24 |
+
input_file = input_csv,
|
| 25 |
+
output_folder = output_dir,
|
| 26 |
+
jobs = jobs
|
| 27 |
+
)
|
toolset/crawl/download/download_list.sh
ADDED
|
@@ -0,0 +1,12 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#!/bin/bash
|
| 2 |
+
|
| 3 |
+
input_csv="" # input video ids
|
| 4 |
+
output_dir="" # output directory
|
| 5 |
+
jobs=8 # number of jobs
|
| 6 |
+
log_name="download.log" # log file name
|
| 7 |
+
|
| 8 |
+
python download_list.py \
|
| 9 |
+
-i "${input_csv}" \
|
| 10 |
+
-o "${output_dir}" \
|
| 11 |
+
-j ${jobs} \
|
| 12 |
+
> ${log_name}
|
toolset/crawl/filter/filter_exist.py
ADDED
|
@@ -0,0 +1,72 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import os
|
| 2 |
+
import csv
|
| 3 |
+
from tqdm import tqdm
|
| 4 |
+
|
| 5 |
+
# black-list database paths
|
| 6 |
+
# items within the video database or channel database will be filtered out
|
| 7 |
+
video_db_path = '' # Path to video_id database file
|
| 8 |
+
channel_db_path = '' # Path to channel_id database file
|
| 9 |
+
|
| 10 |
+
# Path to folder containing search results for filtering
|
| 11 |
+
folder_path = '' # Replace with actual folder path
|
| 12 |
+
output_csv = '' # Replace with actual output filename
|
| 13 |
+
|
| 14 |
+
def read_db(file_path, key_column):
|
| 15 |
+
"""Read values from a database CSV file"""
|
| 16 |
+
values = set()
|
| 17 |
+
with open(file_path, mode='r', newline='', encoding='utf-8') as f:
|
| 18 |
+
reader = csv.DictReader(f)
|
| 19 |
+
for row in reader:
|
| 20 |
+
values.add(row[key_column]) # Get values from specified column
|
| 21 |
+
return values
|
| 22 |
+
|
| 23 |
+
def process_csv_files(folder_path, video_db, channel_db):
|
| 24 |
+
"""Process all CSV files in the folder and filter results"""
|
| 25 |
+
result = set() # Stores final video_id results
|
| 26 |
+
before_filter = set() # Stores video_id results before filtering
|
| 27 |
+
for file_name in tqdm(os.listdir(folder_path)):
|
| 28 |
+
if file_name.endswith('.csv'):
|
| 29 |
+
file_path = os.path.join(folder_path, file_name)
|
| 30 |
+
with open(file_path, mode='r', newline='', encoding='utf-8') as f:
|
| 31 |
+
reader = csv.DictReader(f)
|
| 32 |
+
for row in reader:
|
| 33 |
+
video_id = row['video_id']
|
| 34 |
+
channel_id = row['channel_id']
|
| 35 |
+
before_filter.add(video_id)
|
| 36 |
+
# Check if video_id and channel_id exist in databases
|
| 37 |
+
if video_id not in video_db and channel_id not in channel_db:
|
| 38 |
+
result.add(video_id) # Add to results if not in databases
|
| 39 |
+
return result, before_filter
|
| 40 |
+
|
| 41 |
+
def main():
|
| 42 |
+
# Read databases
|
| 43 |
+
video_db = read_db(video_db_path, 'video_id')
|
| 44 |
+
channel_db = read_db(channel_db_path, 'channel_id')
|
| 45 |
+
|
| 46 |
+
print(f"Video DB: {video_db_path} ({len(video_db)} records)")
|
| 47 |
+
print(f"Channel DB: {channel_db_path} ({len(channel_db)} records)")
|
| 48 |
+
|
| 49 |
+
# Process CSV files in folder
|
| 50 |
+
result, before_filter = process_csv_files(folder_path, video_db, channel_db)
|
| 51 |
+
|
| 52 |
+
# Output final results
|
| 53 |
+
print(f"Number of video_id: {len(result)}/{len(before_filter)}")
|
| 54 |
+
|
| 55 |
+
# Write pre-filter results
|
| 56 |
+
with open(f"before_filter_{output_csv}", mode='w', newline='', encoding='utf-8') as f:
|
| 57 |
+
dict_writer = csv.DictWriter(f, fieldnames=['video_id'])
|
| 58 |
+
dict_writer.writeheader()
|
| 59 |
+
for video_id in before_filter:
|
| 60 |
+
dict_writer.writerow({'video_id': video_id})
|
| 61 |
+
print(f"Before filter results saved to: before_filter_{output_csv}")
|
| 62 |
+
|
| 63 |
+
# Write final filtered results
|
| 64 |
+
with open(output_csv, mode='w', newline='', encoding='utf-8') as f:
|
| 65 |
+
dict_writer = csv.DictWriter(f, fieldnames=['video_id'])
|
| 66 |
+
dict_writer.writeheader()
|
| 67 |
+
for video_id in result:
|
| 68 |
+
dict_writer.writerow({'video_id': video_id})
|
| 69 |
+
print(f"Filtered results saved to: {output_csv}")
|
| 70 |
+
|
| 71 |
+
if __name__ == "__main__":
|
| 72 |
+
main()
|
toolset/crawl/requirements.txt
ADDED
|
@@ -0,0 +1,5 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
google_api_python_client==2.155.0
|
| 2 |
+
httplib2==0.22.0
|
| 3 |
+
pandas==2.2.3
|
| 4 |
+
Requests==2.32.3
|
| 5 |
+
tqdm==4.67.1
|
toolset/crawl/search/search.py
ADDED
|
@@ -0,0 +1,57 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
from tqdm import tqdm
|
| 2 |
+
import json
|
| 3 |
+
import os
|
| 4 |
+
import csv
|
| 5 |
+
import sys
|
| 6 |
+
sys.path.append('..')
|
| 7 |
+
from core import search, build
|
| 8 |
+
|
| 9 |
+
def output_to_csv(video_info_list, output_file):
|
| 10 |
+
os.makedirs(os.path.dirname(output_file), exist_ok=True)
|
| 11 |
+
with open(output_file, 'w') as f:
|
| 12 |
+
if len(video_info_list) == 0:
|
| 13 |
+
return
|
| 14 |
+
dict_writer = csv.DictWriter(f, fieldnames=video_info_list[0].keys())
|
| 15 |
+
dict_writer.writeheader()
|
| 16 |
+
for video_info in video_info_list:
|
| 17 |
+
dict_writer.writerow(video_info)
|
| 18 |
+
|
| 19 |
+
if __name__ == "__main__":
|
| 20 |
+
import argparse
|
| 21 |
+
parser = argparse.ArgumentParser()
|
| 22 |
+
parser.add_argument('-i', '--input', type=str, required=True, help='Input file with keywords')
|
| 23 |
+
parser.add_argument('-o', '--output', type=str, required=True)
|
| 24 |
+
parser.add_argument('-n', '--num-pages', type=int, default=1)
|
| 25 |
+
parser.add_argument('-p', '--postfix', type=str, default=None)
|
| 26 |
+
parser.add_argument('-t', '--tmp-path', type=str)
|
| 27 |
+
args = parser.parse_args()
|
| 28 |
+
output = args.output
|
| 29 |
+
num_pages = args.num_pages
|
| 30 |
+
tmp_path = args.tmp_path
|
| 31 |
+
|
| 32 |
+
with open(args.input, 'r') as f:
|
| 33 |
+
keywords = f.readlines()
|
| 34 |
+
keywords = [keyword.strip() for keyword in keywords]
|
| 35 |
+
|
| 36 |
+
print(f'Searching for {len(keywords)} keywords')
|
| 37 |
+
|
| 38 |
+
youtube = build.build_youtube()
|
| 39 |
+
|
| 40 |
+
pbar = tqdm(keywords)
|
| 41 |
+
for keyword in pbar:
|
| 42 |
+
if args.postfix:
|
| 43 |
+
keyword += args.postfix
|
| 44 |
+
pbar.set_description(f'{keyword}')
|
| 45 |
+
|
| 46 |
+
out_path = os.path.join(output, f'{keyword}.csv')
|
| 47 |
+
if os.path.exists(out_path):
|
| 48 |
+
print(f"Skip {keyword}")
|
| 49 |
+
continue
|
| 50 |
+
|
| 51 |
+
video_ids, video_info_list = search.search_videos_360(
|
| 52 |
+
youtube, keyword, num_pages, 50, True, True, os.path.join(tmp_path, f'{keyword}')
|
| 53 |
+
)
|
| 54 |
+
out_path = os.path.join(output, f'{keyword}.csv')
|
| 55 |
+
output_to_csv(video_info_list, out_path)
|
| 56 |
+
|
| 57 |
+
print(f'Finished searching for {len(keywords)} keywords')
|
toolset/crawl/search/search.sh
ADDED
|
@@ -0,0 +1,19 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#!/bin/bash
|
| 2 |
+
num_pages=1 # Number of search pages (max 50 results per page)
|
| 3 |
+
|
| 4 |
+
keyword_file='' # Keyword file
|
| 5 |
+
postfix=" spatial audio 360" # Keyword suffix, e.g., "spatial audio 360"
|
| 6 |
+
tmp_dir="tmp/" # Temporary folder for search results
|
| 7 |
+
output_dir="search_result/" # Final output folder for all search results
|
| 8 |
+
|
| 9 |
+
log_file="search.log" # Log file
|
| 10 |
+
|
| 11 |
+
# Search and output initial results
|
| 12 |
+
python search.py \
|
| 13 |
+
-i "$keyword_file" \
|
| 14 |
+
-o "$output_dir" \
|
| 15 |
+
-n "$num_pages" \
|
| 16 |
+
-p "$postfix" \
|
| 17 |
+
-t "$tmp_dir" \
|
| 18 |
+
--aid-id "$aid_id" \
|
| 19 |
+
> $log_file
|