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+ # `myshell_nsfw_filter` Image Classification with Hugging Face Transformers
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+ This README demonstrates how to use the `myshell_nsfw_filter` model hosted on Hugging Face for image classification.
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+
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+ ## Prerequisites
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+
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+ 1. Install the required Python packages:
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+ ```bash
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+ pip install transformers requests Pillow
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+ ```
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+
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+ ## Example Usage
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+
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+ Here's a step-by-step Python code example to classify an image:
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+ ```python
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+ from transformers import pipeline
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+ import requests
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+ from PIL import Image
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+ from io import BytesIO
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+
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+ # 1. Load the pipeline for image classification
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+ pipe = pipeline("image-classification", model="zguo0525/myshell_nsfw_filter")
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+
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+ # 2. Load the image into memory (assuming you have the URL for the image)
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+ image_url = 'https://img-myshell.net/meinamix/red_hair_girl'
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+ response = requests.get(image_url)
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+ image = Image.open(BytesIO(response.content))
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+
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+ # 3. Use the pipeline to classify the image
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+ results = pipe(image)
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+
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+ # 4. Print the results
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+ label = results[0]['label']
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+ score = results[0]['score']
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+ print(f"{label}: {score:.4f}")
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+ ```
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+
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+ ## Conclusion
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+ Using the Hugging Face Transformers library, it's straightforward to load and classify images with the `myshell_nsfw_filter` model. This README showcased a simple example, and you can easily adapt it for your own images or applications!
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+
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+ ---
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+ You can use this content for the README.md file in your repository. This provides a clear introduction and step-by-step guidance for users looking to leverage your model.