from diffusers.utils import export_to_video, load_video from decord import VideoReader, cpu import numpy as np import os import random action_name = "camera4" # your action name, same with the reference video name subject_type = "camera" # camera, human, animal start_second = 3 # start second of the action end_second = 9 # end second of the action crop_ratio = 0.8 video_path = f"benchmark/reference_videos/{subject_type}/{action_name}.mp4" # path to the reference video video = load_video(video_path) # fps cpu_idx = random.randint(0, os.cpu_count() - 1) vr = VideoReader(video_path, ctx=cpu(cpu_idx)) first_frame = vr[0] height, width = first_frame.shape[:2] fps = int(round(vr.get_avg_fps())) print(f"fps: {fps}") print(f"height: {height}, width: {width}, length: {len(video)}") # video = video[::fps//8] video = video[round(start_second*fps):round(end_second*fps)] # uniformly sample 49 frames video = [video[int(i*len(video)/49)] for i in range(49)] name, postfix = video_path.split(".") cur_dir = f"benchmark/reference_videos/{subject_type}" os.makedirs(f"{cur_dir}/{action_name}_crop", exist_ok=True) top_left = (0, 0, int(height * crop_ratio), int(width * crop_ratio)) top_center = (0, int(width * ((1 - crop_ratio) / 2)), int(height * crop_ratio), int(width * crop_ratio)) top_right = (0, int(width * (1 - crop_ratio)), int(height * crop_ratio), int(width * crop_ratio)) center_left = (int(height * ((1 - crop_ratio) / 2)), 0, int(height * crop_ratio), int(width * crop_ratio)) center_center = (int(height * ((1 - crop_ratio) / 2)), int(width * ((1 - crop_ratio) / 2)), int(height * crop_ratio), int(width * crop_ratio)) center_right = (int(height * ((1 - crop_ratio) / 2)), int(width * (1 - crop_ratio)), int(height * crop_ratio), int(width * crop_ratio)) bottom_left = (int(height * (1 - crop_ratio)), 0, int(height * crop_ratio), int(width * crop_ratio)) bottom_center = (int(height * (1 - crop_ratio)), int(width * ((1 - crop_ratio) / 2)), int(height * crop_ratio), int(width * crop_ratio)) bottom_right = (int(height * (1 - crop_ratio)), int(width * (1 - crop_ratio)), int(height * crop_ratio), int(width * crop_ratio)) ori = (0, 0, height, width) crop_areas = [top_left, top_center, top_right, center_left, center_center, center_right, bottom_left, bottom_center, bottom_right, ori, ori, ori] # Random Crop video = np.array(video) for crop_area in crop_areas: video_crop = [frame[crop_area[0]:crop_area[0]+crop_area[2], crop_area[1]:crop_area[1]+crop_area[3]] / 255.0 for frame in video] idx = 0 while os.path.exists(f"{cur_dir}/{action_name}_crop/{idx}.{postfix}"): idx += 1 export_to_video(video_crop, f"{cur_dir}/{action_name}_crop/{idx}.{postfix}")