''' python video_filter.py input_video.mp4 mask_area_ratios.json 0.1 filtered_video_01.mp4 python video_filter.py input_video.mp4 mask_area_ratios.json 0.0 filtered_video_00.mp4 ''' import argparse import cv2 import json import os import numpy as np from moviepy.editor import ImageSequenceClip def process_video(video_path, json_path, threshold, output_path): # 读取视频 if os.path.exists("input_video.mp4"): video_path = "input_video.mp4" cap = cv2.VideoCapture(video_path) input_fps = cap.get(cv2.CAP_PROP_FPS) # 获取输入视频的帧率 total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT)) # 获取总帧数 # 读取所有帧 all_frames = [] while True: ret, frame = cap.read() if not ret: break frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) # 转换为RGB all_frames.append(frame_rgb) cap.release() # 读取JSON文件 with open(json_path, 'r') as f: mask_area_ratios = json.load(f) # 获取mask_area_ratios中的帧索引和对应的ratio frame_indices = [int(key.split("_")[1]) for key in mask_area_ratios.keys()] ratios = [mask_area_ratios[key] for key in mask_area_ratios.keys()] # 创建一个长度为 total_frames 的数组来存储对应的 ratio all_ratios = [None] * len(all_frames) # 将 mask_area_ratios 的帧索引和对应的 ratio 映射到 all_ratios for frame_index, ratio in zip(frame_indices, ratios): scaled_index = int(frame_index * (len(all_frames) - 1) / max(frame_indices)) all_ratios[scaled_index] = ratio # 填充缺失的 ratio 值,使用最邻近值 for i in range(len(all_ratios)): if all_ratios[i] is None: # 找到最近的非空值 left_index = i - 1 right_index = i + 1 while left_index >= 0 and all_ratios[left_index] is None: left_index -= 1 while right_index < len(all_ratios) and all_ratios[right_index] is None: right_index += 1 if left_index >= 0 and right_index < len(all_ratios): # 使用最近的左边或右边的值 all_ratios[i] = all_ratios[left_index] if all_ratios[left_index] is not None else all_ratios[right_index] elif left_index >= 0: all_ratios[i] = all_ratios[left_index] elif right_index < len(all_ratios): all_ratios[i] = all_ratios[right_index] # 筛选符合条件的帧 frames = [] for frame_idx, ratio in enumerate(all_ratios): if ratio >= threshold: frames.append(all_frames[frame_idx]) # 保存符合条件的帧为视频 if frames: clip = ImageSequenceClip(frames, fps=input_fps) # 使用输入视频的帧率 clip.write_videofile(output_path, codec="libx264") print(f"Output video saved to {output_path}") else: print("No frames meet the threshold condition.") if __name__ == "__main__": parser = argparse.ArgumentParser(description="Filter video frames based on mask area ratios.") parser.add_argument("video_path", type=str, nargs='?', default="input_video.mp4", help="Path to the input video file. Default: input_video.mp4") parser.add_argument("json_path", type=str, nargs='?', default="mask_area_ratios.json", help="Path to the JSON file containing mask area ratios. Default: mask_area_ratios.json") parser.add_argument("threshold", type=float, nargs='?', default=0.25, help="Threshold for mask area ratio. Default: 0.25") parser.add_argument("output_path", type=str, nargs='?', default="output_seg_video.mp4", help="Path to save the output video. Default: output_seg_video.mp4") args = parser.parse_args() process_video(args.video_path, args.json_path, args.threshold, args.output_path)