| import cv2 | |
| import json | |
| import os | |
| import sys | |
| from .pose import PoseEstimator | |
| def preprocess_video(video_path, output_json_path): | |
| cap = cv2.VideoCapture(video_path) | |
| if not cap.isOpened(): | |
| print(f"Error: Could not open video {video_path}") | |
| return | |
| estimator = PoseEstimator(model_complexity=2) # Higher complexity for reference | |
| all_landmarks = [] | |
| frame_count = 0 | |
| while cap.isOpened(): | |
| ret, frame = cap.read() | |
| if not ret: | |
| break | |
| results = estimator.process_frame(frame) | |
| landmarks = estimator.extract_landmarks(results) | |
| all_landmarks.append({ | |
| "frame": frame_count, | |
| "landmarks": landmarks | |
| }) | |
| frame_count += 1 | |
| if frame_count % 30 == 0: | |
| print(f"Processed {frame_count} frames...") | |
| with open(output_json_path, 'w') as f: | |
| json.dump(all_landmarks, f) | |
| cap.release() | |
| estimator.close() | |
| print(f"Finished! Saved to {output_json_path}") | |
| if __name__ == "__main__": | |
| if len(sys.argv) < 3: | |
| print("Usage: python -m src.core.preprocess_reference <video_path> <output_json_path>") | |
| else: | |
| preprocess_video(sys.argv[1], sys.argv[2]) | |