| import os | |
| import random | |
| import numpy as np | |
| def dense_sampling_from_extracted_frames(folder_path, num_clips=6, frames_per_clip=5): | |
| frame_files = sorted([os.path.join(folder_path, f) for f in os.listdir(folder_path) if f.endswith('.npy')]) | |
| num_frames = len(frame_files) | |
| print(f"Found {num_frames} frames in {folder_path}") | |
| if num_frames < num_clips * frames_per_clip: | |
| raise ValueError("Not enough frames to sample the required clips.") | |
| frames_per_segment = num_frames // num_clips | |
| clips = [] | |
| for i in range(num_clips): | |
| segment_start = i * frames_per_segment | |
| segment_end = segment_start + frames_per_segment - 1 | |
| max_start_frame = segment_end - frames_per_clip + 1 | |
| start_frame = random.randint(segment_start, max_start_frame) | |
| clip = [np.load(frame_files[start_frame + j]) for j in range(frames_per_clip)] | |
| clips.append(clip) | |
| return clips | |