| | import os |
| | import io |
| | import av |
| | import json |
| | from pickle import dumps, loads |
| | import numpy as np |
| | import torch |
| | from torchvision.transforms.functional import resize |
| | import tensorflow as tf |
| | import tensorflow_datasets as tfds |
| | from einops import rearrange |
| |
|
| | def decode_inst(insts): |
| | |
| | decoded_insts = [] |
| | for inst in insts: |
| | decoded_insts.append(bytes(inst[np.where(inst != 0)].tolist()).decode("utf-8")) |
| | return decoded_insts |
| |
|
| | def save_video(file, video): |
| | container = av.open(file, 'w', 'mp4') |
| | stream = container.add_stream('libx264', rate=30) |
| | stream.height = video[0].shape[0] |
| | stream.width = video[0].shape[1] |
| | stream.bit_rate = 2000000 |
| | stream.pix_fmt = 'yuv420p' |
| | for i in range(len(video)): |
| | frame = av.VideoFrame.from_ndarray(video[i], format='rgb24') |
| | frame = frame.reformat(format=stream.pix_fmt) |
| | for packet in stream.encode(frame): |
| | container.mux(packet) |
| | |
| | for packet in stream.encode(): |
| | container.mux(packet) |
| | container.close() |
| |
|
| | if __name__ == '__main__': |
| | tf_builder = tfds.builder_from_directory('./droid/1.0.0/') |
| | tf_dataset = tf_builder.as_dataset(split="train") |
| | skip_episode = 78663 |
| | js_path = 'index.json' |
| | if os.path.exists(js_path): |
| | js_data = json.load(open(js_path, 'r')) |
| | else: |
| | js_data = [] |
| | for episode_id, episode in enumerate(tf_dataset): |
| | file_path = episode['episode_metadata']['file_path'].numpy().decode('utf-8') |
| | recording_folderpath = episode['episode_metadata']['recording_folderpath'].numpy().decode('utf-8') |
| | if episode_id <= skip_episode or 'success' not in file_path: |
| | print(f'skipping {episode_id}/{len(tf_dataset)}') |
| | continue |
| | left_camera = [] |
| | arm_camera = [] |
| | right_camera = [] |
| | inst = [] |
| | skip_episode = False |
| | for step_id, single_step in enumerate(episode['steps']): |
| | if single_step['language_instruction'].numpy().decode('utf-8') not in inst: |
| | inst.append(single_step['language_instruction'].numpy().decode('utf-8')) |
| | if single_step['language_instruction_2'].numpy().decode('utf-8') not in inst: |
| | inst.append(single_step['language_instruction_2'].numpy().decode('utf-8')) |
| | if single_step['language_instruction_3'].numpy().decode('utf-8') not in inst: |
| | inst.append(single_step['language_instruction_3'].numpy().decode('utf-8')) |
| | if len(inst) == 1 and inst[0] == '': |
| | skip_episode = True |
| | break |
| | left_camera.append(single_step['observation']['exterior_image_1_left'].numpy()) |
| | right_camera.append(single_step['observation']['exterior_image_2_left'].numpy()) |
| | arm_camera.append(single_step['observation']['wrist_image_left'].numpy()) |
| | if skip_episode: |
| | print(f'skipping {episode_id}/{len(tf_dataset)}') |
| | continue |
| | print(f'saving {episode_id}/{len(tf_dataset)}') |
| | save_video(f'droid_videos/episode_{episode_id}_left_camera.mp4', left_camera) |
| | save_video(f'droid_videos/episode_{episode_id}_right_camera.mp4', right_camera) |
| | save_video(f'droid_videos/episode_{episode_id}_arm_camera.mp4', arm_camera) |
| | for i in range(len(inst)): |
| | if inst[i] == '': |
| | continue |
| | js_data.append({"path": f'droid_videos/episode_{episode_id}_left_camera.mp4', "recording_folder": recording_folderpath, "cap": [inst[i]]}) |
| | js_data.append({"path": f'droid_videos/episode_{episode_id}_right_camera.mp4', "recording_folder": recording_folderpath, "cap": [inst[i]]}) |
| | js_data.append({"path": f'droid_videos/episode_{episode_id}_arm_camera.mp4', "recording_folder": recording_folderpath, "cap": [inst[i]]}) |
| | if episode_id % 1000 < 10: |
| | json.dump(js_data, open(js_path, 'w'), indent=4) |
| | json.dump(js_data, open(js_path, 'w'), indent=4) |
| |
|
