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Add 25 real world datasets (static + mobile aloha) (#133)

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Remi 2024-05-05 19:13:11 +02:00 committed by GitHub
parent 6e6feae09e
commit 6eaffbef1d
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29 changed files with 502 additions and 84 deletions
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28
lerobot/__init__.py
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@ -9,6 +9,7 @@ Example:
print(lerobot.available_tasks_per_env) print(lerobot.available_tasks_per_env)
print(lerobot.available_datasets) print(lerobot.available_datasets)
print(lerobot.available_datasets_per_env) print(lerobot.available_datasets_per_env)
print(lerobot.available_real_world_datasets)
print(lerobot.available_policies) print(lerobot.available_policies)
print(lerobot.available_policies_per_env) print(lerobot.available_policies_per_env)
``` ```
@ -55,10 +56,33 @@ available_datasets_per_env = {
], ],
} }
available_datasets_without_env = ["lerobot/umi_cup_in_the_wild"] available_real_world_datasets = [
"lerobot/aloha_mobile_cabinet",
"lerobot/aloha_mobile_chair",
"lerobot/aloha_mobile_elevator",
"lerobot/aloha_mobile_shrimp",
"lerobot/aloha_mobile_wash_pan",
"lerobot/aloha_mobile_wipe_wine",
"lerobot/aloha_static_battery",
"lerobot/aloha_static_candy",
"lerobot/aloha_static_coffee",
"lerobot/aloha_static_coffee_new",
"lerobot/aloha_static_cups_open",
"lerobot/aloha_static_fork_pick_up",
"lerobot/aloha_static_pingpong_test",
"lerobot/aloha_static_pro_pencil",
"lerobot/aloha_static_screw_driver",
"lerobot/aloha_static_tape",
"lerobot/aloha_static_thread_velcro",
"lerobot/aloha_static_towel",
"lerobot/aloha_static_vinh_cup",
"lerobot/aloha_static_vinh_cup_left",
"lerobot/aloha_static_ziploc_slide",
"lerobot/umi_cup_in_the_wild",
]
available_datasets = list( available_datasets = list(
itertools.chain(*available_datasets_per_env.values(), available_datasets_without_env) itertools.chain(*available_datasets_per_env.values(), available_real_world_datasets)
) )
# TODO(rcadene, aliberts, alexander-soare): Add real-world env with a gym API # TODO(rcadene, aliberts, alexander-soare): Add real-world env with a gym API

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lerobot/common/datasets/push_dataset_to_hub/_aloha_raw_urls/mobile_cabinet.txt Normal file
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https://drive.google.com/file/d/1_SOJkgfP5yZyVjMhTt3nwhvyUjcnlI51/view?usp=drive_link
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https://drive.google.com/file/d/1KzL3Tt0Le7jVl58XVRUcmigmXjyiuhbK/view?usp=drive_link
https://drive.google.com/file/d/1qy_YBladeHtianSSGtgAPSHtMin7msvf/view?usp=drive_link
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lerobot/common/datasets/push_dataset_to_hub/_aloha_raw_urls/mobile_chair.txt Normal file
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lerobot/common/datasets/push_dataset_to_hub/_aloha_raw_urls/mobile_elevator.txt Normal file
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https://drive.google.com/file/d/1CyTVkdrNGGpouCXr4CfhKbMzE6Ah3oo3/view?usp=drive_link
https://drive.google.com/file/d/1hDRyeM-XEDpHXpptbT8LvNnlQUR3PWOh/view?usp=drive_link
https://drive.google.com/file/d/1XhHWxbra8Iy5irQZ83IvxwaJqHq9x4s1/view?usp=drive_link
https://drive.google.com/file/d/1haZcn6aM1o4JlmP9tJj3x2enrxiPaDSD/view?usp=drive_link
https://drive.google.com/file/d/1ypDyuUTbljaBZ34f-t7lj3O_0bRmyX2n/view?usp=drive_link
https://drive.google.com/file/d/1ILEEZo_tA9_ChIAprr2mPaNVKZi5vXsO/view?usp=drive_link
https://drive.google.com/file/d/1U7nVYFaGE8vVTfLCW33D74xOjDcqfgyJ/view?usp=drive_link
https://drive.google.com/file/d/1rZ93_rmCov5SMDxPkfM3qthcRELZrQX6/view?usp=drive_link
https://drive.google.com/file/d/1mYO1b_csddtyE3qT6cwLiw-m2w2_1Lxh/view?usp=drive_link
https://drive.google.com/file/d/1xz7Q5x2jikY8wJQjMRQpRws6AnfWlHm5/view?usp=drive_link
https://drive.google.com/file/d/1OO8GaO-0FrSZRd1kxMYwBmubyiLOWnbl/view?usp=drive_link
https://drive.google.com/file/d/1EXn4NVDmf-4_HCy34mYwT-vwK2CFI9ev/view?usp=drive_link
https://drive.google.com/file/d/10hH70XhXRL9C5SnAG4toHtfHqfJUJo4H/view?usp=drive_link
https://drive.google.com/file/d/18tiBcxea0guUai4lwsXQvt0q2LZ8ZnnJ/view?usp=drive_link
https://drive.google.com/file/d/1Q8R8qv37vk5PQ5kQ2ibx6BFLOySD0VpX/view?usp=drive_link
https://drive.google.com/file/d/17aNriHzjhdibCyuUjQoMFZqjybJZtggG/view?usp=drive_link
https://drive.google.com/file/d/1LVjEYHSdeKm6CotU1QguIeNEPaIaFl_1/view?usp=drive_link
https://drive.google.com/file/d/1ufAhE_EkgJ85slg2EW8aW_grOzE_Lmxd/view?usp=drive_link
https://drive.google.com/file/d/1wtzLtXrkw9eXRGESTPIOlpl1tInu-b2m/view?usp=drive_link
https://drive.google.com/file/d/1Mk5qvVtD_QHwGOUApRq76TUw2T5THu6f/view?usp=drive_link
https://drive.google.com/file/d/1y1WQ3hboWVJ68KEYQQ3OhreGuaUpSgwc/view?usp=drive_link

52
lerobot/common/datasets/push_dataset_to_hub/_aloha_raw_urls/static_vinh_cup_left.txt Normal file
View File

@ -0,0 +1,52 @@
https://drive.google.com/drive/folders/1dxWh6YFZUDt6qXIoxgD9bla3CiFjZ11C
https://drive.google.com/file/d/1hNBJN00SCAlOl0ZEgm7RRGbAGDjyBs0p/view?usp=drive_link
https://drive.google.com/file/d/17He0CVwXGeoMmXg4SHKo-osNn7YPKVL7/view?usp=drive_link
https://drive.google.com/file/d/1laNKUVID1x2CV6a2O2WQjwFewKu4lidL/view?usp=drive_link
https://drive.google.com/file/d/1pNf36xbZJGRArYLmNAvRj5y6CoqdC6kB/view?usp=drive_link
https://drive.google.com/file/d/1_4E1-y3JXk5I0ebycLYM70YDPK9g52gZ/view?usp=drive_link
https://drive.google.com/file/d/1PHfzhGPdbolKyOpS3FnR2w7Q8zUlJXSk/view?usp=drive_link
https://drive.google.com/file/d/17ls2PPN-Pi3tEuK059cwV2_iDT8aGhOO/view?usp=drive_link
https://drive.google.com/file/d/1LWsg6PmCT00Kv_N_slrmcwKmQPGoBT3k/view?usp=drive_link
https://drive.google.com/file/d/12LckrchoHTUVH7rxi8J7zD9dA19GXvoW/view?usp=drive_link
https://drive.google.com/file/d/1VqrJKjAIkj5gtFXL69grdSeu9CyaqnSw/view?usp=drive_link
https://drive.google.com/file/d/1g5rQYDBZvW-kUtYPeyF3qmd53v6k7kXu/view?usp=drive_link
https://drive.google.com/file/d/10kUgaSJ0TS7teaG83G3Rf_DG4XGrBt6A/view?usp=drive_link
https://drive.google.com/file/d/1je9XmneZQZvTma5adMJICUPDovW3ppei/view?usp=drive_link
https://drive.google.com/file/d/1v28r6bedwZGbUPVVTVImXhK-42XdtGfj/view?usp=drive_link
https://drive.google.com/file/d/1-TEEx9sGVvzMMaNXYfQMtY2JJ6cvl0dT/view?usp=drive_link
https://drive.google.com/file/d/1YdBKdJFP9rJWBUX7qrOYL_gfUA8o6J9M/view?usp=drive_link
https://drive.google.com/file/d/1X9vffwQHNUSKLXr2RlYNtbWDIFCIDfdF/view?usp=drive_link
https://drive.google.com/file/d/11hqesqa5kvEe5FABUnZRcvmOhR373cYM/view?usp=drive_link
https://drive.google.com/file/d/1ltTTECjEcbQPgS3UPRgMzaE2x9n6H7dC/view?usp=drive_link
https://drive.google.com/file/d/1Zxqfa29JdwT-bfMpivi6IG2vz34d21dD/view?usp=drive_link
https://drive.google.com/file/d/11LQlVxS5hz494dYUJ_PNRPx2NHIJbQns/view?usp=drive_link
https://drive.google.com/file/d/1i1JhNtnZpO_E8rAv8gxBP3ZTZRvcvsZi/view?usp=drive_link
https://drive.google.com/file/d/11jOXAr2EULUO4Qkm748634lg4UUFho5U/view?usp=drive_link
https://drive.google.com/file/d/1rj67wur8DdB_Pipwx24bY43xu4X1eQ5e/view?usp=drive_link
https://drive.google.com/file/d/15ZTm6lO6f_JQy_4SNfrOu3iPYn1Ro8mh/view?usp=drive_link
https://drive.google.com/file/d/1q4gBtqWPJtCwXEvknGgN0WHGp7Vfn1b9/view?usp=drive_link
https://drive.google.com/file/d/1t17keyre47AYqm8GgXiQ7EcvcUkeSiDQ/view?usp=drive_link
https://drive.google.com/file/d/1OYUPGxtZgOF86Ng_BEOTXm_XOYpuQPsO/view?usp=drive_link
https://drive.google.com/file/d/1cBjbGHi3dwWHtx6r9EQJi0JT_CE3LuHt/view?usp=drive_link
https://drive.google.com/file/d/14qaMyF0mcbCB-fCYKNyo5_2NahSC6D5u/view?usp=drive_link
https://drive.google.com/file/d/12FgX86eA7Y5co9ULBVK80XMsiKQSs-Ri/view?usp=drive_link
https://drive.google.com/file/d/1yvoHWidf-jdBVw6qCCXOFfkVwKj_2hPk/view?usp=drive_link
https://drive.google.com/file/d/1a2SugsSDlC8UtUrFzp-_KAwyZckQOvdQ/view?usp=drive_link
https://drive.google.com/file/d/1l8pILBFSAosypWJMza2K09Vm7rug9axm/view?usp=drive_link
https://drive.google.com/file/d/1hfPQ8dBCk97PnOhq6_MIISm3IEzcOxJG/view?usp=drive_link
https://drive.google.com/file/d/1PPAUwlJCFKpms8cqF_k1v2_fCgDBOc3S/view?usp=drive_link
https://drive.google.com/file/d/1lVKQZeqFfK3amEmLuFhYLUFQ2eyE8rOW/view?usp=drive_link
https://drive.google.com/file/d/1K9iPMLfDowcIFoyzpvgn88dQ6x6kVwNG/view?usp=drive_link
https://drive.google.com/file/d/1PNvMqG9tL7QxeLaYBGHiWYR6SYb5iIct/view?usp=drive_link
https://drive.google.com/file/d/1xkRtzbvIkUsylx9hrFLGQsJn0h1EYu-5/view?usp=drive_link
https://drive.google.com/file/d/1nxMRrJlSayjDIfr5CmHO1NzAw3COhsLi/view?usp=drive_link
https://drive.google.com/file/d/1Qs3WEyMGrmagiHIkkFEueWNnJhkUeR1s/view?usp=drive_link
https://drive.google.com/file/d/1D-G2_Q0SS3M8zyJbg_XzkF2ANPw1HTuX/view?usp=drive_link
https://drive.google.com/file/d/1mdmJsDGO-YtJAOF_yPKl6lq4PJOIbQhT/view?usp=drive_link
https://drive.google.com/file/d/11m9bwfop_sPmnQr_8amB6EEsrbAeG_z5/view?usp=drive_link
https://drive.google.com/file/d/19tyYt5FMn5kru0g9o2nMJhKPnsDqkIZv/view?usp=drive_link
https://drive.google.com/file/d/1XvTpUdsVTZ-vydvdYYmynbma--HfUGSl/view?usp=drive_link
https://drive.google.com/file/d/1MO3hFu68J6NohTzr9aB_fY02VA6QSOqj/view?usp=drive_link
https://drive.google.com/file/d/1Lh-UjwAk__04YOTWINF_QGVU8SjetVaY/view?usp=drive_link
https://drive.google.com/file/d/1jkSOUwZV5GJ7rZlVeErjcu0DBQs8Np0d/view?usp=drive_link
https://drive.google.com/file/d/1VIN1eLI-93WrVQwCjsv6XQr353DqqBYA/view?usp=drive_link

8
lerobot/common/datasets/push_dataset_to_hub/_aloha_raw_urls/static_ziploc_slide.txt Normal file
View File

@ -0,0 +1,8 @@
https://drive.google.com/drive/folders/1EgKar7rWBmTIRmeJYZciSwjZx3uP2mHO
https://drive.google.com/file/d/12eYWQO15atK2hBjXhynPJd9MKAj_42pz/view?usp=drive_link
https://drive.google.com/file/d/1Ul4oEeICJDjgfYTl4H1uaisTzVYIM6wd/view?usp=drive_link
https://drive.google.com/file/d/1WSF-OG8lKSe2wVYCv5D1aJNipxpgddk-/view?usp=drive_link
https://drive.google.com/file/d/1_ppD5j5sFh26aWW0JmhLzJMeNB-lCArk/view?usp=drive_link
https://drive.google.com/file/d/1WUp846dgWXYhu4oJfhHxiU6YL_7N6s4W/view?usp=drive_link
https://drive.google.com/file/d/1HRZNAIoAQw_uYiPwnBvtBioQoqiqoXdA/view?usp=drive_link
https://drive.google.com/file/d/1hedGq-QDMnIn8GlXXBC3GiEJ_Y-LTxyt/view?usp=drive_link

95
lerobot/common/datasets/push_dataset_to_hub/_download_raw.py
View File

@ -10,6 +10,8 @@ from pathlib import Path
import tqdm import tqdm
ALOHA_RAW_URLS_DIR = "lerobot/common/datasets/push_dataset_to_hub/_aloha_raw_urls"
def download_raw(raw_dir, dataset_id): def download_raw(raw_dir, dataset_id):
if "pusht" in dataset_id: if "pusht" in dataset_id:
@ -87,66 +89,36 @@ def download_xarm(raw_dir: Path):
def download_aloha(raw_dir: Path, dataset_id: str): def download_aloha(raw_dir: Path, dataset_id: str):
# TODO(rcadene): remove gdown and use hugging face download instead
import gdown import gdown
logging.warning( subset_id = dataset_id.replace("aloha_", "")
"Aloha download is broken and requires a custom version of gdown which is not limited on number of files" urls_path = Path(ALOHA_RAW_URLS_DIR) / f"{subset_id}.txt"
) assert urls_path.exists(), f"{subset_id}.txt not found in '{ALOHA_RAW_URLS_DIR}' directory."
folder_urls = { with open(urls_path) as f:
"aloha_sim_insertion_human": "https://drive.google.com/drive/folders/1RgyD0JgTX30H4IM5XZn8I3zSV_mr8pyF", # strip lines and ignore empty lines
"aloha_sim_insertion_scripted": "https://drive.google.com/drive/folders/1TsojQQSXtHEoGnqgJ3gmpPQR2DPLtS2N", urls = [url.strip() for url in f if url.strip()]
"aloha_sim_transfer_cube_human": "https://drive.google.com/drive/folders/1sc-E4QYW7A0o23m1u2VWNGVq5smAsfCo",
"aloha_sim_transfer_cube_scripted": "https://drive.google.com/drive/folders/1aRyoOhQwxhyt1J8XgEig4s6kzaw__LXj",
}
ep48_urls = { # sanity check
"aloha_sim_insertion_human": "https://drive.google.com/file/d/18Cudl6nikDtgRolea7je8iF_gGKzynOP/view?usp=drive_link", for url in urls:
"aloha_sim_insertion_scripted": "https://drive.google.com/file/d/1wfMSZ24oOh5KR_0aaP3Cnu_c4ZCveduB/view?usp=drive_link", assert (
"aloha_sim_transfer_cube_human": "https://drive.google.com/file/d/18smMymtr8tIxaNUQ61gW6dG50pt3MvGq/view?usp=drive_link", "drive.google.com/drive/folders" in url or "drive.google.com/file" in url
"aloha_sim_transfer_cube_scripted": "https://drive.google.com/file/d/1pnGIOd-E4-rhz2P3VxpknMKRZCoKt6eI/view?usp=drive_link", ), f"Wrong url provided '{url}' in file '{urls_path}'."
}
ep49_urls = {
"aloha_sim_insertion_human": "https://drive.google.com/file/d/1C1kZYyROzs-PrLc0SkDgUgMi4-L3lauE/view?usp=drive_link",
"aloha_sim_insertion_scripted": "https://drive.google.com/file/d/17EuCUWS6uCCr6yyNzpXdcdE-_TTNCKtf/view?usp=drive_link",
"aloha_sim_transfer_cube_human": "https://drive.google.com/file/d/1Nk7l53d9sJoGDBKAOnNrExX5nLacATc6/view?usp=drive_link",
"aloha_sim_transfer_cube_scripted": "https://drive.google.com/file/d/1GKReZHrXU73NMiC5zKCq_UtqPVtYq8eo/view?usp=drive_link",
}
num_episodes = { # noqa: F841 # we keep this for reference
"aloha_sim_insertion_human": 50,
"aloha_sim_insertion_scripted": 50,
"aloha_sim_transfer_cube_human": 50,
"aloha_sim_transfer_cube_scripted": 50,
}
episode_len = { # noqa: F841 # we keep this for reference
"aloha_sim_insertion_human": 500,
"aloha_sim_insertion_scripted": 400,
"aloha_sim_transfer_cube_human": 400,
"aloha_sim_transfer_cube_scripted": 400,
}
cameras = { # noqa: F841 # we keep this for reference
"aloha_sim_insertion_human": ["top"],
"aloha_sim_insertion_scripted": ["top"],
"aloha_sim_transfer_cube_human": ["top"],
"aloha_sim_transfer_cube_scripted": ["top"],
}
assert dataset_id in folder_urls
assert dataset_id in ep48_urls
assert dataset_id in ep49_urls
raw_dir = Path(raw_dir) raw_dir = Path(raw_dir)
raw_dir.mkdir(parents=True, exist_ok=True) raw_dir.mkdir(parents=True, exist_ok=True)
gdown.download_folder(folder_urls[dataset_id], output=str(raw_dir)) logging.info(f"Start downloading from google drive for {dataset_id}")
for url in urls:
if "drive.google.com/drive/folders" in url:
# when a folder url is given, download up to 50 files from the folder
gdown.download_folder(url, output=str(raw_dir), remaining_ok=True)
# because of the 50 files limit per directory, two files episode 48 and 49 were missing elif "drive.google.com/file" in url:
gdown.download(ep48_urls[dataset_id], output=str(raw_dir / "episode_48.hdf5"), fuzzy=True) # because of the 50 files limit per folder, we download the remaining files (file by file)
gdown.download(ep49_urls[dataset_id], output=str(raw_dir / "episode_49.hdf5"), fuzzy=True) gdown.download(url, output=str(raw_dir), fuzzy=True)
logging.info(f"End downloading from google drive for {dataset_id}")
def download_umi(raw_dir: Path): def download_umi(raw_dir: Path):
@ -166,10 +138,31 @@ if __name__ == "__main__":
"xarm_lift_medium_replay", "xarm_lift_medium_replay",
"xarm_push_medium", "xarm_push_medium",
"xarm_push_medium_replay", "xarm_push_medium_replay",
"aloha_mobile_cabinet",
"aloha_mobile_chair",
"aloha_mobile_elevator",
"aloha_mobile_shrimp",
"aloha_mobile_wash_pan",
"aloha_mobile_wipe_wine",
"aloha_sim_insertion_human", "aloha_sim_insertion_human",
"aloha_sim_insertion_scripted", "aloha_sim_insertion_scripted",
"aloha_sim_transfer_cube_human", "aloha_sim_transfer_cube_human",
"aloha_sim_transfer_cube_scripted", "aloha_sim_transfer_cube_scripted",
"aloha_static_battery",
"aloha_static_candy",
"aloha_static_coffee",
"aloha_static_coffee_new",
"aloha_static_cups_open",
"aloha_static_fork_pick_up",
"aloha_static_pingpong_test",
"aloha_static_pro_pencil",
"aloha_static_screw_driver",
"aloha_static_tape",
"aloha_static_thread_velcro",
"aloha_static_towel",
"aloha_static_vinh_cup",
"aloha_static_vinh_cup_left",
"aloha_static_ziploc_slide",
"umi_cup_in_the_wild", "umi_cup_in_the_wild",
] ]
for dataset_id in dataset_ids: for dataset_id in dataset_ids:

81
lerobot/common/datasets/push_dataset_to_hub/aloha_hdf5_format.py
View File

@ -7,6 +7,7 @@ import shutil
from pathlib import Path from pathlib import Path
import h5py import h5py
import numpy as np
import torch import torch
import tqdm import tqdm
from datasets import Dataset, Features, Image, Sequence, Value from datasets import Dataset, Features, Image, Sequence, Value
@ -19,41 +20,52 @@ from lerobot.common.datasets.utils import (
from lerobot.common.datasets.video_utils import VideoFrame, encode_video_frames from lerobot.common.datasets.video_utils import VideoFrame, encode_video_frames
def get_cameras(hdf5_data):
# ignore depth channel, not currently handled
# TODO(rcadene): add depth
rgb_cameras = [key for key in hdf5_data["/observations/images"].keys() if "depth" not in key] # noqa: SIM118
return rgb_cameras
def check_format(raw_dir) -> bool: def check_format(raw_dir) -> bool:
cameras = ["top"] # only frames from simulation are uncompressed
compressed_images = "sim" not in raw_dir.name
hdf5_files: list[Path] = list(raw_dir.glob("episode_*.hdf5")) hdf5_paths = list(raw_dir.glob("episode_*.hdf5"))
assert len(hdf5_files) != 0 assert len(hdf5_paths) != 0
hdf5_files = sorted(hdf5_files, key=lambda x: int(re.search(r"episode_(\d+).hdf5", x.name).group(1))) for hdf5_path in hdf5_paths:
with h5py.File(hdf5_path, "r") as data:
assert "/action" in data
assert "/observations/qpos" in data
# Check if the sequence is consecutive eg episode_0, episode_1, episode_2, etc. assert data["/action"].ndim == 2
previous_number = None assert data["/observations/qpos"].ndim == 2
for file in hdf5_files:
current_number = int(re.search(r"episode_(\d+).hdf5", file.name).group(1))
if previous_number is not None:
assert current_number - previous_number == 1
previous_number = current_number
for file in hdf5_files: num_frames = data["/action"].shape[0]
with h5py.File(file, "r") as file: assert num_frames == data["/observations/qpos"].shape[0]
# Check for the expected datasets within the HDF5 file
required_datasets = ["/action", "/observations/qpos"]
# Add camera-specific image datasets to the required datasets
camera_datasets = [f"/observations/images/{cam}" for cam in cameras]
required_datasets.extend(camera_datasets)
assert all(dataset in file for dataset in required_datasets) for camera in get_cameras(data):
assert num_frames == data[f"/observations/images/{camera}"].shape[0]
if compressed_images:
assert data[f"/observations/images/{camera}"].ndim == 2
else:
assert data[f"/observations/images/{camera}"].ndim == 4
b, h, w, c = data[f"/observations/images/{camera}"].shape
assert c < h and c < w, f"Expect (h,w,c) image format but ({h=},{w=},{c=}) provided."
def load_from_raw(raw_dir, out_dir, fps, video, debug): def load_from_raw(raw_dir, out_dir, fps, video, debug):
# only frames from simulation are uncompressed
compressed_images = "sim" not in raw_dir.name
hdf5_files = list(raw_dir.glob("*.hdf5")) hdf5_files = list(raw_dir.glob("*.hdf5"))
hdf5_files = sorted(hdf5_files, key=lambda x: int(re.search(r"episode_(\d+)", x.name).group(1)))
ep_dicts = [] ep_dicts = []
episode_data_index = {"from": [], "to": []} episode_data_index = {"from": [], "to": []}
id_from = 0 id_from = 0
for ep_path in tqdm.tqdm(hdf5_files): for ep_path in tqdm.tqdm(hdf5_files, total=len(hdf5_files)):
with h5py.File(ep_path, "r") as ep: with h5py.File(ep_path, "r") as ep:
ep_idx = int(re.search(r"episode_(\d+)", ep_path.name).group(1)) ep_idx = int(re.search(r"episode_(\d+)", ep_path.name).group(1))
num_frames = ep["/action"].shape[0] num_frames = ep["/action"].shape[0]
@ -67,10 +79,22 @@ def load_from_raw(raw_dir, out_dir, fps, video, debug):
ep_dict = {} ep_dict = {}
cameras = list(ep["/observations/images"].keys()) for camera in get_cameras(ep):
for cam in cameras: img_key = f"observation.images.{camera}"
img_key = f"observation.images.{cam}"
imgs_array = ep[f"/observations/images/{cam}"][:] # b h w c if compressed_images:
import cv2
# load one compressed image after the other in RAM and uncompress
imgs_array = []
for data in ep[f"/observations/images/{camera}"]:
imgs_array.append(cv2.imdecode(data, 1))
imgs_array = np.array(imgs_array)
else:
# load all images in RAM
imgs_array = ep[f"/observations/images/{camera}"][:]
if video: if video:
# save png images in temporary directory # save png images in temporary directory
tmp_imgs_dir = out_dir / "tmp_images" tmp_imgs_dir = out_dir / "tmp_images"
@ -97,9 +121,7 @@ def load_from_raw(raw_dir, out_dir, fps, video, debug):
ep_dict["frame_index"] = torch.arange(0, num_frames, 1) ep_dict["frame_index"] = torch.arange(0, num_frames, 1)
ep_dict["timestamp"] = torch.arange(0, num_frames, 1) / fps ep_dict["timestamp"] = torch.arange(0, num_frames, 1) / fps
ep_dict["next.done"] = done ep_dict["next.done"] = done
# TODO(rcadene): compute reward and success # TODO(rcadene): add reward and success by computing them in sim
# ep_dict[""next.reward"] = reward
# ep_dict[""next.success"] = success
assert isinstance(ep_idx, int) assert isinstance(ep_idx, int)
ep_dicts.append(ep_dict) ep_dicts.append(ep_dict)
@ -138,9 +160,6 @@ def to_hf_dataset(data_dict, video) -> Dataset:
features["timestamp"] = Value(dtype="float32", id=None) features["timestamp"] = Value(dtype="float32", id=None)
features["next.done"] = Value(dtype="bool", id=None) features["next.done"] = Value(dtype="bool", id=None)
features["index"] = Value(dtype="int64", id=None) features["index"] = Value(dtype="int64", id=None)
# TODO(rcadene): add reward and success
# features["next.reward"] = Value(dtype="float32", id=None)
# features["next.success"] = Value(dtype="bool", id=None)
hf_dataset = Dataset.from_dict(data_dict, features=Features(features)) hf_dataset = Dataset.from_dict(data_dict, features=Features(features))
hf_dataset.set_transform(hf_transform_to_torch) hf_dataset.set_transform(hf_transform_to_torch)

1
tests/test_available.py
View File

@ -43,5 +43,6 @@ def test_print():
print(lerobot.available_tasks_per_env) print(lerobot.available_tasks_per_env)
print(lerobot.available_datasets) print(lerobot.available_datasets)
print(lerobot.available_datasets_per_env) print(lerobot.available_datasets_per_env)
print(lerobot.available_real_world_datasets)
print(lerobot.available_policies) print(lerobot.available_policies)
print(lerobot.available_policies_per_env) print(lerobot.available_policies_per_env)