Datasets:

bealam111
/

EndoX_Dataset

Tags:

endoscopy

synthetic dataset

physics-based rendering

webdataset

Libraries:

WebDataset

Dataset card Data Studio Files Files and versions

xet

Community

Dataset Viewer

The dataset viewer is not available for this dataset.

The JWT signature verification failed. Check the signing key and the algorithm.

Error code:   JWTInvalidSignature
Exception:    InvalidSignatureError
Message:      Signature verification failed
Traceback:    Traceback (most recent call last):
                File "/src/libs/libapi/src/libapi/jwt_token.py", line 286, in validate_jwt
                  decoded = jwt.decode(
                      jwt=token,
                  ...<2 lines>...
                      options=options,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 368, in decode
                  decoded = self.decode_complete(
                      jwt,
                  ...<8 lines>...
                      leeway=leeway,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 265, in decode_complete
                  decoded = self._jws.decode_complete(
                      jwt,
                  ...<3 lines>...
                      detached_payload=detached_payload,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 270, in decode_complete
                  self._verify_signature(
                  ~~~~~~~~~~~~~~~~~~~~~~^
                      signing_input,
                      ^^^^^^^^^^^^^^
                  ...<4 lines>...
                      options=merged_options,
                      ^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 417, in _verify_signature
                  raise InvalidSignatureError("Signature verification failed")
              jwt.exceptions.InvalidSignatureError: Signature verification failed

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EndoX Dataset

Folder Structure

Each sequence is stored as one .tar WebDataset shard.

sample_dataset/
  colon/
    sequence_1/
      sample_dataset-colon-sequence_1.tar
  small_intestines/
    sequence_1/
      sample_dataset-small_intestines-sequence_1.tar
    sequence_2/
      sample_dataset-small_intestines-sequence_2.tar
dataset/
  colon/
    sequence_1/
      dataset-colon-sequence_1.tar
    sequence_2/
      dataset-colon-sequence_2.tar
    sequence_3/
      dataset-colon-sequence_3.tar
    sequence_4/
      dataset-colon-sequence_4.tar
    sequence_5/
      dataset-colon-sequence_5.tar

Inside each shard, every frame is one WebDataset sample:

0000.depth.png
0000.normal_camera.png
0000.normal_world.png
0000.occlusion.png
0000.optical_flow.png
0000.rgb.png

Sequence metadata is embedded in each shard:

__metadata__/camera_pose/camera_pose.txt
__metadata__/coverage_map/coverage_vertices.npz
__metadata__/coverage_map/coverage_vertices_per_frame.npz

How To Load The Dataset

Install dependencies:

pip install webdataset pillow

Stream one sequence directly from Hugging Face:

import webdataset as wds

url = (
    "https://huggingface.co/datasets/bealam111/EndoX_Dataset/resolve/"
    "main/dataset/colon/sequence_1/dataset-colon-sequence_1.tar"
)

dataset = (
    wds.WebDataset(url)
    .select(lambda sample: "rgb.png" in sample)
    .decode("pil")
)

for sample in dataset:
    frame_id = sample["__key__"]
    rgb = sample["rgb.png"]
    depth = sample["depth.png"]
    normal_camera = sample["normal_camera.png"]
    normal_world = sample["normal_world.png"]
    occlusion = sample["occlusion.png"]
    optical_flow = sample["optical_flow.png"]
    break

Download one sequence with the Hugging Face CLI:

hf download bealam111/EndoX_Dataset \
  --type dataset \
  --include "dataset/colon/sequence_1/dataset-colon-sequence_1.tar" \
  --local-dir ./EndoX_Dataset

Optional: Extract To Modality Folders

The .tar files use WebDataset names such as 0000.rgb.png so each frame can be streamed as one multi-modal sample. After downloading, users who prefer a traditional folder structure can reorganize one extracted shard into modality folders:

from pathlib import Path
import shutil

sequence_dir = Path("./EndoX_Dataset/dataset/colon/sequence_1")
tar_path = sequence_dir / "dataset-colon-sequence_1.tar"
extract_dir = sequence_dir / "extracted"

shutil.unpack_archive(tar_path, extract_dir)

for path in list(extract_dir.glob("*.png")):
    frame_id, modality, ext = path.name.split(".", 2)
    target = extract_dir / modality / f"{frame_id}.{ext}"
    target.parent.mkdir(parents=True, exist_ok=True)
    path.rename(target)

After running the script, the extracted sequence has this structure:

extracted/
  rgb/
    0000.png
    0001.png
  depth/
    0000.png
    0001.png
  normal_camera/
    0000.png
  normal_world/
    0000.png
  occlusion/
    0000.png
  optical_flow/
    0000.png
  __metadata__/
    camera_pose/camera_pose.txt
    coverage_map/coverage_vertices.npz
    coverage_map/coverage_vertices_per_frame.npz

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Total file size:

94.6 GB