Datasets:

KU626
/

PolypScene-250

DOI:

Dataset Viewer

Split (1)

train

The dataset viewer is not available for this split.

Cannot load the dataset split (in streaming mode) to extract the first rows.

Error code:   StreamingRowsError
Exception:    ValueError
Message:      Invalid string class label PolypScene-250@93b35b247a149e4bec227f0e78b01d0497f6581a
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2240, in __iter__
                  example = _apply_feature_types_on_example(
                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2157, in _apply_feature_types_on_example
                  encoded_example = features.encode_example(example)
                                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2152, in encode_example
                  return encode_nested_example(self, example)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1437, in encode_nested_example
                  {k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1460, in encode_nested_example
                  return schema.encode_example(obj) if obj is not None else None
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1143, in encode_example
                  example_data = self.str2int(example_data)
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1080, in str2int
                  output = [self._strval2int(value) for value in values]
                            ^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1101, in _strval2int
                  raise ValueError(f"Invalid string class label {value}")
              ValueError: Invalid string class label PolypScene-250@93b35b247a149e4bec227f0e78b01d0497f6581a

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

PolypScene-250 Dataset

Overview

PolypScene-250 is a multi-view colonoscopic polyp dataset designed for retrieval-based analysis and representation learning.

The dataset contains 250 polyp cases, where each case corresponds to a single lesion. Each polyp is represented by four images captured from different viewpoints.

Among them, 80 polyps are annotated with pathology labels (benign or malignant).

Dataset Structure

PolypScene-250/
├── Data/
│    ├── Polyp001/
│    │   ├── query01.jpg
│    │   ├── query02.jpg
│    │   ├── ref01.jpg
│    │   └── ref02.jpg
│    ├── Polyp002/
│    ├── ...
├── pathology_80.xlsx
└── metadata_reorganized.jsonl

Folder Description

PolypXXX/
- Each folder represents one polyp (one lesion).
- Contains 4 images:
  - query01.jpg, query02.jpg: query views
  - ref01.jpg, ref02.jpg: reference views
pathology_80.xlsx
- Contains pathology labels for 80 polyps.
- Columns:
  - polyp_id: e.g., Polyp001
  - ground_truth: 0 (benign), 1 (malignant)
  - pathology: text label
metadata_reorganized.jsonl
- Structured metadata describing image paths for each polyp.

Data Characteristics

Case-level dataset Each sample corresponds to one polyp, not individual images.
Multi-view representation Each polyp includes four images from different viewpoints.
Partial annotation Only 80 out of 250 polyps have pathology labels.

Usage

Load Images

import os

polyp_dir = "PolypScene-250/Polyp001"

query_imgs = sorted([f for f in os.listdir(polyp_dir) if "query" in f])
ref_imgs = sorted([f for f in os.listdir(polyp_dir) if "ref" in f])

Typical Tasks

Retrieval-based diagnosis
Multi-view representation learning
Cross-view matching
Classification (using the 80 labeled samples)

Notes

Each folder corresponds to one polyp.
Query and reference images belong to the same lesion.
Do not treat images within a folder as independent samples.

Downloads last month: 45

Total file size:

1.05 GB