Hugging Face's logo

Datasets:
lst627
/
COCO-Facet

Tasks:
Text-to-Image
Languages:
English
Size:
10K<n<100K
Tags:
retrieval
multimodal
benchmark
coco
visual7w
visdial
License:
Dataset card Files
xet
 Community
Dataset Viewer
Duplicate
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 COCO-Facet@7dfc28f1c103421d5b3818da326b9369a6ed8385
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 COCO-Facet@7dfc28f1c103421d5b3818da326b9369a6ed8385

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.

COCO-Facet

COCO-Facet is a benchmark for attribute-focused text-to-image retrieval ("Facets" of images). Annotations are derived from MSCOCO 2017, COCO-Stuff, Visual7W, and VisDial.

Code: https://github.com/lst627/COCO-Facet

Contents

Path Description
benchmark/*.json 11 retrieval subsets (queries and candidate image references)
val2017.zip MSCOCO val2017 images (5,000 files, ~788 MB)
VisualDialog_val2018.zip VisDial val2018 images (2,064 files, ~318 MB)
visual7w_images.zip Visual7W images (47,300 files, ~1.8 GB)

Subsets in benchmark/

  • Original_COCO_retrieval.json
  • COCO_object_retrieval.json
  • COCO_animal_retrieval.json
  • COCO_gesture_retrieval.json
  • COCOStuff_material_retrieval.json
  • Visual7W_time_retrieval.json
  • Visual7W_scene_retrieval.json
  • Visual7W_people_num_retrieval.json
  • mix_weather_retrieval.json
  • Place365_retrieval.json
  • SUN397_retrieval.json

Download and layout 

huggingface-cli download lst627/COCO-Facet --repo-type dataset --local-dir COCO-Facet
cd COCO-Facet

unzip -q val2017.zip
unzip -q VisualDialog_val2018.zip
mkdir -p visual7w && unzip -q visual7w_images.zip -d visual7w

Resulting layout (use this directory as $DATASET_PATH in the evaluation scripts):

COCO-Facet/
├── benchmark/
│   ├── COCO_object_retrieval.json
│   └── ...
├── val2017/
├── VisualDialog_val2018/
└── visual7w/
    └── images/

Acknowledgments

This benchmark builds on MSCOCO, COCO-Stuff, Visual7W, and VisDial. Please respect the licenses of the underlying image sources.
Downloads last month
58
Total file size:
3.21 GB