Datasets:
Sub-tasks:
image-captioning
Languages:
English
Multilinguality:
monolingual
Size Categories:
100K<n<1M
Language Creators:
found
Annotations Creators:
found
Source Datasets:
original
License:
# coding=utf-8 | |
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. | |
# | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, | |
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
# See the License for the specific language governing permissions and | |
# limitations under the License. | |
"""Visual Genome dataset.""" | |
import json | |
import os | |
import re | |
from collections import defaultdict | |
from typing import Any, Callable, Dict, Optional | |
from urllib.parse import urlparse | |
import datasets | |
logger = datasets.logging.get_logger(__name__) | |
_CITATION = """\ | |
@article{Krishna2016VisualGC, | |
title={Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations}, | |
author={Ranjay Krishna and Yuke Zhu and Oliver Groth and Justin Johnson and Kenji Hata and Joshua Kravitz and Stephanie Chen and Yannis Kalantidis and Li-Jia Li and David A. Shamma and Michael S. Bernstein and Li Fei-Fei}, | |
journal={International Journal of Computer Vision}, | |
year={2017}, | |
volume={123}, | |
pages={32-73}, | |
url={https://doi.org/10.1007/s11263-016-0981-7}, | |
doi={10.1007/s11263-016-0981-7} | |
} | |
""" | |
_DESCRIPTION = """\ | |
Visual Genome enable to model objects and relationships between objects. | |
They collect dense annotations of objects, attributes, and relationships within each image. | |
Specifically, the dataset contains over 108K images where each image has an average of 35 objects, 26 attributes, and 21 pairwise relationships between objects. | |
""" | |
_HOMEPAGE = "https://homes.cs.washington.edu/~ranjay/visualgenome/" | |
_LICENSE = "Creative Commons Attribution 4.0 International License" | |
_BASE_IMAGE_URLS = { | |
"https://cs.stanford.edu/people/rak248/VG_100K_2/images.zip": "VG_100K", | |
"https://cs.stanford.edu/people/rak248/VG_100K_2/images2.zip": "VG_100K_2", | |
} | |
_LATEST_VERSIONS = { | |
"region_descriptions": "1.2.0", | |
"objects": "1.4.0", | |
"attributes": "1.2.0", | |
"relationships": "1.4.0", | |
"question_answers": "1.2.0", | |
"image_metadata": "1.2.0", | |
} | |
# ---- Features ---- | |
_BASE_IMAGE_METADATA_FEATURES = { | |
"image_id": datasets.Value("int32"), | |
"url": datasets.Value("string"), | |
"width": datasets.Value("int32"), | |
"height": datasets.Value("int32"), | |
"coco_id": datasets.Value("int64"), | |
"flickr_id": datasets.Value("int64"), | |
} | |
_BASE_SYNTET_FEATURES = { | |
"synset_name": datasets.Value("string"), | |
"entity_name": datasets.Value("string"), | |
"entity_idx_start": datasets.Value("int32"), | |
"entity_idx_end": datasets.Value("int32"), | |
} | |
_BASE_OBJECT_FEATURES = { | |
"object_id": datasets.Value("int32"), | |
"x": datasets.Value("int32"), | |
"y": datasets.Value("int32"), | |
"w": datasets.Value("int32"), | |
"h": datasets.Value("int32"), | |
"names": [datasets.Value("string")], | |
"synsets": [datasets.Value("string")], | |
} | |
_BASE_QA_OBJECT_FEATURES = { | |
"object_id": datasets.Value("int32"), | |
"x": datasets.Value("int32"), | |
"y": datasets.Value("int32"), | |
"w": datasets.Value("int32"), | |
"h": datasets.Value("int32"), | |
"names": [datasets.Value("string")], | |
"synsets": [datasets.Value("string")], | |
} | |
_BASE_QA_OBJECT = { | |
"qa_id": datasets.Value("int32"), | |
"image_id": datasets.Value("int32"), | |
"question": datasets.Value("string"), | |
"answer": datasets.Value("string"), | |
"a_objects": [_BASE_QA_OBJECT_FEATURES], | |
"q_objects": [_BASE_QA_OBJECT_FEATURES], | |
} | |
_BASE_REGION_FEATURES = { | |
"region_id": datasets.Value("int32"), | |
"image_id": datasets.Value("int32"), | |
"phrase": datasets.Value("string"), | |
"x": datasets.Value("int32"), | |
"y": datasets.Value("int32"), | |
"width": datasets.Value("int32"), | |
"height": datasets.Value("int32"), | |
} | |
_BASE_RELATIONSHIP_FEATURES = { | |
"relationship_id": datasets.Value("int32"), | |
"predicate": datasets.Value("string"), | |
"synsets": datasets.Value("string"), | |
"subject": _BASE_OBJECT_FEATURES, | |
"object": _BASE_OBJECT_FEATURES, | |
} | |
_NAME_VERSION_TO_ANNOTATION_FEATURES = { | |
"region_descriptions": { | |
"1.2.0": {"regions": [_BASE_REGION_FEATURES]}, | |
"1.0.0": {"regions": [_BASE_REGION_FEATURES]}, | |
}, | |
"objects": { | |
"1.4.0": {"objects": [{**_BASE_OBJECT_FEATURES, "merged_object_ids": [datasets.Value("int32")]}]}, | |
"1.2.0": {"objects": [_BASE_OBJECT_FEATURES]}, | |
"1.0.0": {"objects": [_BASE_OBJECT_FEATURES]}, | |
}, | |
"attributes": { | |
"1.2.0": {"attributes": [{**_BASE_OBJECT_FEATURES, "attributes": [datasets.Value("string")]}]}, | |
"1.0.0": {"attributes": [{**_BASE_OBJECT_FEATURES, "attributes": [datasets.Value("string")]}]}, | |
}, | |
"relationships": { | |
"1.4.0": { | |
"relationships": [ | |
{ | |
**_BASE_RELATIONSHIP_FEATURES, | |
"subject": {**_BASE_OBJECT_FEATURES, "merged_object_ids": [datasets.Value("int32")]}, | |
"object": {**_BASE_OBJECT_FEATURES, "merged_object_ids": [datasets.Value("int32")]}, | |
} | |
] | |
}, | |
"1.2.0": {"relationships": [_BASE_RELATIONSHIP_FEATURES]}, | |
"1.0.0": {"relationships": [_BASE_RELATIONSHIP_FEATURES]}, | |
}, | |
"question_answers": {"1.2.0": {"qas": [_BASE_QA_OBJECT]}, "1.0.0": {"qas": [_BASE_QA_OBJECT]}}, | |
} | |
# ----- Helpers ----- | |
def _get_decompressed_filename_from_url(url: str) -> str: | |
parsed_url = urlparse(url) | |
compressed_filename = os.path.basename(parsed_url.path) | |
# Remove `.zip` suffix | |
assert compressed_filename.endswith(".zip") | |
uncompressed_filename = compressed_filename[:-4] | |
# Remove version. | |
unversioned_uncompressed_filename = re.sub(r"_v[0-9]+(?:_[0-9]+)?\.json$", ".json", uncompressed_filename) | |
return unversioned_uncompressed_filename | |
def _get_local_image_path(img_url: str, folder_local_paths: Dict[str, str]) -> str: | |
""" | |
Obtain image folder given an image url. | |
For example: | |
Given `https://cs.stanford.edu/people/rak248/VG_100K_2/1.jpg` as an image url, this method returns the local path for that image. | |
""" | |
matches = re.fullmatch(r"^https://cs.stanford.edu/people/rak248/(VG_100K(?:_2)?)/([0-9]+\.jpg)$", img_url) | |
assert matches is not None, f"Got img_url: {img_url}, matched: {matches}" | |
folder, filename = matches.group(1), matches.group(2) | |
return os.path.join(folder_local_paths[folder], filename) | |
# ----- Annotation normalizers ---- | |
_BASE_ANNOTATION_URL = "https://homes.cs.washington.edu/~ranjay/visualgenome/data/dataset" | |
def _normalize_region_description_annotation_(annotation: Dict[str, Any]) -> Dict[str, Any]: | |
"""Normalizes region descriptions annotation in-place""" | |
# Some attributes annotations don't have an attribute field | |
for region in annotation["regions"]: | |
# `id` should be converted to `region_id`: | |
if "id" in region: | |
region["region_id"] = region["id"] | |
del region["id"] | |
# `image` should be converted to `image_id` | |
if "image" in region: | |
region["image_id"] = region["image"] | |
del region["image"] | |
return annotation | |
def _normalize_object_annotation_(annotation: Dict[str, Any]) -> Dict[str, Any]: | |
"""Normalizes object annotation in-place""" | |
# Some attributes annotations don't have an attribute field | |
for object_ in annotation["objects"]: | |
# `id` should be converted to `object_id`: | |
if "id" in object_: | |
object_["object_id"] = object_["id"] | |
del object_["id"] | |
# Some versions of `object` annotations don't have `synsets` field. | |
if "synsets" not in object_: | |
object_["synsets"] = None | |
return annotation | |
def _normalize_attribute_annotation_(annotation: Dict[str, Any]) -> Dict[str, Any]: | |
"""Normalizes attributes annotation in-place""" | |
# Some attributes annotations don't have an attribute field | |
for attribute in annotation["attributes"]: | |
# `id` should be converted to `object_id`: | |
if "id" in attribute: | |
attribute["object_id"] = attribute["id"] | |
del attribute["id"] | |
# `objects_names` should be convered to `names: | |
if "object_names" in attribute: | |
attribute["names"] = attribute["object_names"] | |
del attribute["object_names"] | |
# Some versions of `attribute` annotations don't have `synsets` field. | |
if "synsets" not in attribute: | |
attribute["synsets"] = None | |
# Some versions of `attribute` annotations don't have `attributes` field. | |
if "attributes" not in attribute: | |
attribute["attributes"] = None | |
return annotation | |
def _normalize_relationship_annotation_(annotation: Dict[str, Any]) -> Dict[str, Any]: | |
"""Normalizes relationship annotation in-place""" | |
# For some reason relationships objects have a single name instead of a list of names. | |
for relationship in annotation["relationships"]: | |
# `id` should be converted to `object_id`: | |
if "id" in relationship: | |
relationship["relationship_id"] = relationship["id"] | |
del relationship["id"] | |
if "synsets" not in relationship: | |
relationship["synsets"] = None | |
subject = relationship["subject"] | |
object_ = relationship["object"] | |
for obj in [subject, object_]: | |
# `id` should be converted to `object_id`: | |
if "id" in obj: | |
obj["object_id"] = obj["id"] | |
del obj["id"] | |
if "name" in obj: | |
obj["names"] = [obj["name"]] | |
del obj["name"] | |
if "synsets" not in obj: | |
obj["synsets"] = None | |
return annotation | |
def _normalize_image_metadata_(image_metadata: Dict[str, Any]) -> Dict[str, Any]: | |
"""Normalizes image metadata in-place""" | |
if "id" in image_metadata: | |
image_metadata["image_id"] = image_metadata["id"] | |
del image_metadata["id"] | |
return image_metadata | |
_ANNOTATION_NORMALIZER = defaultdict(lambda: lambda x: x) | |
_ANNOTATION_NORMALIZER.update( | |
{ | |
"region_descriptions": _normalize_region_description_annotation_, | |
"objects": _normalize_object_annotation_, | |
"attributes": _normalize_attribute_annotation_, | |
"relationships": _normalize_relationship_annotation_, | |
} | |
) | |
# ---- Visual Genome loading script ---- | |
class VisualGenomeConfig(datasets.BuilderConfig): | |
"""BuilderConfig for Visual Genome.""" | |
def __init__(self, name: str, version: Optional[str] = None, with_image: bool = True, **kwargs): | |
_version = _LATEST_VERSIONS[name] if version is None else version | |
_name = f"{name}_v{_version}" | |
super(VisualGenomeConfig, self).__init__(version=datasets.Version(_version), name=_name, **kwargs) | |
self._name_without_version = name | |
self.annotations_features = _NAME_VERSION_TO_ANNOTATION_FEATURES[self._name_without_version][ | |
self.version.version_str | |
] | |
self.with_image = with_image | |
def annotations_url(self): | |
if self.version == _LATEST_VERSIONS[self._name_without_version]: | |
return f"{_BASE_ANNOTATION_URL}/{self._name_without_version}.json.zip" | |
major, minor = self.version.major, self.version.minor | |
if minor == 0: | |
return f"{_BASE_ANNOTATION_URL}/{self._name_without_version}_v{major}.json.zip" | |
else: | |
return f"{_BASE_ANNOTATION_URL}/{self._name_without_version}_v{major}_{minor}.json.zip" | |
def image_metadata_url(self): | |
if not self.version == _LATEST_VERSIONS["image_metadata"]: | |
logger.warning( | |
f"Latest image metadata version is {_LATEST_VERSIONS['image_metadata']}. Trying to generate a dataset of version: {self.version}. Please double check that image data are unchanged between the two versions." | |
) | |
return f"{_BASE_ANNOTATION_URL}/image_data.json.zip" | |
def features(self): | |
return datasets.Features( | |
{ | |
**({"image": datasets.Image()} if self.with_image else {}), | |
**_BASE_IMAGE_METADATA_FEATURES, | |
**self.annotations_features, | |
} | |
) | |
class VisualGenome(datasets.GeneratorBasedBuilder): | |
"""Visual Genome dataset.""" | |
BUILDER_CONFIG_CLASS = VisualGenomeConfig | |
BUILDER_CONFIGS = [ | |
*[VisualGenomeConfig(name="region_descriptions", version=version) for version in ["1.0.0", "1.2.0"]], | |
*[VisualGenomeConfig(name="question_answers", version=version) for version in ["1.0.0", "1.2.0"]], | |
*[ | |
VisualGenomeConfig(name="objects", version=version) | |
# TODO: add support for 1.4.0 | |
for version in ["1.0.0", "1.2.0"] | |
], | |
*[VisualGenomeConfig(name="attributes", version=version) for version in ["1.0.0", "1.2.0"]], | |
*[ | |
VisualGenomeConfig(name="relationships", version=version) | |
# TODO: add support for 1.4.0 | |
for version in ["1.0.0", "1.2.0"] | |
], | |
] | |
def _info(self): | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=self.config.features, | |
homepage=_HOMEPAGE, | |
license=_LICENSE, | |
citation=_CITATION, | |
version=self.config.version, | |
) | |
def _split_generators(self, dl_manager): | |
# Download image meta datas. | |
image_metadatas_dir = dl_manager.download_and_extract(self.config.image_metadata_url) | |
image_metadatas_file = os.path.join( | |
image_metadatas_dir, _get_decompressed_filename_from_url(self.config.image_metadata_url) | |
) | |
# Download annotations | |
annotations_dir = dl_manager.download_and_extract(self.config.annotations_url) | |
annotations_file = os.path.join( | |
annotations_dir, _get_decompressed_filename_from_url(self.config.annotations_url) | |
) | |
# Optionally download images | |
if self.config.with_image: | |
image_folder_keys = list(_BASE_IMAGE_URLS.keys()) | |
image_dirs = dl_manager.download_and_extract(image_folder_keys) | |
image_folder_local_paths = { | |
_BASE_IMAGE_URLS[key]: os.path.join(dir_, _BASE_IMAGE_URLS[key]) | |
for key, dir_ in zip(image_folder_keys, image_dirs) | |
} | |
else: | |
image_folder_local_paths = None | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
gen_kwargs={ | |
"image_folder_local_paths": image_folder_local_paths, | |
"image_metadatas_file": image_metadatas_file, | |
"annotations_file": annotations_file, | |
"annotation_normalizer_": _ANNOTATION_NORMALIZER[self.config._name_without_version], | |
}, | |
), | |
] | |
def _generate_examples( | |
self, | |
image_folder_local_paths: Optional[Dict[str, str]], | |
image_metadatas_file: str, | |
annotations_file: str, | |
annotation_normalizer_: Callable[[Dict[str, Any]], Dict[str, Any]], | |
): | |
with open(annotations_file, "r", encoding="utf-8") as fi: | |
annotations = json.load(fi) | |
with open(image_metadatas_file, "r", encoding="utf-8") as fi: | |
image_metadatas = json.load(fi) | |
assert len(image_metadatas) == len(annotations) | |
for idx, (image_metadata, annotation) in enumerate(zip(image_metadatas, annotations)): | |
# in-place operation to normalize image_metadata | |
_normalize_image_metadata_(image_metadata) | |
# Normalize image_id across all annotations | |
if "id" in annotation: | |
# annotation["id"] corresponds to image_metadata["image_id"] | |
assert ( | |
image_metadata["image_id"] == annotation["id"] | |
), f"Annotations doesn't match with image metadataset. Got image_metadata['image_id']: {image_metadata['image_id']} and annotations['id']: {annotation['id']}" | |
del annotation["id"] | |
else: | |
assert "image_id" in annotation | |
assert ( | |
image_metadata["image_id"] == annotation["image_id"] | |
), f"Annotations doesn't match with image metadataset. Got image_metadata['image_id']: {image_metadata['image_id']} and annotations['image_id']: {annotation['image_id']}" | |
# Normalize image_id across all annotations | |
if "image_url" in annotation: | |
# annotation["image_url"] corresponds to image_metadata["url"] | |
assert ( | |
image_metadata["url"] == annotation["image_url"] | |
), f"Annotations doesn't match with image metadataset. Got image_metadata['url']: {image_metadata['url']} and annotations['image_url']: {annotation['image_url']}" | |
del annotation["image_url"] | |
elif "url" in annotation: | |
# annotation["url"] corresponds to image_metadata["url"] | |
assert ( | |
image_metadata["url"] == annotation["url"] | |
), f"Annotations doesn't match with image metadataset. Got image_metadata['url']: {image_metadata['url']} and annotations['url']: {annotation['url']}" | |
# in-place operation to normalize annotations | |
annotation_normalizer_(annotation) | |
# optionally add image to the annotation | |
if image_folder_local_paths is not None: | |
filepath = _get_local_image_path(image_metadata["url"], image_folder_local_paths) | |
image_dict = {"image": filepath} | |
else: | |
image_dict = {} | |
yield idx, {**image_dict, **image_metadata, **annotation} | |