| # 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. | |
| # TODO: Address all TODOs and remove all explanatory comments | |
| """TODO: Add a description here.""" | |
| import os.path as osp | |
| import datasets | |
| from .refer import REFER | |
| # TODO: Add BibTeX citation | |
| # Find for instance the citation on arxiv or on the dataset repo/website | |
| _CITATION = """\ | |
| @InProceedings{huggingface:dataset, | |
| title = {A great new dataset}, | |
| author={huggingface, Inc. | |
| }, | |
| year={2020} | |
| } | |
| """ | |
| # TODO: Add description of the dataset here | |
| # You can copy an official description | |
| _DESCRIPTION = """\ | |
| This RefCOCO dataset is designed to load refcoco, refcoco+, and refcocog. | |
| """ | |
| # TODO: Add a link to an official homepage for the dataset here | |
| _HOMEPAGE = "" | |
| # TODO: Add the licence for the dataset here if you can find it | |
| _LICENSE = "" | |
| # TODO: Add link to the official dataset URLs here | |
| # The HuggingFace Datasets library doesn't host the datasets but only points | |
| # to the original files. | |
| # This can be an arbitrary nested dict/list of URLs | |
| # (see below in `_split_generators` method) | |
| _URLS = {} | |
| VALID_SPLIT_NAMES = ("train", "val", "testA", "testB") | |
| class ReferitBuilderConfig(datasets.BuilderConfig): | |
| def __init__(self, name: str, split_by: str, **kwargs): | |
| super().__init__(name, **kwargs) | |
| self.split_by = split_by | |
| # TODO: Name of the dataset usually matches the script name with CamelCase | |
| # instead of snake_case | |
| class ReferitDataset(datasets.GeneratorBasedBuilder): | |
| """TODO: Short description of my dataset.""" | |
| VERSION = datasets.Version("0.0.1") | |
| # This is an example of a dataset with multiple configurations. | |
| # If you don't want/need to define several sub-sets in your dataset, | |
| # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes. | |
| # If you need to make complex sub-parts in the datasets with configurable | |
| # options | |
| # You can create your own builder configuration class to store attribute, | |
| # inheriting from datasets.BuilderConfig | |
| BUILDER_CONFIG_CLASS = ReferitBuilderConfig | |
| # You will be able to load one or the other configurations | |
| # in the following list with | |
| # data = datasets.load_dataset('my_dataset', 'first_domain') | |
| # data = datasets.load_dataset('my_dataset', 'second_domain') | |
| BUILDER_CONFIGS = [ | |
| # refcoco | |
| ReferitBuilderConfig( | |
| name="refcoco", split_by="unc", | |
| version=VERSION, description="refcoco."), | |
| # refcoco+ | |
| ReferitBuilderConfig( | |
| name="refcoco+", split_by="unc", | |
| version=VERSION, description="refcoco+"), | |
| # refcocog | |
| ReferitBuilderConfig( | |
| name="refcocog", split_by="umd", | |
| version=VERSION, description="refcocog"), | |
| ] | |
| # It's not mandatory to have a default configuration. | |
| # Just use one if it make sense. | |
| DEFAULT_CONFIG_NAME = "refcoco" | |
| def _info(self): | |
| self.config: ReferitBuilderConfig | |
| features = datasets.Features( | |
| { | |
| "ref_id": datasets.Value("int32"), | |
| "img_id": datasets.Value("int32"), | |
| "ann_id": datasets.Value("int32"), | |
| "file_name": datasets.Value("string"), | |
| "image_path": datasets.Value("string"), | |
| "height": datasets.Value("int32"), | |
| "width": datasets.Value("int32"), | |
| "coco_url": datasets.Value("string"), | |
| "sentences": [datasets.Value("string")], | |
| "segmentation": [[[datasets.Value("float")]]], | |
| "bbox": [[datasets.Value("float")]], | |
| "area": datasets.Value("float"), | |
| "iscrowd": datasets.Value("int32"), | |
| "category_id": datasets.Value("int32"), | |
| } | |
| ) | |
| return datasets.DatasetInfo( | |
| # This is the description that will appear on the datasets page. | |
| description=_DESCRIPTION, | |
| # This defines the different columns of the dataset and their types | |
| features=features, | |
| # If there's a common (input, target) tuple from the features, | |
| # uncomment supervised_keys line below and specify them. | |
| # They'll be used if as_supervised=True in builder.as_dataset. | |
| # supervised_keys=("sentence", "label"), | |
| # Homepage of the dataset for documentation | |
| homepage=_HOMEPAGE, | |
| # License for the dataset if available | |
| license=_LICENSE, | |
| # Citation for the dataset | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| # TODO: This method is tasked with downloading/extracting the data and | |
| # defining the splits depending on the configuration | |
| # If several configurations are possible (listed in BUILDER_CONFIGS), | |
| # the configuration selected by the user is in self.config.name | |
| # dl_manager is a datasets.download.DownloadManager that can be used | |
| # to download and extract URLS. It can accept any type | |
| # or nested list/dict and will give back the same structure with | |
| # the url replaced with path to local files. | |
| # By default the archives will be extracted and a path to a cached | |
| # folder where they are extracted is returned instead of the archive | |
| # urls = _URLS[self.config.name] | |
| # data_dir = dl_manager.download_and_extract(urls) | |
| splits = [] | |
| split_names = ("train", "val", "test") | |
| if self.config.name in ("refcoco", "refcoco+"): | |
| split_names += ("testA", "testB") | |
| for split in split_names: | |
| splits.append(datasets.SplitGenerator( | |
| name=datasets.NamedSplit(split), | |
| gen_kwargs={ | |
| "split": split, | |
| }, | |
| )) | |
| return splits | |
| # method parameters are unpacked from `gen_kwargs` as given in | |
| # `_split_generators` | |
| def _generate_examples(self, split: str): | |
| # TODO: This method handles input defined in _split_generators to | |
| # yield (key, example) tuples from the dataset. | |
| # The `key` is for legacy reasons (tfds) and is not important | |
| # in itself, but must be unique for each example. | |
| refer = REFER(data_root=self.config.data_dir, | |
| dataset=self.config.name, | |
| splitBy=self.config.split_by) | |
| ref_ids = refer.getRefIds(split=split) | |
| for ref_id in ref_ids: | |
| ref = refer.loadRefs(ref_id)[0] | |
| ann_id = ref['ann_id'] | |
| ann = refer.loadAnns(ann_id)[0] | |
| img_id = ann['image_id'] | |
| img = refer.loadImgs(img_id)[0] | |
| file_name = img['file_name'] | |
| image_path = osp.join( | |
| self.config.data_dir, "images", "train2014", file_name) | |
| descriptions = [r['raw'] for r in ref['sentences']] | |
| yield ref_id, { | |
| "ref_id": ref_id, | |
| "img_id": img_id, | |
| "ann_id": ann_id, | |
| "file_name": file_name, | |
| "image_path": image_path, | |
| "height": img['height'], | |
| "width": img['width'], | |
| "coco_url": img['coco_url'], | |
| "sentences": descriptions, | |
| "segmentation": [ann['segmentation']], | |
| "bbox": [ann['bbox']], | |
| "area": ann['area'], | |
| "iscrowd": ann['iscrowd'], | |
| "category_id": ann['category_id'], | |
| } | |