yonatanbitton
commited on
Commit
•
4275770
1
Parent(s):
006d305
Create flickr30k.py
Browse files- flickr30k.py +75 -0
flickr30k.py
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# coding=utf-8
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# Copyright 2022 the HuggingFace Datasets Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import pandas as pd
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import datasets
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import json
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from huggingface_hub import hf_hub_url
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_INPUT_CSV = "flickr_annotations_30k.csv"
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_INPUT_IMAGES = "flickr30k-images"
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_REPO_ID = "nlphuji/flickr30k"
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_JSON_KEYS = ['imgids', 'raw', 'sentids']
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class Dataset(datasets.GeneratorBasedBuilder):
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VERSION = datasets.Version("1.1.0")
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(name="TEST", version=VERSION, description="test"),
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]
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def _info(self):
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return datasets.DatasetInfo(
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features=datasets.Features(
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{
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"image": datasets.Image(),
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"caption": [datasets.Value('string')],
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"sentids": [datasets.Value("string")],
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"imgid": datasets.Value("string"),
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"split": datasets.Value("string"),
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"filename": datasets.Value("string"),
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'sentids': [datasets.Value('int64')],
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'imgid': [datasets.Value('int64')],
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'tokens': [[datasets.Value('string')]],
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'sentid': [datasets.Value('int64')],
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}
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),
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task_templates=[],
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)
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def _split_generators(self, dl_manager):
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"""Returns SplitGenerators."""
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repo_id = _REPO_ID
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data_dir = dl_manager.download_and_extract({
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"examples_csv": hf_hub_url(repo_id=repo_id, repo_type='dataset', filename=_INPUT_CSV),
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"images_dir": hf_hub_url(repo_id=repo_id, repo_type='dataset', filename=f"{_INPUT_IMAGES}.zip")
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})
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return [datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs=data_dir)]
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def _generate_examples(self, examples_csv, images_dir):
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"""Yields examples."""
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df = pd.read_csv(examples_csv)
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for c in _JSON_KEYS:
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df[c] = df[c].apply(json.loads)
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for r_idx, r in df.iterrows():
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r_dict = r.to_dict()
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image_path = os.path.join(images_dir, _INPUT_IMAGES, r_dict['filename'])
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r_dict['image'] = image_path
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r_dict['caption'] = r_dict.pop('raw')
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yield r_idx, r_dict
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