Convert dataset to Parquet

README.md

@@ -1,3 +1,32 @@
+---
+dataset_info:
+  config_name: TEST
+  features:
+  - name: image
+    dtype: image
+  - name: caption
+    list: string
+  - name: sentids
+    list: string
+  - name: split
+    dtype: string
+  - name: img_id
+    dtype: string
+  - name: filename
+    dtype: string
+  splits:
+  - name: test
+    num_bytes: 4325959287.86
+    num_examples: 31014
+  download_size: 4305504040
+  dataset_size: 4325959287.86
+configs:
+- config_name: TEST
+  data_files:
+  - split: test
+    path: TEST/test-*
+  default: true
+---
 # Flickr30k
 
 Original paper: [From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions](https://aclanthology.org/Q14-1006)

flickr_annotations_30k.csv → TEST/test-00000-of-00009.parquet

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-size 12896305
+oid sha256:684e8f49c9282a6b79218d4ace88f53e1917e967ff49d8dbbafd8463766e72ed
+size 459231637

flickr30k-images.zip → TEST/test-00001-of-00009.parquet

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-size 4390240817
+oid sha256:ac73948ad3d95b16c5a884e80b23ef10237f6d47b48a6e839eab5048f6ef683c
+size 463201812

TEST/test-00002-of-00009.parquet

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+size 473895143

TEST/test-00003-of-00009.parquet

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TEST/test-00004-of-00009.parquet

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TEST/test-00005-of-00009.parquet

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TEST/test-00006-of-00009.parquet

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+size 517475509

TEST/test-00007-of-00009.parquet

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TEST/test-00008-of-00009.parquet

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+size 466036663

flickr30k.py

@@ -1,71 +0,0 @@
-# coding=utf-8
-# Copyright 2022 the HuggingFace Datasets Authors.
-#
-# 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.
-
-import os
-import pandas as pd 
-import datasets
-import json
-from huggingface_hub import hf_hub_url
-
-_INPUT_CSV = "flickr_annotations_30k.csv"
-_INPUT_IMAGES = "flickr30k-images"
-_REPO_ID = "nlphuji/flickr30k"
-_JSON_KEYS = ['raw', 'sentids']
-
-class Dataset(datasets.GeneratorBasedBuilder):
-    VERSION = datasets.Version("1.1.0")
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="TEST", version=VERSION, description="test"),
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            features=datasets.Features(
-                 {
-                "image": datasets.Image(),
-                "caption": [datasets.Value('string')],
-                "sentids": [datasets.Value("string")],
-                "split": datasets.Value("string"),
-                 "img_id": datasets.Value("string"),
-                "filename": datasets.Value("string"),
-                }
-            ),
-            task_templates=[],
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-
-        repo_id = _REPO_ID
-        data_dir = dl_manager.download_and_extract({
-            "examples_csv": hf_hub_url(repo_id=repo_id, repo_type='dataset', filename=_INPUT_CSV),
-            "images_dir": hf_hub_url(repo_id=repo_id, repo_type='dataset', filename=f"{_INPUT_IMAGES}.zip")
-        })
-
-        return [datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs=data_dir)]
-
-
-    def _generate_examples(self, examples_csv, images_dir):
-        """Yields examples."""
-        df = pd.read_csv(examples_csv)
-        for c in _JSON_KEYS:
-            df[c] = df[c].apply(json.loads)
-
-        for r_idx, r in df.iterrows():
-            r_dict = r.to_dict()
-            image_path = os.path.join(images_dir, _INPUT_IMAGES, r_dict['filename'])
-            r_dict['image'] = image_path
-            r_dict['caption'] = r_dict.pop('raw')
-            yield r_idx, r_dict