init

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README.md

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+This dataset includes 2 images: one of the [IAM Handwriting Database](https://fki.tic.heia-fr.ch/databases/iam-handwriting-database) and one of the [SRIOE](https://rrc.cvc.uab.es/?ch=13) dataset.
+
+They are used for testing OCR models that are part of the HuggingFace Transformers library.
+
+More specifically, they are used inside `test_modeling_vision_encoder_decoder_model.py`, for testing the TrOCR models.

fixtures_image_utils.py

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+# coding=utf-8
+# Copyright 2021 The TensorFlow Datasets Authors and 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 textwrap
+import datasets
+_CITATION = """\\n"""
+_DESCRIPTION = """\\n"""
+class FixturesOCRConfig(datasets.BuilderConfig):
+    """BuilderConfig for fixtures OCR"""
+    def __init__(
+        self,
+        data_url,
+        url,
+        task_templates=None,
+        **kwargs,
+    ):
+        super(FixturesOCRConfig, self).__init__(
+            version=datasets.Version("1.9.0", ""), **kwargs
+        )
+        self.data_url = data_url
+        self.url = url
+        self.task_templates = task_templates
+class FixturesOCR(datasets.GeneratorBasedBuilder):
+    """Fixtures for OCR models. Includes 2 images."""
+    BUILDER_CONFIGS = [
+        FixturesOCRConfig(
+            name="image",
+            description=textwrap.dedent(""),
+            url="",
+            data_url="",
+        )
+    ]
+    DEFAULT_CONFIG_NAME = "image"
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "file": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=("file",),
+            homepage=self.config.url,
+            citation=_CITATION,
+        )
+    def _split_generators(self, dl_manager):
+        DL_URLS = [
+            f"https://huggingface.co/datasets/mishig/fixtures_image_utils/raw/main/{name}"
+            for name in ["cat-rotated.jpg"]
+        ]
+        archive_path = dl_manager.download_and_extract(DL_URLS)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"archive_path": archive_path},
+            ),
+        ]
+    def _generate_examples(self, archive_path):
+        """Generate examples."""
+        for i, filename in enumerate(archive_path):
+            key = str(i)
+            example = {
+                "id": key,
+                "file": filename,
+            }
+            yield key, example