Delete loading script

brill_iconclass.py

@@ -1,75 +0,0 @@
-# Copyright 2022 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.
-"""Brill Iconclass AI Test Set data."""
-
-import json
-import os
-from PIL import Image
-import datasets
-
-_CITATION = """\
-@MISC{iconclass,
-title = {Brill Iconclass AI Test Set},
-author={Etienne Posthumus},
-year={2020}
-}
-"""
-
-
-_DESCRIPTION = """\
-A dataset for applying machine learning to collections described with the Iconclass classification system.
-"""
-
-_HOMEPAGE = "https://iconclass.org/testset/"
-
-_LICENSE = "https://creativecommons.org/publicdomain/zero/1.0/"
-
-_URL = "https://iconclass.org/testset/779ba2ca9e977c58d818e3823a676973.zip"
-
-class BrillIconclass(datasets.GeneratorBasedBuilder):
-    """Brill IconClass AI dataset"""
-
-    VERSION = datasets.Version("1.1.0")
-
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "image": datasets.Image(),
-                "label": [datasets.Value("string")]
-            }
-        )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        data_dir = dl_manager.download_and_extract(_URL)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"data_json": os.path.join(data_dir, "data.json"), "data_dir": data_dir},
-            ),
-        ]
-
-    def _generate_examples(self, data_json, data_dir):
-        with open(data_json, encoding="utf-8") as f:
-            data = json.load(f)
-            for row, item in enumerate(data.items()):
-                filepath, labels = item
-                yield row, {"image": os.path.join(data_dir, filepath), "label": labels}