Create rock_paper_scissors.py

rock_paper_scissors.py

@@ -0,0 +1,74 @@
+# coding=utf-8
+# Copyright 2021 The TensorFlow 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.
+
+"""Rock, Paper, Scissors dataset."""
+import re
+from pathlib import Path
+
+import datasets
+
+_CITATION = """\
+@ONLINE {rps,
+author = "Laurence Moroney",
+title = "Rock, Paper, Scissors Dataset",
+month = "feb",
+year = "2019",
+url = "http://laurencemoroney.com/rock-paper-scissors-dataset"
+}
+"""
+
+_URLS = {
+    'train': "https://storage.googleapis.com/download.tensorflow.org/data/rps.zip",
+    'test': "https://storage.googleapis.com/download.tensorflow.org/data/rps-test-set.zip"
+}
+_NAMES = ["rock", "paper", "scissors"]
+
+class RockPaperScissors(datasets.GeneratorBasedBuilder):
+  """Rock, Paper, Scissors dataset."""
+
+  def _info(self):
+    return datasets.DatasetInfo(
+        description="Images of hands playing rock, paper, scissor game.",
+        features=datasets.Features({
+            "file":
+                datasets.Value("string"),
+            "labels":
+                datasets.features.ClassLabel(names=sorted(tuple(_NAMES))),
+        }),
+        supervised_keys=("file", "labels"),
+        homepage="http://laurencemoroney.com/rock-paper-scissors-dataset",
+        citation=_CITATION
+    )
+
+  def _split_generators(self, dl_manager):
+    data_files = dl_manager.download_and_extract(_URLS)
+    return [
+        datasets.SplitGenerator(
+            name=datasets.Split.TRAIN,
+            gen_kwargs={
+                "archive": data_files['train'],
+            }),
+        datasets.SplitGenerator(
+            name=datasets.Split.TEST,
+            gen_kwargs={
+                "archive": data_files['test'],
+            }),
+    ]
+
+  def _generate_examples(self, archive):
+    labels = self.info.features['labels']
+    for i, path in enumerate(Path(archive).glob('**/*')):
+        if path.suffix == '.png':
+            yield i, dict(file=path.as_posix(), labels=labels.encode_example(path.parent.name.lower()))