Add Imagewoof Dataset

tensorflow_datasets/image/__init__.py

@@ -62,6 +62,7 @@
 from tensorflow_datasets.image.imagenet_resized import ImagenetResized
 from tensorflow_datasets.image.imagenette import Imagenette
 from tensorflow_datasets.image.imagewang import Imagewang
+from tensorflow_datasets.image.imagewoof import Imagewoof
 from tensorflow_datasets.image.inaturalist import INaturalist2017
 from tensorflow_datasets.image.lfw import LFW
 from tensorflow_datasets.image.lost_and_found import LostAndFound

tensorflow_datasets/image/imagewoof.py

@@ -0,0 +1,105 @@
+# coding=utf-8
+# Copyright 2020 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.
+
+# Lint as: python3
+"""Imagewoof Dataset"""
+# gfile cannot be imported directly `from tensorflow.io import gfile`
+import os
+import tensorflow.compat.v2 as tf
+import tensorflow_datasets.public_api as tfds
+
+
+_IMAGEWOOF_URL = "https://s3.amazonaws.com/fast-ai-imageclas/imagewoof2.tgz"
+
+_CITATION = """
+@misc{imagewoof,
+  author    = "Jeremy Howard",
+  title     = "Imagewoof",
+  url       = "https://github.com/fastai/imagenette/"
+}
+"""
+
+_DESCRIPTION = """\
+Imagewoof is a subset of 10 classes from Imagenet that aren't so easy to
+classify, since they're all dog breeds. The breeds are: Australian terrier,
+Border terrier, Samoyed, Beagle, Shih-Tzu, English foxhound, Rhodesian
+ridgeback, Dingo, Golden retriever, Old English sheepdog.
+"""
+
+lbl_dict = {
+    'n02093754': 'Australian terrier',
+    'n02089973': 'Border terrier',
+    'n02099601': 'Samoyed',
+    'n02087394': 'Beagle',
+    'n02105641': 'Shih-Tzu',
+    'n02096294': 'English foxhound',
+    'n02088364': 'Rhodesian ridgeback',
+    'n02115641': 'Dingo',
+    'n02111889': 'Golden retriever',
+    'n02086240': 'Old English sheepdog'
+}
+
+
+class Imagewoof(tfds.core.GeneratorBasedBuilder):
+  """Imagewoof Dataset"""
+  VERSION = tfds.core.Version('0.1.0')
+
+  def _info(self):
+    return tfds.core.DatasetInfo(
+        builder=self,
+        description=_DESCRIPTION,
+        features=tfds.features.FeaturesDict({
+            "image": tfds.features.Image(),
+            "label": tfds.features.ClassLabel(
+                names=['Australian terrier', 'Border terrier', 'Samoyed',
+                       'Beagle', 'Shih-Tzu', 'English foxhound',
+                       'Rhodesian ridgeback', 'Dingo', 'Golden retriever',
+                       'Old English sheepdog']),
+        }),
+        supervised_keys=("image", "label"),
+        homepage="https://github.com/fastai/imagenette",
+        citation=_CITATION
+    )
+
+  def _split_generators(self, dl_manager):
+    """Generate Splits"""
+    extracted_path = dl_manager.download_and_extract(_IMAGEWOOF_URL)
+    extracted_path = os.path.join(extracted_path, 'imagewoof2')
+    # Specify the splits
+    return [
+        tfds.core.SplitGenerator(
+            name=tfds.Split.TRAIN,
+            gen_kwargs={
+                "images_dir_path": os.path.join(extracted_path, "train"),
+            }),
+        tfds.core.SplitGenerator(
+            name=tfds.Split.VALIDATION,
+            gen_kwargs={
+                "images_dir_path": os.path.join(extracted_path, "val"),
+            }),
+        ]
+
+  def _generate_examples(self, images_dir_path):
+    """Generate examples given the image directory path"""
+    count = 0
+    for image_folder in tf.io.gfile.listdir(images_dir_path):
+      for image_file in tf.io.gfile.listdir(os.path.join(images_dir_path,
+                                                         image_folder)):
+        yield count, {
+            'image': '{}/{}/{}'.format(images_dir_path, image_folder,
+                                       image_file),
+            'label': lbl_dict[image_folder]
+        }
+        count += 1

tensorflow_datasets/image/imagewoof_test.py

@@ -0,0 +1,34 @@
+# coding=utf-8
+# Copyright 2020 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.
+
+# Lint as: python3
+
+"""Tests for Imagewoof."""
+
+from tensorflow_datasets import testing
+from tensorflow_datasets.image import imagewoof
+
+
+
+class ImagewangFullSizeTest(testing.DatasetBuilderTestCase):
+  DATASET_CLASS = imagewoof.Imagewoof
+  SPLITS = {
+      "train": 4,
+      "validation": 4,
+  }
+
+
+if __name__ == "__main__":
+  testing.test_main()

tensorflow_datasets/url_checksums/imagewoof.txt

@@ -0,0 +1 @@
+https://s3.amazonaws.com/fast-ai-imageclas/imagewoof2.tgz 1343482285 d6f2ffc7b95663f7701b94cea32db1683b9a50dd389382c7cca024e840af0379