Add imagenet prediction decoder (#1848)

Author: mattdangerw

keras_hub/api/__init__.py

@@ -23,6 +23,7 @@
 from keras_hub.api import models
 from keras_hub.api import samplers
 from keras_hub.api import tokenizers
+from keras_hub.api import utils
 from keras_hub.src.utils.preset_utils import upload_preset
 from keras_hub.src.version_utils import __version__
 from keras_hub.src.version_utils import version

keras_hub/api/utils/__init__.py

@@ -0,0 +1,22 @@
+# Copyright 2024 The KerasHub 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
+#
+#     https://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.
+"""DO NOT EDIT.
+
+This file was autogenerated. Do not edit it by hand,
+since your modifications would be overwritten.
+"""
+
+from keras_hub.src.utils.imagenet.imagenet_utils import (
+    decode_imagenet_predictions,
+)

keras_hub/src/models/resnet/resnet_image_classifier.py

@@ -45,7 +45,9 @@ class ResNetImageClassifier(ImageClassifier):
     ```python
     # Load preset and train
     images = np.ones((2, 224, 224, 3), dtype="float32")
-    classifier = keras_hub.models.ResNetImageClassifier.from_preset("resnet50")
+    classifier = keras_hub.models.ResNetImageClassifier.from_preset(
+        "resnet_50_imagenet"
+    )
     classifier.predict(images)
     ```
 
@@ -54,13 +56,17 @@ class ResNetImageClassifier(ImageClassifier):
     # Load preset and train
     images = np.ones((2, 224, 224, 3), dtype="float32")
     labels = [0, 3]
-    classifier = keras_hub.models.ResNetImageClassifier.from_preset("resnet50")
+    classifier = keras_hub.models.ResNetImageClassifier.from_preset(
+        "resnet_50_imagenet"
+    )
     classifier.fit(x=images, y=labels, batch_size=2)
     ```
 
     Call `fit()` with custom loss, optimizer and backbone.
     ```python
-    classifier = keras_hub.models.ResNetImageClassifier.from_preset("resnet50")
+    classifier = keras_hub.models.ResNetImageClassifier.from_preset(
+        "resnet_50_imagenet"
+    )
     classifier.compile(
         loss=keras.losses.SparseCategoricalCrossentropy(from_logits=True),
         optimizer=keras.optimizers.Adam(5e-5),

keras_hub/src/utils/imagenet/__init__.py

@@ -0,0 +1,13 @@
+# Copyright 2024 The KerasNLP 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
+#
+#     https://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.