kaggle weights

keras_hub/src/models/mobilenet/mobilenet_presets.py

@@ -0,0 +1,67 @@
+"""MobileNet model preset configurations."""
+
+backbone_presets_no_weights = {
+    "mobilenet_v3_small": {
+        "metadata": {
+            "description": (
+                "MobileNetV3 model with 14 layers where the batch "
+                "normalization and hard-swish activation are applied after the "
+                "convolution layers."
+            ),
+            "params": 933502,
+            "official_name": "MobileNetV3",
+            "path": "mobilenetv3",
+        },
+        "kaggle_handle": "kaggle://keras/mobilenetv3/keras/mobilenet_v3_small/2",  # noqa: E501
+    },
+    "mobilenet_v3_large": {
+        "metadata": {
+            "description": (
+                "MobileNetV3 model with 28 layers where the batch "
+                "normalization and hard-swish activation are applied after the "
+                "convolution layers."
+            ),
+            "params": 2994518,
+            "official_name": "MobileNetV3",
+            "path": "mobilenetv3",
+        },
+        "kaggle_handle": "kaggle://keras/mobilenetv3/keras/mobilenet_v3_large/2",  # noqa: E501
+    },
+}
+
+backbone_presets_with_weights = {
+    "mobile_net_v3_large": {
+        "metadata": {
+            "description": (
+                "MobileNetV3 model with 28 layers where the batch "
+                "normalization and hard-swish activation are applied after the "
+                "convolution layers. "
+                "Pre-trained on the ImageNet 2012 classification task."
+            ),
+            "params": 2994518,
+            "official_name": "MobileNetV3",
+            "path": "mobilenetv3",
+        },
+        "kaggle_handle": "kaggle://alexbutcher/mobilenet/keras/mobile_net_v3_large/1",
+        # "kaggle_handle": "kaggle://keras/mobilenetv3/keras/mobilenet_v3_large_imagenet/2",  # noqa: E501
+    },
+    # "mobilenet_v3_small_imagenet": {
+    #     "metadata": {
+    #         "description": (
+    #             "MobileNetV3 model with 14 layers where the batch "
+    #             "normalization and hard-swish activation are applied after the "
+    #             "convolution layers. "
+    #             "Pre-trained on the ImageNet 2012 classification task."
+    #         ),
+    #         "params": 933502,
+    #         "official_name": "MobileNetV3",
+    #         "path": "mobilenetv3",
+    #     },
+    #     "kaggle_handle": "kaggle://keras/mobilenetv3/keras/mobilenet_v3_small_imagenet/2",  # noqa: E501
+    # },
+}
+
+backbone_presets = {
+    # **backbone_presets_no_weights,
+    **backbone_presets_with_weights,
+}