register depth anything presets (#2420)

* register depth anything presets

* update description and enable tests

* fix expected output shape

* tuple as target img shape

* add depth_estimation_type

Author: sachinprasadhs

keras_hub/src/models/depth_anything/depth_anything_backbone_test.py

@@ -50,23 +50,28 @@ def test_saved_model(self):
         )
 
     @pytest.mark.kaggle_key_required
-    @pytest.mark.extra_large
+    @pytest.mark.large
     def test_smallest_preset(self):
-        self.skipTest("Presets are not uploaded yet.")
+        image_batch = (
+            self.load_test_image(target_size=(518, 518))[None, ...] / 255.0
+        )
         self.run_preset_test(
             cls=DepthAnythingBackbone,
             preset="depth_anything_v2_small",
-            input_data=self.input_data,
-            expected_output_shape=(2, 70, 70, 1),
+            input_data=image_batch,
+            expected_output_shape=(1, 518, 518, 1),
         )
 
     @pytest.mark.kaggle_key_required
     @pytest.mark.extra_large
     def test_all_presets(self):
-        self.skipTest("Presets are not uploaded yet.")
+        image_batch = (
+            self.load_test_image(target_size=(518, 518))[None, ...] / 255.0
+        )
         for preset in DepthAnythingBackbone.presets:
             self.run_preset_test(
                 cls=DepthAnythingBackbone,
                 preset=preset,
-                input_data=self.input_data,
+                input_data=image_batch,
+                expected_output_shape=(1, 518, 518, 1),
             )

keras_hub/src/models/depth_anything/depth_anything_depth_estimator_test.py

@@ -63,12 +63,17 @@ def test_depth_estimator_basics(self):
 
     @pytest.mark.large
     def test_smallest_preset(self):
-        self.skipTest("Presets are not uploaded yet.")
-        image_batch = self.load_test_image(target_size=518)[None, ...] / 255.0
+        image_batch = (
+            self.load_test_image(target_size=(518, 518))[None, ...] / 255.0
+        )
         self.run_preset_test(
             cls=DepthAnythingDepthEstimator,
             preset="depth_anything_v2_small",
             input_data=image_batch,
+            init_kwargs={
+                "depth_estimation_type": "relative",
+                "max_depth": None,
+            },
             expected_output_shape={"depths": (1, 518, 518, 1)},
         )
 

keras_hub/src/models/depth_anything/depth_anything_presets.py

@@ -1,4 +1,41 @@
 """DepthAnything model preset configurations."""
 
 # Metadata for loading pretrained model weights.
-backbone_presets = {}
+backbone_presets = {
+    "depth_anything_v2_small": {
+        "metadata": {
+            "description": (
+                "Small variant of Depth Anything V2 monocular depth estimation "
+                "(MDE) model trained on synthetic labeled images and real "
+                "unlabeled images."
+            ),
+            "params": 25_311_169,
+            "path": "depth_anything",
+        },
+        "kaggle_handle": "kaggle://keras/depth-anything/keras/depth_anything_v2_small/1",
+    },
+    "depth_anything_v2_base": {
+        "metadata": {
+            "description": (
+                "Base variant of Depth Anything V2 monocular depth estimation "
+                "(MDE) model trained on synthetic labeled images and real "
+                "unlabeled images."
+            ),
+            "params": 98_522_945,
+            "path": "depth_anything",
+        },
+        "kaggle_handle": "kaggle://keras/depth-anything/keras/depth_anything_v2_base/1",
+    },
+    "depth_anything_v2_large": {
+        "metadata": {
+            "description": (
+                "Large variant of Depth Anything V2 monocular depth estimation "
+                "(MDE) model trained on synthetic labeled images and real "
+                "unlabeled images."
+            ),
+            "params": 336_718_529,
+            "path": "depth_anything",
+        },
+        "kaggle_handle": "kaggle://keras/depth-anything/keras/depth_anything_v2_large/1",
+    },
+}