[Bounding Boxes] Add Support for Bounding Box Transformations during Image Resizing

keras/api/_tf_keras/keras/utils/__init__.py

@@ -4,6 +4,7 @@
 since your modifications would be overwritten.
 """
 
+from keras.api.utils import bounding_boxes
 from keras.api.utils import legacy
 from keras.src.backend.common.global_state import clear_session
 from keras.src.backend.common.keras_tensor import is_keras_tensor

keras/api/_tf_keras/keras/utils/bounding_boxes/__init__.py

@@ -0,0 +1,21 @@
+"""DO NOT EDIT.
+
+This file was autogenerated. Do not edit it by hand,
+since your modifications would be overwritten.
+"""
+
+from keras.src.layers.preprocessing.image_preprocessing.bounding_boxes.converters_new import (
+    affine,
+)
+from keras.src.layers.preprocessing.image_preprocessing.bounding_boxes.converters_new import (
+    clip_to_images,
+)
+from keras.src.layers.preprocessing.image_preprocessing.bounding_boxes.converters_new import (
+    convert_format,
+)
+from keras.src.layers.preprocessing.image_preprocessing.bounding_boxes.converters_new import (
+    crop,
+)
+from keras.src.layers.preprocessing.image_preprocessing.bounding_boxes.converters_new import (
+    pad,
+)

keras/api/utils/__init__.py

@@ -4,6 +4,7 @@
 since your modifications would be overwritten.
 """
 
+from keras.api.utils import bounding_boxes
 from keras.api.utils import legacy
 from keras.src.backend.common.global_state import clear_session
 from keras.src.backend.common.keras_tensor import is_keras_tensor

keras/api/utils/bounding_boxes/__init__.py

@@ -0,0 +1,21 @@
+"""DO NOT EDIT.
+
+This file was autogenerated. Do not edit it by hand,
+since your modifications would be overwritten.
+"""
+
+from keras.src.layers.preprocessing.image_preprocessing.bounding_boxes.converters_new import (
+    affine,
+)
+from keras.src.layers.preprocessing.image_preprocessing.bounding_boxes.converters_new import (
+    clip_to_images,
+)
+from keras.src.layers.preprocessing.image_preprocessing.bounding_boxes.converters_new import (
+    convert_format,
+)
+from keras.src.layers.preprocessing.image_preprocessing.bounding_boxes.converters_new import (
+    crop,
+)
+from keras.src.layers.preprocessing.image_preprocessing.bounding_boxes.converters_new import (
+    pad,
+)

keras/src/layers/preprocessing/image_preprocessing/base_image_preprocessing_layer.py

@@ -64,7 +64,12 @@ def transform_labels(self, labels, transformation, training=True):
         raise NotImplementedError()
 
     def transform_bounding_boxes(
-        self, bounding_boxes, transformation, training=True
+        self,
+        bounding_boxes,
+        orig_height,
+        orig_width,
+        transformation,
+        training=True,
     ):
         raise NotImplementedError()
 
@@ -88,11 +93,20 @@ def transform_single_label(self, label, transformation, training=True):
         return self.backend.numpy.squeeze(outputs, axis=0)
 
     def transform_single_bounding_box(
-        self, bounding_box, transformation, training=True
+        self,
+        bounding_box,
+        orig_width,
+        orig_height,
+        transformation,
+        training=True,
     ):
         bounding_boxes = self.backend.numpy.expand_dims(bounding_box, axis=0)
         outputs = self.transform_bounding_boxes(
-            bounding_boxes, transformation=transformation, training=training
+            bounding_boxes,
+            orig_height,
+            orig_width,
+            transformation=transformation,
+            training=training,
         )
         return self.backend.numpy.squeeze(outputs, axis=0)
 
@@ -144,17 +158,47 @@ def call(self, data, training=True):
                         "`bounding_box_format='xyxy'`."
                     )
                 bounding_boxes = densify_bounding_boxes(
-                    data["bounding_boxes"], backend=self.backend
+                    data["bounding_boxes"],
+                    is_batched=is_batched,
+                    backend=self.backend,
                 )
+                if "orig_width" not in data:
+                    raise ValueError(
+                        "'orig_width' key is missing from the input data. "
+                        "Please provide the original image width."
+                    )
+
+                if "orig_height" not in data:
+                    raise ValueError(
+                        "'orig_height' key is missing from the input data. "
+                        "Please provide the original image width."
+                    )
+
                 if is_batched:
+                    orig_width = self.backend.numpy.expand_dims(
+                        data["orig_width"], axis=-1
+                    )
+                    orig_height = self.backend.numpy.expand_dims(
+                        data["orig_height"], axis=-1
+                    )
                     data["bounding_boxes"] = self.transform_bounding_boxes(
                         bounding_boxes,
+                        orig_height,
+                        orig_width,
                         transformation=transformation,
                         training=training,
                     )
                 else:
+                    orig_width = self.backend.numpy.expand_dims(
+                        [data["orig_width"]], axis=-1
+                    )
+                    orig_height = self.backend.numpy.expand_dims(
+                        [data["orig_height"]], axis=-1
+                    )
                     data["bounding_boxes"] = self.transform_single_bounding_box(
                         bounding_boxes,
+                        orig_height,
+                        orig_width,
                         transformation=transformation,
                         training=training,
                     )