Port Faster R-CNN to Keras3

keras_cv/api/models/__init__.py

@@ -259,4 +259,7 @@
 from keras_cv.src.models.stable_diffusion.stable_diffusion import (
     StableDiffusionV2,
 )
+from keras_cv.src.models.object_detection.faster_rcnn.faster_rcnn import (
+    FasterRCNN
+)
 from keras_cv.src.models.task import Task

keras_cv/src/bounding_box/utils.py

@@ -141,7 +141,7 @@ def _clip_boxes(boxes, box_format, image_shape):
 
     if isinstance(image_shape, list) or isinstance(image_shape, tuple):
         height, width, _ = image_shape
-        max_length = [height, width, height, width]
+        max_length = ops.stack([height, width, height, width], axis=-1)
     else:
         image_shape = ops.cast(image_shape, dtype=boxes.dtype)
         height = image_shape[0]

keras_cv/src/layers/object_detection/roi_align.py

@@ -357,7 +357,7 @@ def multilevel_crop_and_resize(
     # TODO(tanzhenyu): replace tf.gather with tf.gather_nd and try to get
     #  similar performance.
     features_per_box = ops.reshape(
-        ops.take(features_r2, indices),
+        ops.take(features_r2, indices, axis=0),
         [
             batch_size,
             num_boxes,

keras_cv/src/models/__init__.py

@@ -242,3 +242,6 @@
 )
 from keras_cv.src.models.stable_diffusion import StableDiffusion
 from keras_cv.src.models.stable_diffusion import StableDiffusionV2
+from keras_cv.src.models.object_detection.faster_rcnn.faster_rcnn import (
+    FasterRCNN
+)

keras_cv/src/models/object_detection/faster_rcnn/__init__.py

@@ -0,0 +1,6 @@
+from keras_cv.src.models.object_detection.faster_rcnn.feature_pyramid import (
+    FeaturePyramid
+)
+
+from keras_cv.src.models.object_detection.faster_rcnn.rpn_head import RPNHead
+from keras_cv.src.models.object_detection.faster_rcnn.rcnn_head import RCNNHead