[RetinaNet] Image Converter and ObjectDetector #1906
Conversation
…neeli/keras-hub into sineeli/add-retinanet-phase-2
There was a problem hiding this comment.
Thanks for the PR @sineeli!! Looks generally good!! I have left a few comments.
Also, I want to make sure the -The code usage is updated to reflect the correct implementation - https://docs.google.com/document/d/15FUEP_vNehwLWJLragXhPFkYcbmmpbo0NYh5vL6q1xA/edit?tab=t.0
| metrics=None, | ||
| **kwargs, | ||
| ): | ||
| """Configures the `ImageSegmenter` task for training. |
There was a problem hiding this comment.
update docstring for object detection
| object detection tasks. It is intended to be paired with a | ||
| `keras_hub.models.ImageObjectDetector` task. | ||
|
|
||
| All `ImageObjectDetectorPreprocessor` take inputs three inputs, `x`, `y`, and |
There was a problem hiding this comment.
All ImageObjectDetectorPreprocessor take inputs three inputs -> ImageObjectDetectorPreprocessor class acceptes three inputs: x, y, and...
| data_format = standardize_data_format(data_format) | ||
| input_levels = [int(level[1]) for level in backbone.pyramid_outputs] | ||
| backbone_max_level = min(max(input_levels), max_level) | ||
| image_encoder = keras.Model( |
There was a problem hiding this comment.
ooo, we have an image_encoder here. haha, any suggestions for name here other than image_encoder
There was a problem hiding this comment.
for input args: image_encoder (Backbone)
for pyramid outputs extraction: feature_extractor (Resnet with feature pyramid outputs)
|
Kept some layers |
|
|
||
| The `ImageObjectDetector` tasks wrap a `keras_hub.models.Backbone` and | ||
| a `keras_hub.models.Preprocessor` to create a model that can be used for | ||
| image classification. `ImageObjectDetector` tasks take an additional |
There was a problem hiding this comment.
Object detection
| anchor_size: float. Scale of size of the base anchor relative to the | ||
| feature stride 2^level. | ||
| anchor_generator: A `keras_hub.layers.AnchorGenerator`. | ||
| bounding_box_format: str. TODO: |
There was a problem hiding this comment.
you can still add a line of description here for the arg.
| `RetinaNetObjectDetectorPreprocessor` class or a custom preprocessor. | ||
| activation: Optional. The activation function to be used in the | ||
| classification head. | ||
| head_dtype: Optional. The data type for the prediction heads. |
There was a problem hiding this comment.
The dtype will be the same for the model and the head right? can we just pass dtype here?
| ) | ||
|
|
||
| # === Functional Model === | ||
| image_input = keras.layers.Input(backbone.image_shape, name="images") |
There was a problem hiding this comment.
move layers up under === Layers ===
This PR covers preprocessor for RetinaNet object detector and RetinaNet model itself. #1756
ImageObjectDetectorImageObjectDetectorPreprocessorRetinaNetObjectDetectorRetinaNetObjectDetectorPreprocessorRetinaNetImageConverter