Adding Differential Binarization model from PaddleOCR to Keras3

[gowthamkpr]

This adds the Differntial Binarization model for text detection.

Implemented the architecture based on ResNet50_vd from PaddleOCR and ported the weights.

[mattdangerw]

Let's split this up. Start with ResNetVD backbone?

Some notes...

• Remove the aliases. One ResNetVDBackbone can handle all of these with different presets.
• Conversion scripts as scripts not colabs.
• Follow the local style for backbones as closely as possible. See some comments here Add VGG16 and VGG19 backbone #1737
• Keep models a flat directory. No backbones/xx etc.
• Add some tests.

[divyashreepathihalli]

@gowthamkpr is the PR ready for review?

[divyashreepathihalli]

Thanks for the PR! I have left a reorganization comment.

example for structuring the code - https://github.com/keras-team/keras-hub/tree/master/keras_hub/src/models/sam

[divyashreepathihalli]

rename folder to differential_binarization and file to differential_binarization.py

[divyashreepathihalli]

please create a file differential_binarization_backbone.py and move the diffbin_fpn_model and backbone code into that. You can rename the backbone you are using in this file to image_encoder in the differential_binarization_backbone file. The task model should contain the preprocessor, backbone and the task head.

[divyashreepathihalli]

add test coverage for the losses here

[divyashreepathihalli]

Hi @gowthamkpr! can you please refactor the code to KerasHub style?

• Add a preprocessor flow
• subclass image segementer model for the task class
• add preset class
• add standard test routines

[gowthamkpr]

Hi @gowthamkpr! can you please refactor the code to KerasHub style?

I've refactored using SAM as example.

* [ ]  Add a preprocessor flow

I've added DifferentialBinarizationPreprocessor and DifferentialBinarizationImageConverter.

* [ ]  subclass image segementer model for the task class

I've subclassed ImageSegmenter, but I left the custom compile() method, since we need a different loss than the one used in ImageSegmenter's compile().

* [ ]  add preset class

Done. The model is not yet in Kaggle, so I've disabled the presets test for now.

* [ ]  add standard test routines

Done. Not sure if there are additional standard test routines other than the ones used in SAM that should be run.