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  * Replaced the deprecated `to_int/to_float` in `center_net_meta_arch.py` with `tf.cast()` (following the warning).
  * Added `max_norm_coord` argument to CenterNet source code to allow controlling the maximum coordinate value to be considered, to allow for the wrap-around special case for RxR data.

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true_image_shape is not required and can be inferred by the prediction tensors.

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Made changes in `center_net_meta_arch.py` for the particular use case in Marky Landmark Detection, i.e.
1. Accessing an access-protected field in the model;
2. Traverse layers to set trainability.

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This allows the exported TF Lite MoveNet model to be able to run on device GPU
using OpenCL/OpenGL.

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over new parameters in the CenterNet model.

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1) Added the score-to-scaled-distance ranking method.
2) Added the gaussian-weighted ranking method.
3) Added the hyperparameter used in the rescoring function.

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1. Make api_template always use third_party/py/keras (or keras PIP package in OSS).
2. API tests are updated to ignore tensorflow/python/keras end points.
3. All Keras-related code will be removed in a follow up change. Keras-specific APIs are tracked in google3/third_party/py/keras/api/golden/
4. There are a few APIs (optimizer/initializer) that are exposed as both tf and keras APIs. Their pbtxt are updated to reflect the latest class path change.

Once this change is submitted, the current code in tensorflow/python/keras will become a stale copy, and will be removed soon. No more changes should be made to tensorflow/python/keras.

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Add notebook and update ODT TFLite conversion doc to show how to make the model compatible with TFLite Task Library.

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region for the keypoint heatmap if the instance's keypoint visibility is 0.

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Adding head customization parameters to `ObjectDetection` and `MaskEstimation` CenterNet proto messages.

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