GitLab

PiperOrigin-RevId: 405458782

the image/object/keypoint/text feature but not in the keypoint label map.

PiperOrigin-RevId: 404372105

PiperOrigin-RevId: 404311441

PiperOrigin-RevId: 402944074

- Added configurable arguments in CenterNet for maximum normalized coordinate (this might be useful for handling cases where the bounding box can only be presented out-of-bound with the direction-of-path point at the center in panorama rotation).

PiperOrigin-RevId: 402882653

PiperOrigin-RevId: 402663280

PiperOrigin-RevId: 401003754

PiperOrigin-RevId: 400090738

datasets which contain different subset of keypoints.

PiperOrigin-RevId: 400065449

that maps from the keypoint names to their ids.

PiperOrigin-RevId: 400009398

PiperOrigin-RevId: 399303089

PiperOrigin-RevId: 399210729

PiperOrigin-RevId: 398596089

using 5d tensors to avoid issue when converted to TfLite model.

PiperOrigin-RevId: 398301856

PiperOrigin-RevId: 397358689

PiperOrigin-RevId: 395297294

PiperOrigin-RevId: 394568069

PiperOrigin-RevId: 394512536

PiperOrigin-RevId: 394505975

CenterNet meta arch to avoid using scatter_nd and tf.cond.

Also, use static_or_dynamic_map_fn in the convert_strided_predictions_to_normalized_keypoints function to avoid introducing cycles in the graph that causes the TPU converter errors.

PiperOrigin-RevId: 394152521

runs much slower in the browser.

PiperOrigin-RevId: 394148346

PiperOrigin-RevId: 393480597

The order of the input tensors is incorrect and therefore the sample notebook does not run.

The sample code has the order of the input tensors as `boxes, classes, scores, num_detections`, but actually the order should be `scores, boxes,  num_detections, classes`

After correcting the indexes of the input tensor, the sample notebook runs.

PiperOrigin-RevId: 392061572

  * 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.

PiperOrigin-RevId: 391319766

PiperOrigin-RevId: 391079006

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

PiperOrigin-RevId: 390421432

PiperOrigin-RevId: 388508391

PiperOrigin-RevId: 385646058

PiperOrigin-RevId: 385342213

PiperOrigin-RevId: 385224486

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.

PiperOrigin-RevId: 385136419

PiperOrigin-RevId: 385042521

PiperOrigin-RevId: 383699499

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PiperOrigin-RevId: 383469336

PiperOrigin-RevId: 382773317

PiperOrigin-RevId: 382236941

PiperOrigin-RevId: 381366438

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

PiperOrigin-RevId: 381343791