GitLab

PiperOrigin-RevId: 354590046

PiperOrigin-RevId: 354429469

properly changed if the keep_aspect_ratio_resizer was used in conjunction with
pad_to_max_dimension.

PiperOrigin-RevId: 354336467

depth and weight fields.

PiperOrigin-RevId: 353975078

PiperOrigin-RevId: 353788624

Updated the tf_example decoder and decoder builders to parse the keypoint depth features from the input tf.Example.

PiperOrigin-RevId: 353305509

PiperOrigin-RevId: 352873888

PiperOrigin-RevId: 352851428

estimation. It is designed specifically to run the model in the browser
environment using tf.js.

PiperOrigin-RevId: 352609409

PiperOrigin-RevId: 352601466

PiperOrigin-RevId: 351619683

PiperOrigin-RevId: 351610384

FPN network.

PiperOrigin-RevId: 351255218

for object detection and keypoint estimation tasks.

PiperOrigin-RevId: 350640225

PiperOrigin-RevId: 347837387

by default NMS is off.

PiperOrigin-RevId: 347613472

Context R-CNN Updates: Added capabilities to use multi-headed or multi-layered attention, to place the attention heads pre- or post-second stage feature extraction, and to work with embedded features in the context feature back from pre- or post-second stage feature extraction. Added an option for RPN feature map crops to be piped through to model outputs.

PiperOrigin-RevId: 345777219

DEFAULT_VALUE_OK=setting prefetch batches default to 2 as using -1 can cause memory issues for some models such as context r-cnn that use sequence examples.

PiperOrigin-RevId: 345682268

PiperOrigin-RevId: 345620862

PiperOrigin-RevId: 345586686

PiperOrigin-RevId: 345586199

Updating Context R-CNN dataset tools to fix a bug in context feature bank building logic when the number of context examples in the time horizon is greater than the specified maximum, and adding capabilities to track and save the number of embeddings stored per image.

PiperOrigin-RevId: 345548385

added a new operating mode for single-instance prediction.

1) Refactored the _postprocess_keypoints_for_class_and_image function such that
it can be reused by single/multi class keypoint tasks.
2) Removed the "mod" operator to make the model compatible with WASM.

PiperOrigin-RevId: 345468250

Avoid  explicit tf.unstack in `convert_strided_predictions_to_normalized_boxes`. This enables exporting a saved model with dynamic batch size.

PiperOrigin-RevId: 345055072

PiperOrigin-RevId: 344743049

PiperOrigin-RevId: 344310944

Fix the score_converter issue, which should apply on the dimension of num_class_slots per anchor separately, not on all anchors per location together (e.g. think of softmax).

PiperOrigin-RevId: 344143469

PiperOrigin-RevId: 343920343

PiperOrigin-RevId: 343491021

PiperOrigin-RevId: 343342628

Modify adjust_gamma method to only adjust rgb channels (or a single grayscale channel), and to call tf.image.adjust_gamma on an image with values between 0 and 1.

PiperOrigin-RevId: 342911345

PiperOrigin-RevId: 342373365

PiperOrigin-RevId: 341573525

PiperOrigin-RevId: 341188685

Make label_id_offset an argument so it can be turned off when eval_util.result_dict_for_batched_example is applied on the outputs of an exported SavedModel. Exported saved models already apply label offset.

PiperOrigin-RevId: 341176846

Run inference under distribution strategy, gather outputs locally and evaluate the results with coco tools on cpu.

PiperOrigin-RevId: 341162083

PiperOrigin-RevId: 340366780

Fixes two bugs when handling verified_neg_classes and not_exhaustive_classes fields for LVIS evaluation:
(1) Before, if one of these fields was empty, the input pipeline would default to an all-ones representation; this CL turns out off this behavior for the LVIS-specific classes.
(2) Labels are now 1-indexed coming out of the _prepare_groundtruth_for_eval function in model_lib (as they should be).

PiperOrigin-RevId: 340357845

Plumb LVIS specific fields (e.g. `neg_category_ids`, `not_exhaustive_category_ids`) through input pipelines.

PiperOrigin-RevId: 339614575