GitLab

PiperOrigin-RevId: 402944074

PiperOrigin-RevId: 397358689

runs much slower in the browser.

PiperOrigin-RevId: 394148346

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.

PiperOrigin-RevId: 379646603

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

PiperOrigin-RevId: 377280733

PiperOrigin-RevId: 373010443

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interpolation method is configurable.

PiperOrigin-RevId: 372198977

for the object center head parameters in CenterNet.

PiperOrigin-RevId: 371783912

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use case which uses the keypoint location to determine the object center
location and heatmap.

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FPN network.

PiperOrigin-RevId: 351255218

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.

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Add a temporal offset prediction head to improve tracking accuracy, similar to "Tracking Objects as Points"(https://arxiv.org/abs/2004.01177).
Notice that the original paper requires a change to the input pipeline, which is not included in this commit.

PiperOrigin-RevId: 330796987

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PiperOrigin-RevId: 321810710

320618558  by rathodv:

    Internal Change.

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320597532  by ronnyvotel:

    Exposing DensePose visualizations to model_lib_v2.py.

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320533669  by ronnyvotel:

    Adding utilities to visualize DensePose outputs.

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320529647  by lzc:

    Fix saved_model issue in object_detection_tutorial notebook.

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320510127  by aom:

    Internal change.

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320490236  by derekjchow:

    Update Dockerfiles to use setup.py

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320443572  by rathodv:

    Update `Tensorflow` to `TensorFlow` in documentation.

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320426460  by ronnyvotel:

    DensePose proto and model builder.

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320352611  by rathodv:

    Update documentation to reflect the support for TF1 and TF2. Provide separate sets of instructions to reduce confusion.

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320350724  by rathodv:

    Internal Change.

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PiperOrigin-RevId: 320618558
Co-authored-by: kmindspark <kaushikshiv@google.com>

320335495  by rathodv:

    Remove hparams support form TF1 main binaries as its not available in TF1.15 runtime on cloud ai platform.

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320278161  by ronnyvotel:

    Exposing DensePose fields to model libraries.

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320277319  by rathodv:

    Remove TPU Name check since TPU is automatically inferred under cloud AI platform.

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320258215  by rathodv:

    Internal Change.

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320245458  by yuhuic:

    Updated the CenterNet restore_from_objects function to be compatible with
    existing configs that load converted checkpoints.

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320225405  by jonathanhuang:

    Small change to Keras box predictor and box heads to fix export errors for SSD and Faster R-CNN.

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320145077  by aom:

    Implements EfficientDet feature extractor.

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PiperOrigin-RevId: 320335495
Co-authored-by: TF Object Detection Team <no-reply@google.com>

319539052  by rathodv:

    Internal Change.

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319537186  by rathodv:

    Internal Change

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319320800  by jonathanhuang:

    Internal changes.

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319260368  by ronnyvotel:

    Adding a target assigner for DensePose.

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319240476  by sbeery:

    switching to main() for argparse

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PiperOrigin-RevId: 319539052
Co-authored-by: TF Object Detection Team <no-reply@google.com>

* Initial commit for faster rcnn resnet v1 fpn feature extractor.

1. Setup code structure for fpn feature extractor

* draft for faster rcnn resnet vi fpn feature extractor

* draft for faster rcnn resnet v1 fpn feature extractor

* add seperated class for resnet 50 101 152

* draft for get_box_classifier_feature_extractor_model

* remove unused code

* Init test file for faster_rcnn_fpn_keras_feature extractor

* add unit test for get_proposal_feature_extractor_model

* add unit test for get_proposal_feature_extractor_model smaller input size

* add unit test for get_proposal_feature_extractor_model incorrect dimension

* change keras model output format

* Update size on extract_proposal_features tests

* change default fpn_min_level to 2

* fix error in get_box_classifier_feature_extractor_model

* add shape test for get_box_classifier_feature_extractor_model

* fix coding style

* Fix coding style for feature extractor.

* add faster rcnn resnet v1 fpn feature extractor to model builder

* rename fpn feature extractors

* modify doc string for Feature extractor:

drop word "implementation"

* add todo in get_box_classifier_feature_extractor_model

* remove enable_v2_behavior

* drop unittest test_extract_proposal_features_dies_with_incorrect_rank_inputs

* modify feature extractor name

* remove min_depth and depth_multiplier feature

* Add coarse layers for faster rcnn fpn keras model

1. Add coarse layers
2. Update corresponding unit test to check the size of the coarse layer
is correct

* change the default max_fpn_level to 6

* change unittest since default max_fpn_level is change to 6

Internal changes

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PiperOrigin-RevId: 316837667