GitLab

319125512  by aom:

    Internal change

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319108395  by rathodv:

    Internal Change

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319106259  by ronnyvotel:

    Updating input pipeline to return DensePose labels.

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PiperOrigin-RevId: 319125512
Co-authored-by: Zhichao Lu <lzc@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

319052168  by rathodv:

    Change assertAllEqual to assertAllClose for Position Sensitive Crop and Resize to avoid flaky tests.

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319044492  by rathodv:

    Internal change.

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319039033  by ronnyvotel:

    Preprocessor ops for DensePose.

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319035440  by sbeery:

    External beam code with DataFlow Support

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318899436  by ronnyvotel:

    DensePose library for common operations like scaling, coordinate transformations, and flipping.

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318833308  by Vivek Rathod:

      Internal Change

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PiperOrigin-RevId: 319052168

318569851  by jonathanhuang:

    Fix for fine-tuning from classification checkpoints in the v2 binary.

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PiperOrigin-RevId: 318569851

318545448  by jonathanhuang:

    Modifies visualization code in TF2 evaluation loop so that we don't write out image summaries to disk for every single image.  This change will reduce summary file sizes by ~2 orders of magnitude on average and speed up evaluation cycles (20 minutes per COCO eval cycle vs 2 hours for RetinaNet).

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318514741  by sbeery:

    Adding link to the blog post

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PiperOrigin-RevId: 318545448

318497061  by rathodv:

    1. Replace strategy.run() with strategy.experimental_run_v2() and replace tensor.ref() with tensor.experimental_ref() to be compatible with TF2.1 runtime on cloud.
    2. Fix expected string in failing PY3 tests.

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318493408  by aom:

    Implements "Bidirectional Feature Pyramid Network Generators" for BiFPN-based feature extractors (e.g. EfficientDet).

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PiperOrigin-RevId: 318497061

318417714  by jonathanhuang:

    Internal change.

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318367213  by sbeery:

    Pointing users to more documentation for beam

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318358685  by sbeery:

    Context R-CNN sample config for GPU

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318309800  by rathodv:

    Internal

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318303364  by ronnyvotel:

    Adding the option for parsing and including DensePose annotations. http://densepose.org/

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318291319  by aom:

    Adds conv_bn_act conv_block option, and naming convention changes for BiFPN utils.

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318200598  by ronnyvotel:

    Updating the TF Example Decoder to parse DensePose annotations.

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318174065  by jonathanhuang:

    Internal change.

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318167805  by rathodv:

    Add use_tpu flag to TF2 binary.

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318145285  by aom:

    Adds option for convolutional keras box predictor to force use_bias.

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PiperOrigin-RevId: 318417714

318106429  by derekjchow:

    Add Dockerfiles for TF-OD API.

    1.15 and 2.2 supported currently.

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318083650  by rathodv:

    Internal Change.

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317893148  by Zhichao Lu:

    Fix mapping from proto fields to parameters of the data augmentation functions for horizontal flip, vertical flip and 90 degree rotations.

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317753117  by Zhichao Lu:

    Adds keras hyperparam option to force use_bias to True, even when using batch norm.

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317613986  by Zhichao Lu:

    Improves Keypoints support for data augmentation by means of 90 degree rotation adding an option to permute keypoints.

    Unify the interfaces among flip and rotation ops for data augmentation by exposing additional properties to the user.

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317136881  by Zhichao Lu:

    Clarifying documentation

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317097141  by Zhichao Lu:

    Adding Context R-CNN Release to TFODAPI ReadMe

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316999744  by Zhichao Lu:

    Add import tensorflow.compat.v2 as tf2 in the model_lib to
    ensure tf1 compatibility.

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316964482  by Zhichao Lu:

    adding a note about a config change needed for exporting detection features

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316944293  by Zhichao Lu:

    Adding install instructions for apache beam

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316917592  by lzc:

    Internal change.

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PiperOrigin-RevId: 318106429
Co-authored-by: Zhichao Lu <lzc@google.com>

Context R-CNN: Long Term Temporal Context for Per Camera Object Detection

http://openaccess.thecvf.com/content_CVPR_2020/html/Beery_Context_R-CNN_Long_Term_Temporal_Context_for_Per-Camera_Object_Detection_CVPR_2020_paper.html

Internal changes

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PiperOrigin-RevId: 316837667