GitLab

PiperOrigin-RevId: 341188685

PiperOrigin-RevId: 329650549

PiperOrigin-RevId: 328477362

310447280  by lzc:

    Internal change

310420845  by Zhichao Lu:

    Open source the internal Context RCNN code.

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310362339  by Zhichao Lu:

    Internal change

310259448  by lzc:

    Update required TF version for OD API.

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310252159  by Zhichao Lu:

    Port patch_ops_test to TF1/TF2 as TPUs.

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310247180  by Zhichao Lu:

    Ignore keypoint heatmap loss in the regions/bounding boxes with target keypoint
    class but no valid keypoint annotations.

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310178294  by Zhichao Lu:

    Opensource MnasFPN
    https://arxiv.org/abs/1912.01106

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310094222  by lzc:

    Internal changes.

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310085250  by lzc:

    Internal Change.

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310016447  by huizhongc:

    Remove unrecognized classes from labeled_classes.

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310009470  by rathodv:

    Mark batcher.py as TF1 only.

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310001984  by rathodv:

    Update core/preprocessor.py to be compatible with TF1/TF2..

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309455035  by Zhichao Lu:

    Makes the freezable_batch_norm_test run w/ v2 behavior.

    The main change is in v2 updates will happen right away when running batchnorm in training mode. So, we need to restore the weights between batchnorm calls to make sure the numerical checks all start from the same place.

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309425881  by Zhichao Lu:

    Make TF1/TF2 optimizer builder tests explicit.

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309408646  by Zhichao Lu:

    Make dataset builder tests TF1 and TF2 compatible.

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309246305  by Zhichao Lu:

    Added the functionality of combining the person keypoints and object detection
    annotations in the binary that converts the COCO raw data to TfRecord.

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309125076  by Zhichao Lu:

    Convert target_assigner_utils to TF1/TF2.

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308966359  by huizhongc:

    Support SSD training with partially labeled groundtruth.

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308937159  by rathodv:

    Update core/target_assigner.py to be compatible with TF1/TF2.

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308774302  by Zhichao Lu:

    Internal

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308732860  by rathodv:

    Make core/prefetcher.py  compatible with TF1 only.

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308726984  by rathodv:

    Update core/multiclass_nms_test.py to be TF1/TF2 compatible.

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308714718  by rathodv:

    Update core/region_similarity_calculator_test.py to be TF1/TF2 compatible.

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308707960  by rathodv:

    Update core/minibatch_sampler_test.py to be TF1/TF2 compatible.

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308700595  by rathodv:

    Update core/losses_test.py to be TF1/TF2 compatible and remove losses_test_v2.py

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308361472  by rathodv:

    Update core/matcher_test.py to be TF1/TF2 compatible.

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308335846  by Zhichao Lu:

    Updated the COCO evaluation logics and populated the groundturth area
    information through. This change matches the groundtruth format expected by the
    COCO keypoint evaluation.

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308256924  by rathodv:

    Update core/keypoints_ops_test.py to be TF1/TF2 compatible.

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308256826  by rathodv:

    Update class_agnostic_nms_test.py to be TF1/TF2 compatible.

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308256112  by rathodv:

    Update box_list_ops_test.py to be TF1/TF2 compatible.

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308159360  by Zhichao Lu:

    Internal change

308145008  by Zhichao Lu:

    Added 'image/class/confidence' field in the TFExample decoder.

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307651875  by rathodv:

    Refactor core/box_list.py to support TF1/TF2.

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307651798  by rathodv:

    Modify box_coder.py base class to work with with TF1/TF2

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307651652  by rathodv:

    Refactor core/balanced_positive_negative_sampler.py to support TF1/TF2.

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307651571  by rathodv:

    Modify BoxCoders tests to use test_case:execute method to allow testing with TF1.X and TF2.X

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307651480  by rathodv:

    Modify Matcher tests to use test_case:execute method to allow testing with TF1.X and TF2.X

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307651409  by rathodv:

    Modify AnchorGenerator tests to use test_case:execute method to allow testing with TF1.X and TF2.X

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307651314  by rathodv:

    Refactor model_builder to support TF1 or TF2 models based on TensorFlow version.

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307092053  by Zhichao Lu:

    Use manager to save checkpoint.

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307071352  by ronnyvotel:

    Fixing keypoint visibilities. Now by default, the visibility is marked True if the keypoint is labeled (regardless of whether it is visible or not).
    Also, if visibilities are not present in the dataset, they will be created based on whether the keypoint coordinates are finite (vis = True) or NaN (vis = False).

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307069557  by Zhichao Lu:

    Internal change to add few fields related to postprocessing parameters in
    center_net.proto and populate those parameters to the keypoint postprocessing
    functions.

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307012091  by Zhichao Lu:

    Make Adam Optimizer's epsilon proto configurable.

    Potential issue: tf.compat.v1's AdamOptimizer has a default epsilon on 1e-08 ([doc-link](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/AdamOptimizer))  whereas tf.keras's AdamOptimizer has default epsilon 1e-07 ([doc-link](https://www.tensorflow.org/api_docs/python/tf/keras/optimizers/Adam))

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306858598  by Zhichao Lu:

    Internal changes to update the CenterNet model:
    1) Modified eval job loss computation to avoid averaging over batches with zero loss.
    2) Updated CenterNet keypoint heatmap target assigner to apply box size to heatmap Guassian standard deviation.
    3) Updated the CenterNet meta arch keypoint losses computation to apply weights outside of loss function.

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306731223  by jonathanhuang:

    Internal change.

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306549183  by rathodv:

    Internal Update.

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306542930  by rathodv:

    Internal Update

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306322697  by rathodv:

    Internal.

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305345036  by Zhichao Lu:

    Adding COCO Camera Traps Json to tf.Example beam code

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304104869  by lzc:

    Internal changes.

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304068971  by jonathanhuang:

    Internal change.

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304050469  by Zhichao Lu:

    Internal change.

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303880642  by huizhongc:

    Support parsing partially labeled groundtruth.

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303841743  by Zhichao Lu:

    Deprecate nms_on_host in SSDMetaArch.

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303803204  by rathodv:

    Internal change.

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303793895  by jonathanhuang:

    Internal change.

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303467631  by rathodv:

    Py3 update for detection inference test.

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303444542  by rathodv:

    Py3 update to metrics module

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303421960  by rathodv:

    Update json_utils to python3.

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302787583  by ronnyvotel:

    Coco results generator for submission to the coco test server.

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302719091  by Zhichao Lu:

    Internal change to add the ResNet50 image feature extractor for CenterNet model.

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302116230  by Zhichao Lu:

    Added the functions to overlay the heatmaps with images in visualization util
    library.

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301888316  by Zhichao Lu:

    Fix checkpoint_filepath not defined error.

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301840312  by ronnyvotel:

    Adding keypoint_scores to visualizations.

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301683475  by ronnyvotel:

    Introducing the ability to preprocess `keypoint_visibilities`.

    Some data augmentation ops such as random crop can filter instances and keypoints. It's important to also filter keypoint visibilities, so that the groundtruth tensors are always in alignment.

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301532344  by Zhichao Lu:

    Don't use tf.divide since "Quantization not yet supported for op: DIV"

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301480348  by ronnyvotel:

    Introducing keypoint evaluation into model lib v2.
    Also, making some fixes to coco keypoint evaluation.

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301454018  by Zhichao Lu:

    Added the image summary to visualize the train/eval input images and eval's
    prediction/groundtruth side-by-side image.

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301317527  by Zhichao Lu:

    Updated the random_absolute_pad_image function in the preprocessor library to
    support the keypoints argument.

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301300324  by Zhichao Lu:

    Apply name change(experimental_run_v2 -> run) for all callers in Tensorflow.

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301297115  by ronnyvotel:

    Utility function for setting keypoint visibilities based on keypoint coordinates.

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301248885  by Zhichao Lu:

    Allow MultiworkerMirroredStrategy(MWMS) use by adding checkpoint handling with temporary directories in model_lib_v2. Added missing WeakKeyDictionary cfer_fn_cache field in CollectiveAllReduceStrategyExtended.

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301224559  by Zhichao Lu:

    ...1) Fixes model_lib to also use keypoints while preparing model groundtruth.
    ...2) Tests model_lib with newly added keypoint metrics config.

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300836556  by Zhichao Lu:

    Internal changes to add keypoint estimation parameters in CenterNet proto.

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300795208  by Zhichao Lu:

    Updated the eval_util library to populate the keypoint groundtruth to
    eval_dict.

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299474766  by Zhichao Lu:

    ...Modifies eval_util to create Keypoint Evaluator objects when configured in eval config.

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299453920  by Zhichao Lu:

    Add swish activation as a hyperperams option.

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299240093  by ronnyvotel:

    Keypoint postprocessing for CenterNetMetaArch.

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299176395  by Zhichao Lu:

    Internal change.

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299135608  by Zhichao Lu:

    Internal changes to refactor the CenterNet model in preparation for keypoint estimation tasks.

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298915482  by Zhichao Lu:

    Make dataset_builder aware of input_context for distributed training.

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298713595  by Zhichao Lu:

    Handling data with negative size boxes.

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298695964  by Zhichao Lu:

    Expose change_coordinate_frame as a config parameter; fix multiclass_scores optional field.

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298492150  by Zhichao Lu:

    Rename optimizer_builder_test_v2.py -> optimizer_builder_v2_test.py

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298476471  by Zhichao Lu:

    Internal changes to support CenterNet keypoint estimation.

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298365851  by ronnyvotel:

    Fixing a bug where groundtruth_keypoint_weights were being padded with a dynamic dimension.

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297843700  by Zhichao Lu:

    Internal change.

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297706988  by lzc:

    Internal change.

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297705287  by ronnyvotel:

    Creating the "snapping" behavior in CenterNet, where regressed keypoints are refined with updated candidate keypoints from a heatmap.

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297700447  by Zhichao Lu:

    Improve checkpoint checking logic with TF2 loop.

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297686094  by Zhichao Lu:

    Convert "import tensorflow as tf" to "import tensorflow.compat.v1".

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297670468  by lzc:

    Internal change.

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297241327  by Zhichao Lu:

    Convert "import tensorflow as tf" to "import tensorflow.compat.v1".

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297205959  by Zhichao Lu:

    Internal changes to support refactored the centernet object detection target assigner into a separate library.

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297143806  by Zhichao Lu:

    Convert "import tensorflow as tf" to "import tensorflow.compat.v1".

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297129625  by Zhichao Lu:

    Explicitly replace "import tensorflow" with "tensorflow.compat.v1" for TF2.x migration

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297117070  by Zhichao Lu:

    Explicitly replace "import tensorflow" with "tensorflow.compat.v1" for TF2.x migration

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297030190  by Zhichao Lu:

    Add configuration options for visualizing keypoint edges

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296359649  by Zhichao Lu:

    Support DepthwiseConv2dNative (of separable conv) in weight equalization loss.

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296290582  by Zhichao Lu:

    Internal change.

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296093857  by Zhichao Lu:

    Internal changes to add general target assigner utilities.

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295975116  by Zhichao Lu:

    Fix visualize_boxes_and_labels_on_image_array to show max_boxes_to_draw correctly.

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295819711  by Zhichao Lu:

    Adds a flag to visualize_boxes_and_labels_on_image_array to skip the drawing of axis aligned bounding boxes.

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295811929  by Zhichao Lu:

    Keypoint support in random_square_crop_by_scale.

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295788458  by rathodv:

    Remove unused checkpoint to reduce repo size on github

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295787184  by Zhichao Lu:

    Enable visualization of edges between keypoints

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295763508  by Zhichao Lu:

    [Context RCNN] Add an option to enable / disable cropping feature in the post
    process step in the meta archtecture.

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295605344  by Zhichao Lu:

    internal change.

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294926050  by ronnyvotel:

    Adding per-keypoint groundtruth weights. These weights are intended to be used as multipliers in a keypoint loss function.

    Groundtruth keypoint weights are constructed as follows:
    - Initialize the weight for each keypoint type based on user-specified weights in the input_reader proto
    - Mask out (i.e. make zero) all keypoint weights that are not visible.

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294829061  by lzc:

    Internal change.

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294566503  by Zhichao Lu:

    Changed internal CenterNet Model configuration.

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294346662  by ronnyvotel:

    Using NaN values in keypoint coordinates that are not visible.

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294333339  by Zhichao Lu:

    Change experimetna_distribute_dataset -> experimental_distribute_dataset_from_function

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293928752  by Zhichao Lu:

    Internal change

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293909384  by Zhichao Lu:

    Add capabilities to train 1024x1024 CenterNet models.

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293637554  by ronnyvotel:

    Adding keypoint visibilities to TfExampleDecoder.

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293501558  by lzc:

    Internal change.

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293252851  by Zhichao Lu:

    Change tf.gfile.GFile to tf.io.gfile.GFile.

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292730217  by Zhichao Lu:

    Internal change.

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292456563  by lzc:

    Internal changes.

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292355612  by Zhichao Lu:

    Use tf.gather and tf.scatter_nd instead of matrix ops.

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292245265  by rathodv:

    Internal

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291989323  by richardmunoz:

    Refactor out building a DataDecoder from building a tf.data.Dataset.

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291950147  by Zhichao Lu:

    Flip bounding boxes in arbitrary shaped tensors.

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291401052  by huizhongc:

    Fix multiscale grid anchor generator to allow fully convolutional inference. When exporting model with identity_resizer as image_resizer, there is an incorrect box offset on the detection results. We add the anchor offset to address this problem.

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291298871  by Zhichao Lu:

    Py3 compatibility changes.

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290957957  by Zhichao Lu:

    Hourglass feature extractor for CenterNet.

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290564372  by Zhichao Lu:

    Internal change.

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290155278  by rathodv:

    Remove Dataset Explorer.

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290155153  by Zhichao Lu:

    Internal change

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290122054  by Zhichao Lu:

    Unify the format in the faster_rcnn.proto

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290116084  by Zhichao Lu:

    Deprecate tensorflow.contrib.

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290100672  by Zhichao Lu:

    Update MobilenetV3 SSD candidates

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289926392  by Zhichao Lu:

    Internal change

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289553440  by Zhichao Lu:

    [Object Detection API] Fix the comments about the dimension of the rpn_box_encodings from 4-D to 3-D.

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288994128  by lzc:

    Internal changes.

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288942194  by lzc:

    Internal change.

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288746124  by Zhichao Lu:

    Configurable channel mean/std. dev in CenterNet feature extractors.

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288552509  by rathodv:

    Internal.

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288541285  by rathodv:

    Internal update.

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288396396  by Zhichao Lu:

    Make object detection import contrib explicitly

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288255791  by rathodv:

    Internal

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288078600  by Zhichao Lu:

    Fix model_lib_v2 test

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287952244  by rathodv:

    Internal

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287921774  by Zhichao Lu:

    internal change

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287906173  by Zhichao Lu:

    internal change

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287889407  by jonathanhuang:

    PY3 compatibility

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287889042  by rathodv:

    Internal

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287876178  by Zhichao Lu:

    Internal change.

--
287770490  by Zhichao Lu:

    Add CenterNet proto and builder

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287694213  by Zhichao Lu:

    Support for running multiple steps per tf.function call.

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287377183  by jonathanhuang:

    PY3 compatibility

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287371344  by rathodv:

    Support loading keypoint labels and ids.

--
287368213  by rathodv:

    Add protos supporting keypoint evaluation.

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286673200  by rathodv:

    dataset_tools PY3 migration

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286635106  by Zhichao Lu:

    Update code for upcoming tf.contrib removal

--
286479439  by Zhichao Lu:

    Internal change

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286311711  by Zhichao Lu:

    Skeleton of context model within TFODAPI

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286005546  by Zhichao Lu:

    Fix Faster-RCNN training when using keep_aspect_ratio_resizer with pad_to_max_dimension

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285906400  by derekjchow:

    Internal change

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285822795  by Zhichao Lu:

    Add CenterNet meta arch target assigners.

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285447238  by Zhichao Lu:

    Internal changes.

--
285016927  by Zhichao Lu:

    Make _dummy_computation a tf.function. This fixes breakage caused by
    cl/284256438

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284827274  by Zhichao Lu:

    Convert to python 3.

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284645593  by rathodv:

    Internal change

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284639893  by rathodv:

    Add missing documentation for keypoints in eval_util.py.

--
284323712  by Zhichao Lu:

    Internal changes.

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284295290  by Zhichao Lu:

    Updating input config proto and dataset builder to include context fields

    Updating standard_fields and tf_example_decoder to include context features

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284226821  by derekjchow:

    Update exporter.

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284211030  by Zhichao Lu:

    API changes in CenterNet informed by the experiments with hourlgass network.

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284190451  by Zhichao Lu:

    Add support for CenterNet losses in protos and builders.

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284093961  by lzc:

    Internal changes.

--
284028174  by Zhichao Lu:

    Internal change

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284014719  by derekjchow:

    Do not pad top_down feature maps unnecessarily.

--
284005765  by Zhichao Lu:

    Add new pad_to_multiple_resizer

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283858233  by Zhichao Lu:

    Make target assigner work when under tf.function.

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283836611  by Zhichao Lu:

    Make config getters more general.

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283808990  by Zhichao Lu:

    Internal change

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283754588  by Zhichao Lu:

    Internal changes.

--
282460301  by Zhichao Lu:

    Add ability to restore v2 style checkpoints.

--
281605842  by lzc:

    Add option to disable loss computation in OD API eval job.

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280298212  by Zhichao Lu:

    Add backwards compatible change

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280237857  by Zhichao Lu:

    internal change

--

PiperOrigin-RevId: 310447280

280142968  by Zhichao Lu:

    Opensource MobilenetEdgeTPU + ssdlite into third-party object detection APIs on EdgeTPU.

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280134001  by Zhichao Lu:

    Adds MobilenetEdgeTpu + ssdlite into internal object detection APIs on EdgeTPU.

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278941778  by Zhichao Lu:

    Add support for fixed input shapes for 'encoded_image_string_tensor' and 'tf_example' inputs.

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278933274  by Zhichao Lu:

      Adding fool proof check to avoid using 1x1 depthwise conv op.

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278762192  by Zhichao Lu:

    Ensure correct number of iterations after training resumes.

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278746440  by Zhichao Lu:

    Internal change.

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278006953  by Zhichao Lu:

    Internal changes to tf.contrib symbols

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278006330  by Zhichao Lu:

    Internal changes to tf.contrib symbols

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277593959  by Zhichao Lu:

      Make the ssd_feature_extractor_test.py PY3 compatible. The "six.zip" will use "itertools.izip" in Python 2 and "zip" in Python 3.

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277344551  by Zhichao Lu:

    Internal change.

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277154953  by Zhichao Lu:

    Conditionally use keras based optimizers so that check-pointing works correctly.
    This change also enables summaries on TPU which were previously not enabled
    due to a bug.

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277087572  by Zhichao Lu:

    Fix resizing boxes when using keep_aspect_ratio_rezier with padding.

--
275898543  by Zhichao Lu:

    Support label_map_proto as input in label_map_util.

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275347137  by Zhichao Lu:

    Add force_no_resize flag in eval.proto which replaces
    the resize config with identity resizer. This is useful
    when we want to test at the original image resolution.

--

PiperOrigin-RevId: 280142968

* Merged commit includes the following changes:
275131829  by Sergio Guadarrama:

    updates mobilenet/README.md to be github compatible adds V2+ reference to mobilenet_v1.md file and fixes invalid markdown

--
274908068  by Sergio Guadarrama:

    Opensource MobilenetV3 detection models.

--
274697808  by Sergio Guadarrama:

    Fixed cases where tf.TensorShape was constructed with float dimensions

    This is a prerequisite for making TensorShape and Dimension more strict
    about the types of their arguments.

--
273577462  by Sergio Guadarrama:

    Fixing `conv_defs['defaults']` override issue.

--
272801298  by Sergio Guadarrama:

    Adds links to trained models for Moblienet V3, adds a version of minimalistic mobilenet-v3 to the definitions.

--
268928503  by Sergio Guadarrama:

    Mobilenet v2 with group normalization.

--
263492735  by Sergio Guadarrama:

    Internal change

260037126  by Sergio Guadarrama:

    Adds an option of using a custom depthwise operation in `expanded_conv`.

--
259997001  by Sergio Guadarrama:

    Explicitly mark Python binaries/tests with python_version = "PY2".

--
252697685  by Sergio Guadarrama:

    Internal change

251918746  by Sergio Guadarrama:

    Internal change

251909704  by Sergio Guadarrama:

    Mobilenet V3 backbone implementation.

--
247510236  by Sergio Guadarrama:

    Internal change

246196802  by Sergio Guadarrama:

    Internal change

246014539  by Sergio Guadarrama:

    Internal change

245891435  by Sergio Guadarrama:

    Internal change

245834925  by Sergio Guadarrama:

    n/a

--

PiperOrigin-RevId: 275131829

* Merged commit includes the following changes:
274959989  by Zhichao Lu:

    Update detection model zoo with MobilenetV3 SSD candidates.

--
274908068  by Zhichao Lu:

    Opensource MobilenetV3 detection models.

--
274695889  by richardmunoz:

    RandomPatchGaussian preprocessing step

    This step can be used during model training to randomly apply gaussian noise to a random image patch. Example addition to an Object Detection API pipeline config:

    train_config {
      ...
      data_augmentation_options {
        random_patch_gaussian {
          random_coef: 0.5
          min_patch_size: 1
          max_patch_size: 250
          min_gaussian_stddev: 0.0
          max_gaussian_stddev: 1.0
        }
      }
      ...
    }

--
274257872  by lzc:

    Internal change.

--
274114689  by Zhichao Lu:

    Pass native_resize flag to other FPN variants.

--
274112308  by lzc:

    Internal change.

--
274090763  by richardmunoz:

    Util function for getting a patch mask on an image for use with the Object Detection API

--
274069806  by Zhichao Lu:

    Adding functions which will help compute predictions and losses for CenterNet.

--
273860828  by lzc:

    Internal change.

--
273380069  by richardmunoz:

    RandomImageDownscaleToTargetPixels preprocessing step

    This step can be used during model training to randomly downscale an image to a random target number of pixels. If the image does not contain more than the target number of pixels, then downscaling is skipped. Example addition to an Object Detection API pipeline config:

    train_config {
      ...
      data_augmentation_options {
        random_downscale_to_target_pixels {
          random_coef: 0.5
          min_target_pixels: 300000
          max_target_pixels: 500000
        }
      }
      ...
    }

--
272987602  by Zhichao Lu:

    Avoid -inf when empty box list is passed.

--
272525836  by Zhichao Lu:

    Cleanup repeated resizing code in meta archs.

--
272458667  by richardmunoz:

    RandomJpegQuality preprocessing step

    This step can be used during model training to randomly encode the image into a jpeg with a random quality level. Example addition to an Object Detection API pipeline config:

    train_config {
      ...
      data_augmentation_options {
        random_jpeg_quality {
          random_coef: 0.5
          min_jpeg_quality: 80
          max_jpeg_quality: 100
        }
      }
      ...
    }

--
271412717  by Zhichao Lu:

    Enables TPU training with the V2 eager + tf.function Object Detection training loops.

--
270744153  by Zhichao Lu:

    Adding the offset and size target assigners for CenterNet.

--
269916081  by Zhichao Lu:

    Include basic installation in Object Detection API tutorial.
    Also:
     - Use TF2.0
     - Use saved_model

--
269376056  by Zhichao Lu:

    Fix to variable loading in RetinaNet w/ custom loops. (makes the code rely on the exact name scopes that are generated a little bit less)

--
269256251  by lzc:

    Add use_partitioned_nms field to config and update post_prossing_builder to honor that flag when building nms function.

--
268865295  by Zhichao Lu:

    Adding functionality for importing and merging back internal state of the metric.

--
268640984  by Zhichao Lu:

    Fix computation of gaussian sigma value to create CenterNet heatmap target.

--
267475576  by Zhichao Lu:

    Fix for exporter trying to export non-existent exponential moving averages.

--
267286768  by Zhichao Lu:

    Update mixed-precision policy.

--
266166879  by Zhichao Lu:

    Internal change

265860884  by Zhichao Lu:

    Apply floor function to center coordinates when creating heatmap for CenterNet target.

--
265702749  by Zhichao Lu:

    Internal change

--
264241949  by ronnyvotel:

    Updating Faster R-CNN 'final_anchors' to be in normalized coordinates.

--
264175192  by lzc:

    Update model_fn to only read hparams if it is not None.

--
264159328  by Zhichao Lu:

    Modify nearest neighbor upsampling to eliminate a multiply operation. For quantized models, the multiply operation gets unnecessarily quantized and reduces accuracy (simple stacking would work in place of the broadcast op which doesn't require quantization). Also removes an unnecessary reshape op.

--
263668306  by Zhichao Lu:

    Add the option to use dynamic map_fn for batch NMS

--
263031163  by Zhichao Lu:

    Mark outside compilation for NMS as optional.

--
263024916  by Zhichao Lu:

    Add an ExperimentalModel meta arch for experimenting with new model types.

--
262655894  by Zhichao Lu:

    Add the center heatmap target assigner for CenterNet

--
262431036  by Zhichao Lu:

    Adding add_eval_dict to allow for evaluation on model_v2

--
262035351  by ronnyvotel:

    Removing any non-Tensor predictions from the third stage of Mask R-CNN.

--
261953416  by Zhichao Lu:

    Internal change.

--
261834966  by Zhichao Lu:

    Fix the NMS OOM issue on TPU by forcing NMS to run outside of TPU.

--
261775941  by Zhichao Lu:

    Make Keras InputLayer compatible with both TF 1.x and TF 2.0.

--
261775633  by Zhichao Lu:

    Visualize additional channels with ground-truth bounding boxes.

--
261768117  by lzc:

    Internal change.

--
261766773  by ronnyvotel:

    Exposing `return_raw_detections_during_predict` in Faster R-CNN Proto.

--
260975089  by ronnyvotel:

    Moving calculation of batched prediction tensor names after all tensors in prediction dictionary are created.

--
259816913  by ronnyvotel:

    Adding raw detection boxes and feature map indices to SSD

--
259791955  by Zhichao Lu:

    Added a flag to control the use partitioned_non_max_suppression.

--
259580475  by Zhichao Lu:

    Tweak quantization-aware training re-writer to support NasFpn model architecture.

--
259579943  by rathodv:

    Add a meta target assigner proto and builders in OD API.

--
259577741  by Zhichao Lu:

    Internal change.

--
259366315  by lzc:

    Internal change.

--
259344310  by ronnyvotel:

    Updating faster rcnn so that raw_detection_boxes from predict() are in normalized coordinates.

--
259338670  by Zhichao Lu:

    Add support for use_native_resize_op to more feature extractors. Use dynamic shapes when static shapes are not available.

--
259083543  by ronnyvotel:

    Updating/fixing documentation.

--
259078937  by rathodv:

    Add prediction fields for tensors returned from detection_model.predict.

--
259044601  by Zhichao Lu:

    Add protocol buffer and builders for temperature scaling calibration.

--
259036770  by lzc:

    Internal changes.

--
259006223  by ronnyvotel:

    Adding detection anchor indices to Faster R-CNN Config. This is useful when one wishes to associate final detections and the anchors (or pre-nms boxes) from which they originated.

--
258872501  by Zhichao Lu:

    Run the training pipeline of ssd + resnet_v1_50 + fpn with a checkpoint.

--
258840686  by ronnyvotel:

    Adding standard outputs to DetectionModel.predict(). This CL only updates Faster R-CNN. Other meta architectures will be updated in future CLs.

--
258672969  by lzc:

    Internal change.

--
258649494  by lzc:

    Internal changes.

--
258630321  by ronnyvotel:

    Fixing documentation in shape_utils.flatten_dimensions().

--
258468145  by Zhichao Lu:

    Add additional output tensors parameter to Postprocess op.

--
258099219  by Zhichao Lu:

    Internal changes

--

PiperOrigin-RevId: 274959989

250447559  by Zhichao Lu:

    Update expected files format for Instance Segmentation challenge:
    - add fields ImageWidth, ImageHeight and store the values per prediction
    - as mask, store only encoded image and assume its size is ImageWidth x ImageHeight

--
250402780  by rathodv:

    Fix failing Mask R-CNN TPU convergence test.

    Cast second stage prediction tensors from bfloat16 to float32 to prevent errors in third target assignment (Mask Prediction) - Concat with different types bfloat16 and bfloat32 isn't allowed.

--
250300240  by Zhichao Lu:

    Addion Open Images Challenge 2019 object detection and instance segmentation
    support into Estimator framework.

--
249944839  by rathodv:

    Modify exporter.py to add multiclass score nodes in exported inference graphs.

--
249935201  by rathodv:

    Modify postprocess methods to preserve multiclass scores after non max suppression.

--
249878079  by Zhichao Lu:

    This CL slightly refactors some Object Detection helper functions for data creation, evaluation, and groundtruth providing.

    This will allow the eager+function custom loops to share code with the existing estimator training loops.

    Concretely we make the following changes:
    1. In input creation we separate dataset-creation into top-level helpers, and allow it to optionally accept a pre-constructed model directly instead of always creating a model from the config just for feature preprocessing.

    2. In coco evaluation we split the update_op creation into its own function, which the custom loops will call directly.

    3. In model_lib we move groundtruth providing/ datastructure munging into a helper function

    4. For now we put an escape hatch in `_summarize_target_assignment` when executing in tf v2.0 behavior because the summary apis used only work w/ tf 1.x

--
249673507  by rathodv:

    Use explicit casts instead of tf.to_float and tf.to_int32 to avoid warnings.

--
249656006  by Zhichao Lu:

    Add named "raw_keypoint_locations" node that corresponds with the "raw_box_locations" node.

--
249651674  by rathodv:

    Keep proposal boxes in float format. MatMulCropAndResize can handle the type even when feature themselves are bfloat16s.

--
249568633  by rathodv:

    Support q > 1 in class agnostic NMS.
    Break post_processing_test.py into 3 separate files to avoid linter errors.

--
249535530  by rathodv:

    Update some deprecated arguments to tf ops.

--
249368223  by rathodv:

    Modify MatMulCropAndResize to use MultiLevelRoIAlign method and move the tests to spatial_transform_ops.py module.

    This cl establishes that CropAndResize and RoIAlign are equivalent and only differ in the sampling point grid within the boxes. CropAndResize uses a uniform size x size point grid such that the corner points exactly overlap box corners, while RoiAlign divides boxes into size x size cells and uses their centers as sampling points. In this cl, we switch MatMulCropAndResize to use the MultiLevelRoIAlign implementation with `align_corner` option as MultiLevelRoIAlign implementation is more memory efficient on TPU when compared to the original MatMulCropAndResize.

--
249337338  by chowdhery:

    Add class-agnostic non-max-suppression in post_processing

--
249139196  by Zhichao Lu:

    Fix positional argument bug in export_tflite_ssd_graph

--
249120219  by Zhichao Lu:

    Add evaluator for computing precision limited to a given recall range.

--
249030593  by Zhichao Lu:

    Evaluation util to run segmentation and detection challenge evaluation.

--
248554358  by Zhichao Lu:

    This change contains the auxiliary changes required for TF 2.0 style training with eager+functions+dist strat loops, but not the loops themselves.

    It includes:
    - Updates to shape usage to support both tensorshape v1 and tensorshape v2
    - A fix to FreezableBatchNorm to not override the `training` arg in call when `None` was passed to the constructor (Not an issue in the estimator loops but it was in the custom loops)
    - Puts some constants in init_scope so they work in eager + functions
    - Makes learning rate schedules return a callable in eager mode (required so they update when the global_step changes)
    - Makes DetectionModel a tf.module so it tracks variables (e.g. ones nested in layers)
    - Removes some references to `op.name` for some losses and replaces it w/ explicit names
    - A small part of the change to allow the coco evaluation metrics to work in eager mode

--
248271226  by rathodv:

    Add MultiLevel RoIAlign op.

--
248229103  by rathodv:

    Add functions to 1. pad features maps 2. ravel 5-D indices

--
248206769  by rathodv:

    Add utilities needed to introduce RoI Align op.

--
248177733  by pengchong:

    Internal changes

--
247742582  by Zhichao Lu:

    Open Images Challenge 2019 instance segmentation metric: part 2

--
247525401  by Zhichao Lu:

    Update comments on max_class_per_detection.

--
247520753  by rathodv:

    Add multilevel crop and resize operation that builds on top of matmul_crop_and_resize.

--
247391600  by Zhichao Lu:

    Open Images Challenge 2019 instance segmentation metric

--
247325813  by chowdhery:

    Quantized MobileNet v2 SSD FPNLite config with depth multiplier 0.75

--

PiperOrigin-RevId: 250447559

214018767  by Zhichao Lu:

    Add original_image_spatial_shape tensor in input dictionary to store shape of the original input image

--
213914693  by lzc:

    Internal change.

--
213872175  by Zhichao Lu:

    This CL adds a Keras-based mobilenet_v2 feature extractor for object detection models.

    As part of this CL, we use the Keras mobilenet_v2 application's keyword argument layer injection API to allow the generated network to support the object detection hyperparameters.

--
213848499  by Zhichao Lu:

    Replace tf.image.resize_nearest_neighbor with tf.image.resize_images. tf.image.resize_nearest_neighbor only supports 4-D tensors but masks is a 3-D tensor.

--
213758622  by lzc:

    Internal change.

--

PiperOrigin-RevId: 214018767

Release iNaturalist Species-trained models, refactor of evaluation, box predictor for object detection. (#5289)

* Merged commit includes the following changes:
212389173  by Zhichao Lu:

    1. Replace tf.boolean_mask with tf.where

--
212282646  by Zhichao Lu:

    1. Fix a typo in model_builder.py and add a test to cover it.

--
212142989  by Zhichao Lu:

    Only resize masks in meta architecture if it has not already been resized in the input pipeline.

--
212136935  by Zhichao Lu:

    Choose matmul or native crop_and_resize in the model builder instead of faster r-cnn meta architecture.

--
211907984  by Zhichao Lu:

    Make eval input reader repeated field and update config util to handle this field.

--
211858098  by Zhichao Lu:

    Change the implementation of merge_boxes_with_multiple_labels.

--
211843915  by Zhichao Lu:

    Add Mobilenet v2 + FPN support.

--
211655076  by Zhichao Lu:

    Bug fix for generic keys in config overrides

    In generic configuration overrides, we had a duplicate entry for train_input_config and we were missing the eval_input_config and eval_config.

    This change also introduces testing for all config overrides.

--
211157501  by Zhichao Lu:

    Make the locally-modified conv defs a copy.

    So that it doesn't modify MobileNet conv defs globally for other code that
    transitively imports this package.

--
211112813  by Zhichao Lu:

    Refactoring visualization tools for Estimator's eval_metric_ops. This will make it easier for future models to take advantage of a single interface and mechanics.

--
211109571  by Zhichao Lu:

    A test decorator.

--
210747685  by Zhichao Lu:

    For FPN, when use_depthwise is set to true, use slightly modified mobilenet v1 config.

--
210723882  by Zhichao Lu:

    Integrating the losses mask into the meta architectures. When providing groundtruth, one can optionally specify annotation information (i.e. which images are labeled vs. unlabeled). For any image that is unlabeled, there is no loss accumulation.

--
210673675  by Zhichao Lu:

    Internal change.

--
210546590  by Zhichao Lu:

    Internal change.

--
210529752  by Zhichao Lu:

    Support batched inputs with ops.matmul_crop_and_resize.

    With this change the new inputs are images of shape [batch, heigh, width, depth] and boxes of shape [batch, num_boxes, 4]. The output tensor is of the shape [batch, num_boxes, crop_height, crop_width, depth].

--
210485912  by Zhichao Lu:

    Fix TensorFlow version check in object_detection_tutorial.ipynb

--
210484076  by Zhichao Lu:

    Reduce TPU memory required for single image matmul_crop_and_resize.

    Using tf.einsum eliminates intermediate tensors, tiling and expansion. for an image of size [40, 40, 1024] and boxes of shape [300, 4] HBM memory usage goes down from 3.52G to 1.67G.

--
210468361  by Zhichao Lu:

    Remove PositiveAnchorLossCDF/NegativeAnchorLossCDF to resolve "Main thread is not in main loop error" issue in local training.

--
210100253  by Zhichao Lu:

    Pooling pyramid feature maps: add option to replace max pool with convolution layers.

--
209995842  by Zhichao Lu:

    Fix a bug which prevents variable sharing in Faster RCNN.

--
209965526  by Zhichao Lu:

    Add support for enabling export_to_tpu through the estimator.

--
209946440  by Zhichao Lu:

    Replace deprecated tf.train.Supervisor with tf.train.MonitoredSession. MonitoredSession also takes away the hassle of starting queue runners.

--
209888003  by Zhichao Lu:

    Implement function to handle data where source_id is not set.

    If the field source_id is found to be the empty string for any image during runtime, it will be replaced with a random string. This avoids hash-collisions on dataset where many examples do not have source_id set. Those hash-collisions have unintended site effects and may lead to bugs in the detection pipeline.

--
209842134  by Zhichao Lu:

    Converting loss mask into multiplier, rather than using it as a boolean mask (which changes tensor shape). This is necessary, since other utilities (e.g. hard example miner) require a loss matrix with the same dimensions as the original prediction tensor.

--
209768066  by Zhichao Lu:

    Adding ability to remove loss computation from specific images in a batch, via an optional boolean mask.

--
209722556  by Zhichao Lu:

    Remove dead code.

    (_USE_C_API was flipped to True by default in TensorFlow 1.8)

--
209701861  by Zhichao Lu:

    This CL cleans-up some tf.Example creation snippets, by reusing the convenient tf.train.Feature building functions in dataset_util.

--
209697893  by Zhichao Lu:

    Do not overwrite num_epoch for eval input. This leads to errors in some cases.

--
209694652  by Zhichao Lu:

    Sample boxes by jittering around the currently given boxes.

--
209550300  by Zhichao Lu:

    `create_category_index_from_labelmap()` function now accepts `use_display_name` parameter.
    Also added create_categories_from_labelmap function for convenience

--
209490273  by Zhichao Lu:

    Check result_dict type before accessing image_id via key.

--
209442529  by Zhichao Lu:

    Introducing the capability to sample examples for evaluation. This makes it easy to specify one full epoch of evaluation, or a subset (e.g. sample 1 of every N examples).

--
208941150  by Zhichao Lu:

    Adding the capability of exporting the results in json format.

--
208888798  by Zhichao Lu:

    Fixes wrong dictionary key for num_det_boxes_per_image.

--
208873549  by Zhichao Lu:

    Reduce the number of HLO ops created by matmul_crop_and_resize.

    Do not unroll along the channels dimension. Instead, transpose the input image dimensions, apply tf.matmul and transpose back.

    The number of HLO instructions for 1024 channels reduce from 12368 to 110.

--
208844315  by Zhichao Lu:

    Add an option to use tf.non_maximal_supression_padded in SSD post-process

--
208731380  by Zhichao Lu:

    Add field in box_predictor config to enable mask prediction and update builders accordingly.

--
208699405  by Zhichao Lu:

    This CL creates a keras-based multi-resolution feature map extractor.

--
208557208  by Zhichao Lu:

    Add TPU tests for Faster R-CNN Meta arch.

    * Tests that two_stage_predict and total_loss tests run successfully on TPU.
    * Small mods to multiclass_non_max_suppression to preserve static shapes.

--
208499278  by Zhichao Lu:

    This CL makes sure the Keras convolutional box predictor & head layers apply activation layers *after* normalization (as opposed to before).

--
208391694  by Zhichao Lu:

    Updating visualization tool to produce multiple evaluation images.

--
208275961  by Zhichao Lu:

    This CL adds a Keras version of the Convolutional Box Predictor, as well as more general infrastructure for making Keras Prediction heads & Keras box predictors.

--
208275585  by Zhichao Lu:

    This CL enables the Keras layer hyperparameter object to build a dedicated activation layer, and to disable activation by default in the op layer construction kwargs.

    This is necessary because in most cases the normalization layer must be applied before the activation layer. So, in Keras models we must set the convolution activation in a dedicated layer after normalization is applied, rather than setting it in the convolution layer construction args.

--
208263792  by Zhichao Lu:

    Add a new SSD mask meta arch that can predict masks for SSD models.
    Changes including:
     - overwrite loss function to add mask loss computation.
     - update ssd_meta_arch to handle masks if predicted in predict and postprocessing.

--
208000218  by Zhichao Lu:

    Make FasterRCNN choose static shape operations only in training mode.

--
207997797  by Zhichao Lu:

    Add static boolean_mask op to box_list_ops.py and use that in faster_rcnn_meta_arch.py to support use_static_shapes option.

--
207993460  by Zhichao Lu:

    Include FGVC detection models in model zoo.

--
207971213  by Zhichao Lu:

    remove the restriction to run tf.nn.top_k op on CPU

--
207961187  by Zhichao Lu:

    Build the first stage NMS function in the model builder and pass it to FasterRCNN meta arch.

--
207960608  by Zhichao Lu:

    Internal Change.

--
207927015  by Zhichao Lu:

    Have an option to use the TPU compatible NMS op cl/206673787, in the batch_multiclass_non_max_suppression function. On setting pad_to_max_output_size to true, the output nmsed boxes are padded to be of length max_size_per_class.

    This can be used in first stage Region Proposal Network in FasterRCNN model by setting the first_stage_nms_pad_to_max_proposals field to true in config proto.

--
207809668  by Zhichao Lu:

    Add option to use depthwise separable conv instead of conv2d in FPN and WeightSharedBoxPredictor. More specifically, there are two related configs:
    - SsdFeatureExtractor.use_depthwise
    - WeightSharedConvolutionalBoxPredictor.use_depthwise

--
207808651  by Zhichao Lu:

    Fix the static balanced positive negative sampler's TPU tests

--
207798658  by Zhichao Lu:

    Fixes a post-refactoring bug where the pre-prediction convolution layers in the convolutional box predictor are ignored.

--
207796470  by Zhichao Lu:

    Make slim endpoints visible in FasterRCNNMetaArch.

--
207787053  by Zhichao Lu:

    Refactor ssd_meta_arch so that the target assigner instance is passed into the SSDMetaArch constructor rather than constructed inside.

--

PiperOrigin-RevId: 212389173

* Fix detection model zoo typo.

* Modify tf example decoder to handle label maps with either `display_name` or `name` fields seamlessly.

Currently, tf example decoder uses only `name` field to look up ids for class text field present in the data. This change uses both `display_name` and `name` fields in the label map to fetch ids for class text.

PiperOrigin-RevId: 212672223

* Modify create_coco_tf_record tool to write out class text instead of class labels.

PiperOrigin-RevId: 212679112

* Fix detection model zoo typo.

PiperOrigin-RevId: 212715692

* Adding the following two optional flags to WeightSharedConvolutionalBoxHead:
1) In the box head, apply clipping to box encodings in the box head.
2) In the class head, apply sigmoid to class predictions at inference time.

PiperOrigin-RevId: 212723242

* Support class confidences in merge boxes with multiple labels.

PiperOrigin-RevId: 212884998

* Creates multiple eval specs for object detection.

PiperOrigin-RevId: 212894556

* Set batch_norm on last layer in Mask Head to None.

PiperOrigin-RevId: 213030087

* Enable bfloat16 training for object detection models.

PiperOrigin-RevId: 213053547

* Skip padding op when unnecessary.

PiperOrigin-RevId: 213065869

* Modify `Matchers` to use groundtruth weights before performing matching.

Groundtruth weights tensor is used to indicate padding in groundtruth box tensor. It is handled in `TargetAssigner` by creating appropriate classification and regression target weights based on the groundtruth box each anchor matches to. However, options such as `force_match_all_rows` in `ArgmaxMatcher` force certain anchors to match to groundtruth boxes that are just paddings thereby reducing the number of anchors that could otherwise match to real groundtruth boxes.

For single stage models like SSD the effect of this is negligible as there are two orders of magnitude more anchors than the number of padded groundtruth boxes. But for Faster R-CNN and Mask R-CNN where there are only 300 anchors in the second stage, a significant number of these match to groundtruth paddings reducing the number of anchors regressing to real groundtruth boxes degrading the performance severely.

Therefore, this change introduces an additional boolean argument `valid_rows` to `Matcher.match` methods and the implementations now ignore such padded groudtruth boxes during matching.

PiperOrigin-RevId: 213345395

* Add release note for iNaturalist Species trained models.

PiperOrigin-RevId: 213347179

* Fix the bug of uninitialized gt_is_crowd_list variable.

PiperOrigin-RevId: 213364858

* ...text exposed to open source public git repo...

PiperOrigin-RevId: 213554260

196161788  by Zhichao Lu:

    Add eval_on_train_steps parameter.

    Since the number of samples in train dataset is usually different to the number of samples in the eval dataset.

--
196151742  by Zhichao Lu:

    Add an optional random sampling process for SSD meta arch and update mean stddev coder to use default std dev when corresponding tensor is not added to boxlist field.

--
196148940  by Zhichao Lu:

    Release ssdlite mobilenet v2 coco trained model.

--
196058528  by Zhichao Lu:

    Apply FPN feature map generation before we add additional layers on top of resnet feature extractor.

--
195818367  by Zhichao Lu:

    Add support for exporting detection keypoints.

--
195745420  by Zhichao Lu:

    Introduce include_metrics_per_category option to Object Detection eval_config.

--
195734733  by Zhichao Lu:

    Rename SSDLite config to be more explicit.

--
195717383  by Zhichao Lu:

    Add quantized training to object_detection.

--
195683542  by Zhichao Lu:

    Fix documentation for the interaction of fine_tune_checkpoint_type and load_all_detection_checkpoint_vars interaction.

--
195668233  by Zhichao Lu:

    Using batch size from params dictionary if present.

--
195570173  by Zhichao Lu:

    A few fixes to get new estimator API eval to match legacy detection eval binary by (1) plumbing `is_crowd` annotations through to COCO evaluator, (2) setting the `sloppy` flag in tf.contrib.data.parallel_interleave based on whether shuffling is enabled, and (3) saving the original image instead of the resized original image, which allows for small/medium/large mAP metrics to be properly computed.

--
195316756  by Zhichao Lu:

    Internal change

--

PiperOrigin-RevId: 196161788

Enabling both train and eval image summaries. Note that eval summaries are not created tf-learn environment. To get them to show up, added the summary image into the eval_metric_ops.

PiperOrigin-RevId: 189658259

184048729  by Zhichao Lu:

    Modify target_assigner so that it creates regression targets taking keypoints into account.

--
184027183  by Zhichao Lu:

    Resnet V1 FPN based feature extractors for SSD meta architecture in Object Detection V2 API.

--
184004730  by Zhichao Lu:

    Expose a lever to override the configured mask_type.

--
183933113  by Zhichao Lu:

    Weight shared convolutional box predictor as described in https://arxiv.org/abs/1708.02002

--
183929669  by Zhichao Lu:

    Expanding box list operations for future data augmentations.

--
183916792  by Zhichao Lu:

    Fix unrecognized assertion function in tests.

--
183906851  by Zhichao Lu:

    - Change ssd meta architecture to use regression weights to compute loss normalizer.

--
183871003  by Zhichao Lu:

    Fix config_util_test wrong dependency.

--
183782120  by Zhichao Lu:

    Add __init__ file to third_party directories.

--
183779109  by Zhichao Lu:

    Setup regular version sync.

--
183768772  by Zhichao Lu:

    Make test compatible with numpy 1.12 and higher

--
183767893  by Zhichao Lu:

    Make test compatible with numpy 1.12 and higher

--
183719318  by Zhichao Lu:

    Use the new test interface in ssd feature extractor.

--
183714671  by Zhichao Lu:

    Use the new test_case interface for all anchor generators.

--
183708155  by Zhichao Lu:

    Change variable scopes in ConvolutionalBoxPredictor such that previously trained checkpoints are still compatible after the change in BoxPredictor interface

--
183705798  by Zhichao Lu:

    Internal change.

--
183636023  by Zhichao Lu:

    Fixing argument name for np_box_list_ops.concatenate() function.

--
183490404  by Zhichao Lu:

    Make sure code that relies in SSD older code still works.

--
183426762  by Zhichao Lu:

    Internal change

183412315  by Zhichao Lu:

    Internal change

183337814  by Zhichao Lu:

    Internal change

183303933  by Zhichao Lu:

    Internal change

183257349  by Zhichao Lu:

    Internal change

183254447  by Zhichao Lu:

    Internal change

183251200  by Zhichao Lu:

    Internal change

183135002  by Zhichao Lu:

    Internal change

182851500  by Zhichao Lu:

    Internal change

182839607  by Zhichao Lu:

    Internal change

182830719  by Zhichao Lu:

    Internal change

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    Internal change

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    https://github.com/tensorflow/models/issues/2530
    https://github.com/tensorflow/models/issues/2534

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PiperOrigin-RevId: 184048729

For details see our paper:
"Speed/accuracy trade-offs for modern convolutional object detectors."
Huang J, Rathod V, Sun C, Zhu M, Korattikara A, Fathi A, Fischer I,
Wojna Z, Song Y, Guadarrama S, Murphy K, CVPR 2017
https://arxiv.org/abs/1611.10012