GitLab

310447280  by lzc:

    Internal change

310420845  by Zhichao Lu:

    Open source the internal Context RCNN code.

--
310362339  by Zhichao Lu:

    Internal change

310259448  by lzc:

    Update required TF version for OD API.

--
310252159  by Zhichao Lu:

    Port patch_ops_test to TF1/TF2 as TPUs.

--
310247180  by Zhichao Lu:

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

--
310178294  by Zhichao Lu:

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

--
310094222  by lzc:

    Internal changes.

--
310085250  by lzc:

    Internal Change.

--
310016447  by huizhongc:

    Remove unrecognized classes from labeled_classes.

--
310009470  by rathodv:

    Mark batcher.py as TF1 only.

--
310001984  by rathodv:

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

--
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.

--
309425881  by Zhichao Lu:

    Make TF1/TF2 optimizer builder tests explicit.

--
309408646  by Zhichao Lu:

    Make dataset builder tests TF1 and TF2 compatible.

--
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.

--
309125076  by Zhichao Lu:

    Convert target_assigner_utils to TF1/TF2.

--
308966359  by huizhongc:

    Support SSD training with partially labeled groundtruth.

--
308937159  by rathodv:

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

--
308774302  by Zhichao Lu:

    Internal

--
308732860  by rathodv:

    Make core/prefetcher.py  compatible with TF1 only.

--
308726984  by rathodv:

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

--
308714718  by rathodv:

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

--
308707960  by rathodv:

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

--
308700595  by rathodv:

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

--
308361472  by rathodv:

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

--
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.

--
308256924  by rathodv:

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

--
308256826  by rathodv:

    Update class_agnostic_nms_test.py to be TF1/TF2 compatible.

--
308256112  by rathodv:

    Update box_list_ops_test.py to be TF1/TF2 compatible.

--
308159360  by Zhichao Lu:

    Internal change

308145008  by Zhichao Lu:

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

--
307651875  by rathodv:

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

--
307651798  by rathodv:

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

--
307651652  by rathodv:

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

--
307651571  by rathodv:

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

--
307651480  by rathodv:

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

--
307651409  by rathodv:

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

--
307651314  by rathodv:

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

--
307092053  by Zhichao Lu:

    Use manager to save checkpoint.

--
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).

--
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.

--
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))

--
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.

--
306731223  by jonathanhuang:

    Internal change.

--
306549183  by rathodv:

    Internal Update.

--
306542930  by rathodv:

    Internal Update

--
306322697  by rathodv:

    Internal.

--
305345036  by Zhichao Lu:

    Adding COCO Camera Traps Json to tf.Example beam code

--
304104869  by lzc:

    Internal changes.

--
304068971  by jonathanhuang:

    Internal change.

--
304050469  by Zhichao Lu:

    Internal change.

--
303880642  by huizhongc:

    Support parsing partially labeled groundtruth.

--
303841743  by Zhichao Lu:

    Deprecate nms_on_host in SSDMetaArch.

--
303803204  by rathodv:

    Internal change.

--
303793895  by jonathanhuang:

    Internal change.

--
303467631  by rathodv:

    Py3 update for detection inference test.

--
303444542  by rathodv:

    Py3 update to metrics module

--
303421960  by rathodv:

    Update json_utils to python3.

--
302787583  by ronnyvotel:

    Coco results generator for submission to the coco test server.

--
302719091  by Zhichao Lu:

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

--
302116230  by Zhichao Lu:

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

--
301888316  by Zhichao Lu:

    Fix checkpoint_filepath not defined error.

--
301840312  by ronnyvotel:

    Adding keypoint_scores to visualizations.

--
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.

--
301532344  by Zhichao Lu:

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

--
301480348  by ronnyvotel:

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

--
301454018  by Zhichao Lu:

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

--
301317527  by Zhichao Lu:

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

--
301300324  by Zhichao Lu:

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

--
301297115  by ronnyvotel:

    Utility function for setting keypoint visibilities based on keypoint coordinates.

--
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.

--
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.

--
300836556  by Zhichao Lu:

    Internal changes to add keypoint estimation parameters in CenterNet proto.

--
300795208  by Zhichao Lu:

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

--
299474766  by Zhichao Lu:

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

--
299453920  by Zhichao Lu:

    Add swish activation as a hyperperams option.

--
299240093  by ronnyvotel:

    Keypoint postprocessing for CenterNetMetaArch.

--
299176395  by Zhichao Lu:

    Internal change.

--
299135608  by Zhichao Lu:

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

--
298915482  by Zhichao Lu:

    Make dataset_builder aware of input_context for distributed training.

--
298713595  by Zhichao Lu:

    Handling data with negative size boxes.

--
298695964  by Zhichao Lu:

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

--
298492150  by Zhichao Lu:

    Rename optimizer_builder_test_v2.py -> optimizer_builder_v2_test.py

--
298476471  by Zhichao Lu:

    Internal changes to support CenterNet keypoint estimation.

--
298365851  by ronnyvotel:

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

--
297843700  by Zhichao Lu:

    Internal change.

--
297706988  by lzc:

    Internal change.

--
297705287  by ronnyvotel:

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

--
297700447  by Zhichao Lu:

    Improve checkpoint checking logic with TF2 loop.

--
297686094  by Zhichao Lu:

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

--
297670468  by lzc:

    Internal change.

--
297241327  by Zhichao Lu:

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

--
297205959  by Zhichao Lu:

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

--
297143806  by Zhichao Lu:

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

--
297129625  by Zhichao Lu:

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

--
297117070  by Zhichao Lu:

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

--
297030190  by Zhichao Lu:

    Add configuration options for visualizing keypoint edges

--
296359649  by Zhichao Lu:

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

--
296290582  by Zhichao Lu:

    Internal change.

--
296093857  by Zhichao Lu:

    Internal changes to add general target assigner utilities.

--
295975116  by Zhichao Lu:

    Fix visualize_boxes_and_labels_on_image_array to show max_boxes_to_draw correctly.

--
295819711  by Zhichao Lu:

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

--
295811929  by Zhichao Lu:

    Keypoint support in random_square_crop_by_scale.

--
295788458  by rathodv:

    Remove unused checkpoint to reduce repo size on github

--
295787184  by Zhichao Lu:

    Enable visualization of edges between keypoints

--
295763508  by Zhichao Lu:

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

--
295605344  by Zhichao Lu:

    internal change.

--
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.

--
294829061  by lzc:

    Internal change.

--
294566503  by Zhichao Lu:

    Changed internal CenterNet Model configuration.

--
294346662  by ronnyvotel:

    Using NaN values in keypoint coordinates that are not visible.

--
294333339  by Zhichao Lu:

    Change experimetna_distribute_dataset -> experimental_distribute_dataset_from_function

--
293928752  by Zhichao Lu:

    Internal change

--
293909384  by Zhichao Lu:

    Add capabilities to train 1024x1024 CenterNet models.

--
293637554  by ronnyvotel:

    Adding keypoint visibilities to TfExampleDecoder.

--
293501558  by lzc:

    Internal change.

--
293252851  by Zhichao Lu:

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

--
292730217  by Zhichao Lu:

    Internal change.

--
292456563  by lzc:

    Internal changes.

--
292355612  by Zhichao Lu:

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

--
292245265  by rathodv:

    Internal

--
291989323  by richardmunoz:

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

--
291950147  by Zhichao Lu:

    Flip bounding boxes in arbitrary shaped tensors.

--
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.

--
291298871  by Zhichao Lu:

    Py3 compatibility changes.

--
290957957  by Zhichao Lu:

    Hourglass feature extractor for CenterNet.

--
290564372  by Zhichao Lu:

    Internal change.

--
290155278  by rathodv:

    Remove Dataset Explorer.

--
290155153  by Zhichao Lu:

    Internal change

--
290122054  by Zhichao Lu:

    Unify the format in the faster_rcnn.proto

--
290116084  by Zhichao Lu:

    Deprecate tensorflow.contrib.

--
290100672  by Zhichao Lu:

    Update MobilenetV3 SSD candidates

--
289926392  by Zhichao Lu:

    Internal change

--
289553440  by Zhichao Lu:

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

--
288994128  by lzc:

    Internal changes.

--
288942194  by lzc:

    Internal change.

--
288746124  by Zhichao Lu:

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

--
288552509  by rathodv:

    Internal.

--
288541285  by rathodv:

    Internal update.

--
288396396  by Zhichao Lu:

    Make object detection import contrib explicitly

--
288255791  by rathodv:

    Internal

--
288078600  by Zhichao Lu:

    Fix model_lib_v2 test

--
287952244  by rathodv:

    Internal

--
287921774  by Zhichao Lu:

    internal change

--
287906173  by Zhichao Lu:

    internal change

--
287889407  by jonathanhuang:

    PY3 compatibility

--
287889042  by rathodv:

    Internal

--
287876178  by Zhichao Lu:

    Internal change.

--
287770490  by Zhichao Lu:

    Add CenterNet proto and builder

--
287694213  by Zhichao Lu:

    Support for running multiple steps per tf.function call.

--
287377183  by jonathanhuang:

    PY3 compatibility

--
287371344  by rathodv:

    Support loading keypoint labels and ids.

--
287368213  by rathodv:

    Add protos supporting keypoint evaluation.

--
286673200  by rathodv:

    dataset_tools PY3 migration

--
286635106  by Zhichao Lu:

    Update code for upcoming tf.contrib removal

--
286479439  by Zhichao Lu:

    Internal change

--
286311711  by Zhichao Lu:

    Skeleton of context model within TFODAPI

--
286005546  by Zhichao Lu:

    Fix Faster-RCNN training when using keep_aspect_ratio_resizer with pad_to_max_dimension

--
285906400  by derekjchow:

    Internal change

--
285822795  by Zhichao Lu:

    Add CenterNet meta arch target assigners.

--
285447238  by Zhichao Lu:

    Internal changes.

--
285016927  by Zhichao Lu:

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

--
284827274  by Zhichao Lu:

    Convert to python 3.

--
284645593  by rathodv:

    Internal change

--
284639893  by rathodv:

    Add missing documentation for keypoints in eval_util.py.

--
284323712  by Zhichao Lu:

    Internal changes.

--
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

--
284226821  by derekjchow:

    Update exporter.

--
284211030  by Zhichao Lu:

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

--
284190451  by Zhichao Lu:

    Add support for CenterNet losses in protos and builders.

--
284093961  by lzc:

    Internal changes.

--
284028174  by Zhichao Lu:

    Internal change

--
284014719  by derekjchow:

    Do not pad top_down feature maps unnecessarily.

--
284005765  by Zhichao Lu:

    Add new pad_to_multiple_resizer

--
283858233  by Zhichao Lu:

    Make target assigner work when under tf.function.

--
283836611  by Zhichao Lu:

    Make config getters more general.

--
283808990  by Zhichao Lu:

    Internal change

--
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.

--
280298212  by Zhichao Lu:

    Add backwards compatible change

--
280237857  by Zhichao Lu:

    internal change

--

PiperOrigin-RevId: 310447280

* 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

257914648  by lzc:

    Internal changes

--
257525973  by Zhichao Lu:

    Fixes bug that silently prevents checkpoints from loading when training w/ eager + functions. Also sets up scripts to run training.

--
257296614  by Zhichao Lu:

    Adding detection_features to model outputs

--
257234565  by Zhichao Lu:

    Fix wrong order of `classes_with_max_scores` in class-agnostic NMS caused by
    sorting in partitioned-NMS.

--
257232002  by ronnyvotel:

    Supporting `filter_nonoverlapping` option in np_box_list_ops.clip_to_window().

--
257198282  by Zhichao Lu:

    Adding the focal loss and l1 loss from the Objects as Points paper.

--
257089535  by Zhichao Lu:

    Create Keras based ssd + resnetv1 + fpn.

--
257087407  by Zhichao Lu:

    Make object_detection/data_decoders Python3-compatible.

--
257004582  by Zhichao Lu:

    Updates _decode_raw_data_into_masks_and_boxes to the latest binary masks-to-string encoding format.

--
257002124  by Zhichao Lu:

    Make object_detection/utils Python3-compatible, except json_utils.

    The patching trick used in json_utils is not going to work in Python 3.

--
256795056  by lzc:

    Add a detection_anchor_indices field to detection outputs.

--
256477542  by Zhichao Lu:

    Make object_detection/core Python3-compatible.

--
256387593  by Zhichao Lu:

    Edit class_id_function_approximations builder to skip class ids not present in label map.

--
256259039  by Zhichao Lu:

    Move NMS to TPU for FasterRCNN.

--
256071360  by rathodv:

    When multiclass_scores is empty, add one-hot encoding of groundtruth_classes as multiclass scores so that data_augmentation ops that expect the presence of multiclass_scores don't have to individually handle this case.

    Also copy input tensor_dict to out_tensor_dict first to avoid inplace modification.

--
256023645  by Zhichao Lu:

    Adds the first WIP iterations of TensorFlow v2 eager + functions style custom training & evaluation loops.

--
255980623  by Zhichao Lu:

    Adds a new data augmentation operation "remap_labels" which remaps a set of labels to a new label.

--
255753259  by Zhichao Lu:

    Announcement of the released evaluation tutorial for Open Images Challenge
    2019.

--
255698776  by lzc:

    Fix rewrite_nn_resize_op function which was broken by tf forward compatibility movement.

--
255623150  by Zhichao Lu:

    Add Keras-based ResnetV1 models.

--
255504992  by Zhichao Lu:

    Fixing the typo in specifying label expansion for ground truth segmentation
    file.

--
255470768  by Zhichao Lu:

    1. Fixing Python bug with parsed arguments.
    2. Adding capability to parse relevant columns from CSV header.
    3. Fixing bug with duplicated labels expansion.

--
255462432  by Zhichao Lu:

    Adds a new data augmentation operation "drop_label_probabilistically" which drops a given label with the given probability. This supports experiments on training in the presence of label noise.

--
255441632  by rathodv:

    Fallback on groundtruth classes when multiclass_scores tensor is empty.

--
255434899  by Zhichao Lu:

    Ensuring evaluation binary can run even with big files by synchronizing
    processing of ground truth and predictions: in this way, ground truth is not stored but immediatly
    used for evaluation. In case gt of object masks, this allows to run
    evaluations on relatively large sets.

--
255337855  by lzc:

    Internal change.

--
255308908  by Zhichao Lu:

    Add comment to clarify usage of calibration parameters proto.

--
255266371  by Zhichao Lu:

    Ensuring correct processing of the case, when no groundtruth masks are provided
    for an image.

--
255236648  by Zhichao Lu:

    Refactor model_builder in faster_rcnn.py to a util_map, so that it's possible to be overwritten.

--
255093285  by Zhichao Lu:

    Updating capability to subsample data during evaluation

--
255081222  by rathodv:

    Convert groundtruth masks to be of type float32 before its used in the loss function.

    When using mixed precision training, masks are represented using bfloat16 tensors in the input pipeline for performance reasons. We need to convert them to float32 before using it in the loss function.

--
254788436  by Zhichao Lu:

    Add forward_compatible to non_max_suppression_with_scores to make it is
    compatible with older tensorflow version.

--
254442362  by Zhichao Lu:

    Add num_layer field to ssd feature extractor proto.

--
253911582  by jonathanhuang:

    Plumbs Soft-NMS options (using the new tf.image.non_max_suppression_with_scores op) into the TF Object Detection API.  It adds a `soft_nms_sigma` field to the postprocessing proto file and plumbs this through to both the multiclass and class_agnostic versions of NMS. Note that there is no effect on behavior of NMS when soft_nms_sigma=0 (which it is set to by default).

    See also "Soft-NMS -- Improving Object Detection With One Line of Code" by Bodla et al (https://arxiv.org/abs/1704.04503)

--
253703949  by Zhichao Lu:

    Internal test fixes.

--
253151266  by Zhichao Lu:

    Fix the op type check for FusedBatchNorm, given that we introduced
    FusedBatchNormV3 in a previous change.

--
252718956  by Zhichao Lu:

    Customize activation function to enable relu6 instead of relu for saliency
    prediction model seastarization

--
252158593  by Zhichao Lu:

    Make object_detection/core Python3-compatible.

--
252150717  by Zhichao Lu:

    Make object_detection/core Python3-compatible.

--
251967048  by Zhichao Lu:

    Make GraphRewriter proto extensible.

--
251950039  by Zhichao Lu:

    Remove experimental_export_device_assignment from TPUEstimator.export_savedmodel(), so as to remove rewrite_for_inference().

    As a replacement, export_savedmodel() V2 API supports device_assignment where user call tpu.rewrite in model_fn and pass in device_assigment there.

--
251890697  by rathodv:

    Updated docstring to include new output nodes.

--
251662894  by Zhichao Lu:

    Add autoaugment augmentation option to objection detection api codebase. This
    is an available option in preprocessor.py.

    The intended usage of autoaugment is to be done along with random flipping and
    cropping for best results.

--
251532908  by Zhichao Lu:

    Add TrainingDataType enum to track whether class-specific or agnostic data was used to fit the calibration function.

    This is useful, since classes with few observations may require a calibration function fit on all classes.

--
251511339  by Zhichao Lu:

    Add multiclass isotonic regression to the calibration builder.

--
251317769  by pengchong:

    Internal Change.

--
250729989  by Zhichao Lu:

    Fixing bug in gt statistics count in case of mask and box annotations.

--
250729627  by Zhichao Lu:

    Label expansion for segmentation.

--
250724905  by Zhichao Lu:

    Fix use_depthwise in fpn and test it with fpnlite on ssd + mobilenet v2.

--
250670379  by Zhichao Lu:

    Internal change

250630364  by lzc:

    Fix detection_model_zoo footnotes

--
250560654  by Zhichao Lu:

    Fix static shape issue in matmul_crop_and_resize.

--
250534857  by Zhichao Lu:

    Edit class agnostic calibration function docstring to more accurately describe the function's outputs.

--
250533277  by Zhichao Lu:

    Edit the multiclass messages to use class ids instead of labels.

--

PiperOrigin-RevId: 257914648

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

247226201  by ronnyvotel:

    Updating the visualization tools to accept unique_ids for color coding.

--
247067830  by Zhichao Lu:

    Add box_encodings_clip_range options for the convolutional box predictor (for TPU compatibility).

--
246888475  by Zhichao Lu:

    Remove unused _update_eval_steps function.

--
246163259  by lzc:

    Add a gather op that can handle ignore indices (which are "-1"s in this case).

--
246084944  by Zhichao Lu:

    Keras based implementation for SSD + MobilenetV2 + FPN.

--
245544227  by rathodv:

    Add batch_get_targets method to target assigner module to gather any groundtruth tensors based on the results of target assigner.

--
245540854  by rathodv:

    Update target assigner to return match tensor instead of a match object.

--
245434441  by Zhichao Lu:

    Add README for tpu_exporters package.

--
245381834  by lzc:

    Internal change.

--
245298983  by Zhichao Lu:

    Add conditional_shape_resizer to config_util

--
245134666  by Zhichao Lu:

    Adds ConditionalShapeResizer to the ImageResizer proto which enables resizing only if input image height or width is is greater or smaller than a certain size. Also enables specification of resize method in resize_to_{max, min}_dimension methods.

--
245093975  by Zhichao Lu:

    Exporting SavedModel for Object Detection TPU inference. (faster-rcnn)

--
245072421  by Zhichao Lu:

    Adds a new image resizing method "resize_to_max_dimension" which resizes images only if a dimension is greater than the maximum desired value while maintaining aspect ratio.

--
244946998  by lzc:

    Internal Changes.

--
244943693  by Zhichao Lu:

    Add a custom config to mobilenet v2 that makes it more detection friendly.

--
244754158  by derekjchow:

    Internal change.

--
244699875  by Zhichao Lu:

    Add check_range=False to box_list_ops.to_normalized_coordinates when training
    for instance segmentation.  This is consistent with other calls when training
    for object detection.  There could be wrongly annotated boxes in the dataset.

--
244507425  by rathodv:

    Support bfloat16 for ssd models.

--
244399982  by Zhichao Lu:

    Exporting SavedModel for Object Detection TPU inference. (ssd)

--
244209387  by Zhichao Lu:

    Internal change.

--
243922296  by rathodv:

    Change `raw_detection_scores` to contain softmax/sigmoid scores (not logits) for `raw_ detection_boxes`.

--
243883978  by Zhichao Lu:

    Add a sample fully conv config.

--
243369455  by Zhichao Lu:

    Fix regularization loss gap in Keras and Slim.

--
243292002  by lzc:

    Internal changes.

--
243097958  by Zhichao Lu:

    Exporting SavedModel for Object Detection TPU inference. (ssd model)

--
243007177  by Zhichao Lu:

    Exporting SavedModel for Object Detection TPU inference. (ssd model)

--
242776550  by Zhichao Lu:

    Make object detection pre-processing run on GPU.  tf.map_fn() uses
    TensorArrayV3 ops, which have no int32 GPU implementation.  Cast to int64,
    then cast back to int32.

--
242723128  by Zhichao Lu:

    Using sorted dictionaries for additional heads in non_max_suppression to ensure tensor order

--
242495311  by Zhichao Lu:

    Update documentation to reflect new TFLite examples repo location

--
242230527  by Zhichao Lu:

    Fix Dropout bugs for WeightSharedConvolutionalBoxPred.

--
242226573  by Zhichao Lu:

    Create Keras-based WeightSharedConvolutionalBoxPredictor.

--
241806074  by Zhichao Lu:

    Add inference in unit tests of TFX OD template.

--
241641498  by lzc:

    Internal change.

--
241637481  by Zhichao Lu:

    matmul_crop_and_resize(): Switch to dynamic shaping, so that not all dimensions are required to be known.

--
241429980  by Zhichao Lu:

    Internal change

--
241167237  by Zhichao Lu:

    Adds a faster_rcnn_inception_resnet_v2 Keras feature extractor, and updates the model builder to construct it.

--
241088616  by Zhichao Lu:

    Make it compatible with different dtype, e.g. float32, bfloat16, etc.

--
240897364  by lzc:

    Use image_np_expanded in object_detection_tutorial notebook.

--
240890393  by Zhichao Lu:

    Disable multicore inference for OD template as its not yet compatible.

--
240352168  by Zhichao Lu:

    Make SSDResnetV1FpnFeatureExtractor not protected to allow inheritance.

--
240351470  by lzc:

    Internal change.

--
239878928  by Zhichao Lu:

    Defines Keras box predictors for Faster RCNN and RFCN

--
239872103  by Zhichao Lu:

    Delete duplicated inputs in test.

--
239714273  by Zhichao Lu:

    Adding scope variable to all class heads

--
239698643  by Zhichao Lu:

    Create FPN feature extractor for object detection.

--
239696657  by Zhichao Lu:

    Internal Change.

--
239299404  by Zhichao Lu:

    Allows the faster rcnn meta-architecture to support Keras subcomponents

--
238502595  by Zhichao Lu:

    Lay the groundwork for symmetric quantization.

--
238496885  by Zhichao Lu:

    Add flexible_grid_anchor_generator

--
238138727  by lzc:

    Remove dead code.

    _USE_C_SHAPES has been forced True in TensorFlow releases since
    TensorFlow 1.9
    (https://github.com/tensorflow/tensorflow/commit/1d74a69443f741e69f9f52cb6bc2940b4d4ae3b7)

--
238123936  by rathodv:

    Add num_matched_groundtruth summary to target assigner in SSD.

--
238103345  by ronnyvotel:

    Raising error if input file pattern does not match any files.
    Also printing the number of evaluation images for coco metrics.

--
238044081  by Zhichao Lu:

    Fix docstring to state the correct dimensionality of `class_predictions_with_background`.

--
237920279  by Zhichao Lu:

    [XLA] Rework debug flags for dumping HLO.

    The following flags (usually passed via the XLA_FLAGS envvar) are removed:

      xla_dump_computations_to
      xla_dump_executions_to
      xla_dump_ir_to
      xla_dump_optimized_hlo_proto_to
      xla_dump_per_pass_hlo_proto_to
      xla_dump_unoptimized_hlo_proto_to
      xla_generate_hlo_graph
      xla_generate_hlo_text_to
      xla_hlo_dump_as_html
      xla_hlo_graph_path
      xla_log_hlo_text

    The following new flags are added:

      xla_dump_to
      xla_dump_hlo_module_re
      xla_dump_hlo_pass_re
      xla_dump_hlo_as_text
      xla_dump_hlo_as_proto
      xla_dump_hlo_as_dot
      xla_dump_hlo_as_url
      xla_dump_hlo_as_html
      xla_dump_ir
      xla_dump_hlo_snapshots

    The default is not to dump anything at all, but as soon as some dumping flag is
    specified, we enable the following defaults (most of which can be overridden).

     * dump to stdout (overridden by --xla_dump_to)
     * dump HLO modules at the very beginning and end of the optimization pipeline
     * don't dump between any HLO passes (overridden by --xla_dump_hlo_pass_re)
     * dump all HLO modules (overridden by --xla_dump_hlo_module_re)
     * dump in textual format (overridden by
       --xla_dump_hlo_as_{text,proto,dot,url,html}).

    For example, to dump optimized and unoptimized HLO text and protos to /tmp/foo,
    pass

      --xla_dump_to=/tmp/foo --xla_dump_hlo_as_text --xla_dump_hlo_as_proto

    For details on these flags' meanings, see xla.proto.

    The intent of this change is to make dumping both simpler to use and more
    powerful.

    For example:

     * Previously there was no way to dump the HLO module during the pass pipeline
       in HLO text format; the only option was --dump_per_pass_hlo_proto_to, which
       dumped in proto format.

       Now this is --xla_dump_pass_re=.* --xla_dump_hlo_as_text.  (In fact, the
       second flag is not necessary in this case, as dumping as text is the
       default.)

     * Previously there was no way to dump HLO as a graph before and after
       compilation; the only option was --xla_generate_hlo_graph, which would dump
       before/after every pass.

       Now this is --xla_dump_hlo_as_{dot,url,html} (depending on what format you
       want the graph in).

     * Previously, there was no coordination between the filenames written by the
       various flags, so info about one module might be dumped with various
       filename prefixes.  Now the filenames are consistent and all dumps from a
       particular module are next to each other.

    If you only specify some of these flags, we try to figure out what you wanted.
    For example:

     * --xla_dump_to implies --xla_dump_hlo_as_text unless you specify some
       other --xla_dump_as_* flag.

     * --xla_dump_hlo_as_text or --xla_dump_ir implies dumping to stdout unless you
       specify a different --xla_dump_to directory.  You can explicitly dump to
       stdout with --xla_dump_to=-.

    As part of this change, I simplified the debugging code in the HLO passes for
    dumping HLO modules.  Previously, many tests explicitly VLOG'ed the HLO module
    before, after, and sometimes during the pass.  I removed these VLOGs.  If you
    want dumps before/during/after an HLO pass, use --xla_dump_pass_re=<pass_name>.

--
237510043  by lzc:

    Internal Change.

--
237469515  by Zhichao Lu:

    Parameterize model_builder.build in inputs.py.

--
237293511  by rathodv:

    Remove multiclass_scores from tensor_dict in transform_data_fn always.

--
237260333  by ronnyvotel:

    Updating faster_rcnn_meta_arch to define prediction dictionary fields that are batched.

--

PiperOrigin-RevId: 247226201

223075771  by lzc:

    Bring in external fixes.

--
222919755  by ronnyvotel:

    Bug fix in faster r-cnn model builder. Was previously using `inplace_batchnorm_update` for `reuse_weights`.

--
222885680  by Zhichao Lu:

    Use the result_dict_for_batched_example in models_lib
    Also fixes the visualization size on when eval is on GPU

--
222883648  by Zhichao Lu:

    Fix _unmatched_class_label for the _add_background_class == False case in ssd_meta_arch.py.

--
222836663  by Zhichao Lu:

    Adding support for visualizing grayscale images. Without this change, the images are black-red instead of grayscale.

--
222501978  by Zhichao Lu:

    Fix a bug that caused convert_to_grayscale flag not to be respected.

--
222432846  by richardmunoz:

    Fix mapping of groundtruth_confidences from shape [num_boxes] to [num_boxes, num_classes] when the input contains the groundtruth_confidences field.

--
221725755  by richardmunoz:

    Internal change.

--
221458...

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

199348852  by Zhichao Lu:

    Small typos fixes in VRD evaluation.

--
199315191  by Zhichao Lu:

    Change padding shapes when additional channels are available.

--
199309180  by Zhichao Lu:

    Adds minor fixes to the Object Detection API implementation.

--
199298605  by Zhichao Lu:

    Force num_readers to be 1 when only input file is not sharded.

--
199292952  by Zhichao Lu:

    Adds image-level labels parsing into TfExampleDetectionAndGTParser.

--
199259866  by Zhichao Lu:

    Visual Relationships Evaluation executable.

--
199208330  by Zhichao Lu:

    Infer train_config.batch_size as the effective batch size. Therefore we need to divide the effective batch size in trainer by train_config.replica_to_aggregate to get per worker batch size.

--
199207842  by Zhichao Lu:

    Internal change.

--
199204222  by Zhichao Lu:

    In case the image has more than three channels, we only take the first three channels for visualization.

--
199194388  by Zhichao Lu:

    Correcting protocols description: VOC 2007 -> VOC 2012.

--
199188290  by Zhichao Lu:

    Adds per-relationship APs and mAP computation to VRD evaluation.

--
199158801  by Zhichao Lu:

    If available, additional channels are merged with input image.

--
199099637  by Zhichao Lu:

    OpenImages Challenge metric support:
    -adding verified labels standard field for TFExample;
    -adding tfrecord creation functionality.

--
198957391  by Zhichao Lu:

    Allow tf record sharding when creating pets dataset.

--
198925184  by Zhichao Lu:

    Introduce moving average support for evaluation. Also adding the ability to override this configuration via config_util.

--
198918186  by Zhichao Lu:

    Handles the case where there are 0 box masks.

--
198809009  by Zhichao Lu:

    Plumb groundtruth weights into target assigner for Faster RCNN.

--
198759987  by Zhichao Lu:

    Fix object detection test broken by shape inference.

--
198668602  by Zhichao Lu:

    Adding a new input field in data_decoders/tf_example_decoder.py for storing additional channels.

--
198530013  by Zhichao Lu:

    An util for hierarchical expandion of boxes and labels of OID dataset.

--
198503124  by Zhichao Lu:

    Fix dimension mismatch error introduced by
    https://github.com/tensorflow/tensorflow/pull/18251, or cl/194031845.
    After above change, conv2d strictly checks for conv_dims + 2 == input_rank.

--
198445807  by Zhichao Lu:

    Enabling Object Detection Challenge 2018 metric in evaluator.py framework for
    running eval job.
    Renaming old OpenImages V2 metric.

--
198413950  by Zhichao Lu:

    Support generic configuration override using namespaced keys

    Useful for adding custom hyper-parameter tuning fields without having to add custom override methods to config_utils.py.

--
198106437  by Zhichao Lu:

    Enable fused batchnorm now that quantization is supported.

--
198048364  by Zhichao Lu:

    Add support for keypoints in tf sequence examples and some util ops.

--
198004736  by Zhichao Lu:

    Relax postprocessing unit tests that are based on assumption that tf.image.non_max_suppression are stable with respect to input.

--
197997513  by Zhichao Lu:

    More lenient validation for normalized box boundaries.

--
197940068  by Zhichao Lu:

    A couple of minor updates/fixes:
    - Updating input reader proto with option to use display_name when decoding data.
    - Updating visualization tool to specify whether using absolute or normalized box coordinates. Appropriate boxes will now appear in TB when using model_main.py

--
197920152  by Zhichao Lu:

    Add quantized training support in the new OD binaries and a config for SSD Mobilenet v1 quantized training that is TPU compatible.

--
197213563  by Zhichao Lu:

    Do not share batch_norm for classification and regression tower in weight shared box predictor.

--
197196757  by Zhichao Lu:

    Relax the box_predictor api to return box_prediction of shape [batch_size, num_anchors, code_size] in addition to [batch_size, num_anchors, (1|q), code_size].

--
196898361  by Zhichao Lu:

    Allow per-channel scalar value to pad input image with when using keep aspect ratio resizer (when pad_to_max_dimension=True).

    In Object Detection Pipeline, we pad image before normalization and this skews batch_norm statistics during training. The option to set per channel pad value lets us truly pad with zeros.

--
196592101  by Zhichao Lu:

    Fix bug regarding tfrecord shuffling in object_detection

--
196320138  by Zhichao Lu:

    Fix typo in exporting_models.md

--

PiperOrigin-RevId: 199348852

* Adding option for one_box_for_all_classes to the box_predictor

PiperOrigin-RevId: 192813444

* Extend to accept different ratios of conv channels.

PiperOrigin-RevId: 192837477

* Remove inaccurate caveat from proto file.

PiperOrigin-RevId: 192850747

* Add option to set dropout for classification net in weight shared box predictor.

PiperOrigin-RevId: 192922089

* fix flakiness in testSSDRandomCropWithMultiClassScores due to randomness.

PiperOrigin-RevId: 193067658

* Post-process now works again in train mode.

PiperOrigin-RevId: 193087707

* Adding support for reading in logits as groundtruth labels and applying an optional temperature (scaling) before softmax in support of distillation.

PiperOrigin-RevId: 193119411

* Add a util function to visualize value histogram as a tf.summary.image.

PiperOrigin-RevId: 193137342

* Do not add batch norm parameters to final conv2d ops that predict boxes encodings and class scores in weight shared conv box predictor.

This allows us to set proper bias and force initial predictions to be background when using focal loss.

PiperOrigin-RevId: 193204364

* Make sure the final layers are also resized proportional to conv_depth_ratio.

PiperOrigin-RevId: 193228972

* Remove deprecated batch_norm_trainable field from ssd mobilenet v2 config

PiperOrigin-RevId: 193244778

* Updating coco evaluation metrics to allow for a batch of image info, rather than a single image.

PiperOrigin-RevId: 193382651

* Update protobuf requirements to 3+ in installation docs.

PiperOrigin-RevId: 193409179

* Add support for training keypoints.

PiperOrigin-RevId: 193576336

* Fix data augmentation functions.

PiperOrigin-RevId: 193737238

* Read the default batch size from config file.

PiperOrigin-RevId: 193959861

* Fixing a bug in the coco evaluator.

PiperOrigin-RevId: 193974479

* num_gt_boxes_per_image and num_det_boxes_per_image value incorrect.
Should be not the expand dim.

PiperOrigin-RevId: 194122420

* Add option to evaluate any checkpoint (without requiring write access to that directory and overwriting any existing logs there).

PiperOrigin-RevId: 194292198

* PiperOrigin-RevId: 190346687

* - Expose slim arg_scope function to compute keys to enable tessting.
- Add is_training=None option to mobinenet arg_scopes. This allows the users to set is_training from an outer scope.

PiperOrigin-RevId: 190997959

* Add an option to not set slim arg_scope for batch_norm is_training parameter. This enables users to set the is_training parameter from an outer scope.

PiperOrigin-RevId: 191611934

* PiperOrigin-RevId: 191955231

* PiperOrigin-RevId: 193254125

* PiperOrigin-RevId: 193371562

* PiperOrigin-RevId: 194085628

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.

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183933113  by Zhichao Lu:

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

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183929669  by Zhichao Lu:

    Expanding box list operations for future data augmentations.

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183916792  by Zhichao Lu:

    Fix unrecognized assertion function in tests.

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183906851  by Zhichao Lu:

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

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183871003  by Zhichao Lu:

    Fix config_util_test wrong dependency.

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183782120  by Zhichao Lu:

    Add __init__ file to third_party directories.

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183779109  by Zhichao Lu:

    Setup regular version sync.

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183768772  by Zhichao Lu:

    Make test compatible with numpy 1.12 and higher

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183767893  by Zhichao Lu:

    Make test compatible with numpy 1.12 and higher

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183719318  by Zhichao Lu:

    Use the new test interface in ssd feature extractor.

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183714671  by Zhichao Lu:

    Use the new test_case interface for all anchor generators.

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183708155  by Zhichao Lu:

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

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183705798  by Zhichao Lu:

    Internal change.

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183636023  by Zhichao Lu:

    Fixing argument name for np_box_list_ops.concatenate() function.

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183490404  by Zhichao Lu:

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

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175743440  by Zhichao Lu:

    Use Toggle instead of bool to make the layout optimizer name and usage consistent with other optimizers.

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    As a result of these friendly issues:
    https://github.com/tensorflow/models/issues/2530
    https://github.com/tensorflow/models/issues/2534

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PiperOrigin-RevId: 184048729

Add back six dependency and change pbtxt files to reflect new way of using own data to train object recognition models

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