GitLab

320335495  by rathodv:

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

--
320278161  by ronnyvotel:

    Exposing DensePose fields to model libraries.

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320277319  by rathodv:

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

--
320258215  by rathodv:

    Internal Change.

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320245458  by yuhuic:

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

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320225405  by jonathanhuang:

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

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320145077  by aom:

    Implements EfficientDet feature extractor.

--

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

Internal changes

--

PiperOrigin-RevId: 316837667

* Merged commit includes the following changes:
311933687  by Sergio Guadarrama:

    Removes spurios use of tf.compat.v2, which results in spurious tf.compat.v1.compat.v2. Adds basic test to nasnet_utils.
    Replaces all remaining import tensorflow as tf with import tensorflow.compat.v1 as tf

--
311766063  by Sergio Guadarrama:

    Removes explicit tf.compat.v1 in all call sites (we already import tf.compat.v1, so this code was  doing tf.compat.v1.compat.v1). The existing code worked in latest version of tensorflow, 2.2, (and 1.15) but not in 1.14 or in 2.0.0a, this CL fixes it.

--
311624958  by Sergio Guadarrama:

    Updates README that doesn't render properly in github documentation

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310980959  by Sergio Guadarrama:

    Moves research_models/slim off tf.contrib.slim/layers/framework to tf_slim

--
310263156  by Sergio Guadarrama:

    Adds model breakdown for MobilenetV3

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308640516  by Sergio Guadarrama:

    Internal change

308244396  by Sergio Guadarrama:

    GroupNormalization support for MobilenetV3.

--
307475800  by Sergio Guadarrama:

    Internal change

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302077708  by Sergio Guadarrama:

    Remove `disable_tf2` behavior from slim py_library targets

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301208453  by Sergio Guadarrama:

    Automated refactoring to make code Python 3 compatible.

--
300816672  by Sergio Guadarrama:

    Internal change

299433840  by Sergio Guadarrama:

    Internal change

299221609  by Sergio Guadarrama:

    Explicitly disable Tensorflow v2 behaviors for all TF1.x binaries and tests

--
299179617  by Sergio Guadarrama:

    Internal change

299040784  by Sergio Guadarrama:

    Internal change

299036699  by Sergio Guadarrama:

    Internal change

298736510  by Sergio Guadarrama:

    Internal change

298732599  by Sergio Guadarrama:

    Internal change

298729507  by Sergio Guadarrama:

    Internal change

298253328  by Sergio Guadarrama:

    Internal change

297788346  by Sergio Guadarrama:

    Internal change

297785278  by Sergio Guadarrama:

    Internal change

297783127  by Sergio Guadarrama:

    Internal change

297725870  by Sergio Guadarrama:

    Internal change

297721811  by Sergio Guadarrama:

    Internal change

297711347  by Sergio Guadarrama:

    Internal change

297708059  by Sergio Guadarrama:

    Internal change

297701831  by Sergio Guadarrama:

    Internal change

297700038  by Sergio Guadarrama:

    Internal change

297670468  by Sergio Guadarrama:

    Internal change.

--
297350326  by Sergio Guadarrama:

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

--
297201668  by Sergio Guadarrama:

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

--
294483372  by Sergio Guadarrama:

    Internal change

PiperOrigin-RevId: 311933687

* Merged commit includes the following changes:
312578615  by Menglong Zhu:

    Modify the LSTM feature extractors to be python 3 compatible.

--
311264357  by Menglong Zhu:

    Removes contrib.slim

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308957207  by Menglong Zhu:

    Automated refactoring to make code Python 3 compatible.

--
306976470  by yongzhe:

    Internal change

306777559  by Menglong Zhu:

    Internal change

--
299232507  by lzyuan:

    Internal update.

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299221735  by lzyuan:

    Add small epsilon on max_range for quantize_op to prevent range collapse.

--

PiperOrigin-RevId: 312578615

* Merged commit includes the following changes:
310447280  by lzc:

    Internal changes.

--

PiperOrigin-RevId: 310447280
Co-authored-by: Sergio Guadarrama <sguada@google.com>
Co-authored-by: Menglong Zhu <menglong@google.com>

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 Zhi...

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.

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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.

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255698776  by lzc:

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

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255623150  by Zhichao Lu:

    Add Keras-based ResnetV1 models.

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255504992  by Zhichao Lu:

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

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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.

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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.

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255441632  by rathodv:

    Fallback on groundtruth classes when multiclass_scores tensor is empty.

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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.

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255308908  by Zhichao Lu:

    Add comment to clarify usage of calibration parameters proto.

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255266371  by Zhichao Lu:

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

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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

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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.

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253151266  by Zhichao Lu:

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

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252718956  by Zhichao Lu:

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

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252158593  by Zhichao Lu:

    Make object_detection/core Python3-compatible.

--
252150717  by Zhichao Lu:

    Make object_detection/core Python3-compatible.

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251967048  by Zhichao Lu:

    Make GraphRewriter proto extensible.

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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.

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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.

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251511339  by Zhichao Lu:

    Add multiclass isotonic regression to the calibration builder.

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251317769  by pengchong:

    Internal Change.

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250729989  by Zhichao Lu:

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

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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 Zh...

The evaluation crashes in python3 if iteritems() is used instead of items()

* Internal change.

PiperOrigin-RevId: 213914693

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

PiperOrigin-RevId: 214018767

* Remove "groundtruth_confidences" from decoders use "groundtruth_weights" to indicate label confidence.

This also solves a bug that only surfaced now - random crop routines in core/preprocessor.py did not correctly handle "groundtruth_weight" tensors returned by the decoders.

PiperOrigin-RevId: 214091843

* Update CocoMaskEvaluator to allow for a batch of image info, rather than a single image.

PiperOrigin-RevId: 214295305

* Adding the option to be able to summarize gradients.

PiperOrigin-RevId: 214310875

* Adds FasterRCNN inference on CPU

1. Adds a flag use_static_shapes_for_eval to restrict to the ops that guarantees static shape.
2. No filtering of overlapping anchors while clipping the anchors when use_static_shapes_for_eval is set to True.
3. A...

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

* Merged commit includes the following changes:
207771702  by Zhichao Lu:

    Refactoring evaluation utilities so that it is easier to introduce new DetectionEvaluators with eval_metric_ops.

--
207758641  by Zhichao Lu:

    Require tensorflow version 1.9+ for running object detection API.

--
207641470  by Zhichao Lu:

    Clip `num_groundtruth_boxes` in pad_input_data_to_static_shapes() to `max_num_boxes`. This prevents a scenario where tensors are sliced to an invalid range in model_lib.unstack_batch().

--
207621728  by Zhichao Lu:

    This CL adds a FreezableBatchNorm that inherits from the Keras BatchNormalization layer, but supports freezing the `training` parameter at construction time instead of having to do it in the `call` method.

    It also adds a method to the `KerasLayerHyperparams` class that will build an appropriate FreezableBatchNorm layer according to the hyperparameter configuration. If batch_norm is disabled, this method returns and Identity layer.

    These will be used to simplify the conversion to Keras APIs.

--
207610524  by Zhichao Lu:

    Update anchor generators and box predictors for python3 compatibility.

--
207585122  by Zhichao Lu:

    Refactoring convolutional box predictor into separate prediction heads.

--
207549305  by Zhichao Lu:

    Pass all 1s for batch weights if nothing is specified in GT.

--
207336575  by Zhichao Lu:

    Move the new argument 'target_assigner_instance' to the end of the list of arguments to the ssd_meta_arch constructor for backwards compatibility.

--
207327862  by Zhichao Lu:

    Enable support for float output in quantized custom op for postprocessing in SSD Mobilenet model.

--
207323154  by Zhichao Lu:

    Bug fix: change dict.iteritems() to dict.items()

--
207301109  by Zhichao Lu:

    Integrating expected_classification_loss_under_sampling op as an option in the ssd_meta_arch

--
207286221  by Zhichao Lu:

    Adding an option to weight regression loss with foreground scores from the ground truth labels.

--
207231739  by Zhichao Lu:

    Explicitly mentioning the argument names when calling the batch target assigner.

--
207206356  by Zhichao Lu:

    Add include_trainable_variables field to train config to better handle trainable variables.

--
207135930  by Zhichao Lu:

    Internal change.

--
206862541  by Zhichao Lu:

    Do not unpad the outputs from batch_non_max_suppression before sampling.

    Since BalancedPositiveNegativeSampler takes an indicator for valid positions to sample from we can pass the output from NMS directly into Sampler.

--

PiperOrigin-RevId: 207771702

* Remove unused doc.

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

* 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

* Force cast of num_classes to integer

PiperOrigin-RevId: 188335318

* Updating config util to allow overwriting of cosine decay learning rates.

PiperOrigin-RevId: 188338852

* Make box_list_ops.py and box_list_ops_test.py work with C API enabled.

The C API has improved shape inference over the original Python
code. This causes some previously-working conds to fail. Switching to smart_cond fixes this.

Another effect of the improved shape inference is that one of the
failures tested gets caught earlier, so I modified the test to reflect
this.

PiperOrigin-RevId: 188409792

* Fix parallel event file writing issue.

Without this change, the event files might get corrupted when multiple evaluations are run in parallel.

PiperOrigin-RevId: 188502560

* Deprecating the boolean flag of from_detection_checkpoint.

Replace with a string field fine_tune_checkpoint_type to train_config to provide extensibility. The fine_tune_checkpoint_type can currently take value of `detection`, `classification`, or others when the restore_map is overwritten.

PiperOrigin-RevId: 188518685

* Automated g4 rollback of changelist 188502560

PiperOrigin-RevId: 188519969

* Introducing eval metrics specs for Coco Mask metrics. This allows metrics to be computed in tensorflow using the tf.learn Estimator.

PiperOrigin-RevId: 188528485

* Minor fix to make object_detection/metrics/coco_evaluation.py python3 compatible.

PiperOrigin-RevId: 188550683

* Updating eval_util to handle eval_metric_ops from multiple `DetectionEvaluator`s.

PiperOrigin-RevId: 188560474

* Allow tensor input for new_height and new_width for resize_image.

PiperOrigin-RevId: 188561908

* Fix typo in fine_tune_checkpoint_type name in trainer.

PiperOrigin-RevId: 188799033

* Adding mobilenet feature extractor to object detection.

PiperOrigin-RevId: 188916897

* Allow label maps to optionally contain an explicit background class with id zero.

PiperOrigin-RevId: 188951089

* Fix boundary conditions in random_pad_to_aspect_ratio to ensure that min_scale is always less than max_scale.

PiperOrigin-RevId: 189026868

* Fallback on from_detection_checkpoint option if fine_tune_checkpoint_type isn't set.

PiperOrigin-RevId: 189052833

* Add proper names for learning rate schedules so we don't see cryptic names on tensorboard.

PiperOrigin-RevId: 189069837

* Enforcing that all datasets are batched (and then unbatched in the model) with batch_size >= 1.

PiperOrigin-RevId: 189117178

* Adding regularization to total loss returned from DetectionModel.loss().

PiperOrigin-RevId: 189189123

* Standardize the names of loss scalars (for SSD, Faster R-CNN and R-FCN) in both training and eval so they can be compared on tensorboard.

Log localization and classification losses in evaluation.

PiperOrigin-RevId: 189189940

* Remove negative test from box list ops test.

PiperOrigin-RevId: 189229327

* Add an option to warmup learning rate in manual stepping schedule.

PiperOrigin-RevId: 189361039

* Replace tf.contrib.slim.tfexample_decoder.LookupTensor with object_detection.data_decoders.tf_example_decoder.LookupTensor.

PiperOrigin-RevId: 189388556

* Force regularization summary variables under specific family names.

PiperOrigin-RevId: 189393190

* Automated g4 rollback of changelist 188619139

PiperOrigin-RevId: 189396001

* Remove step 0 schedule since we do a hard check for it after cl/189361039

PiperOrigin-RevId: 189396697

* PiperOrigin-RevId: 189040463

* PiperOrigin-RevId: 189059229

* PiperOrigin-RevId: 189214402

* Force regularization summary variables under specific family names.

PiperOrigin-RevId: 189393190

* Automated g4 rollback of changelist 188619139

PiperOrigin-RevId: 189396001

* Make slim python3 compatible.

* Monir fixes.

* Add TargetAssignment summaries in a separate family.

PiperOrigin-RevId: 189407487

* 1. Setting `family` keyword arg prepends the summary names twice with the same name. Directly adding family suffix to the name gets rid of this problem.
2. Make sure the eval losses have the same name.

PiperOrigin-RevId: 189434618

* Minor fixes to make object detection tf 1.4 compatible.

PiperOrigin-RevId: 189437519

* Call the base of mobilenet_v1 feature extractor under the right arg scope and set batchnorm is_training based on the value passed in the constructor.

PiperOrigin-RevId: 189460890

* Automated g4 rollback of changelist 188409792

PiperOrigin-RevId: 189463882

* Update object detection syncing.

PiperOrigin-RevId: 189601955

* Add an option to warmup learning rate, hold it constant for a certain number of steps and cosine decay it.

PiperOrigin-RevId: 189606169

* Let the proposal feature extractor function in faster_rcnn meta architectures return the activations (end_points).

PiperOrigin-RevId: 189619301

* Fixed bug which caused masks to be mostly zeros (caused by detection_boxes being in absolute coordinates if scale_to_absolute=True.

PiperOrigin-RevId: 189641294

* Open sourcing Mobilenetv2 + SSDLite.

PiperOrigin-RevId: 189654520

* Remove unused files.

PiperOrigin-RevId: 187527188

185215255  by Zhichao Lu:

    Stop populating image/object/class/text field when generating COCO tf record.

--
185213306  by Zhichao Lu:

    Use the params batch size and not the one from train_config in input_fn

--
185209081  by Zhichao Lu:

    Handle the case when there are no ground-truth masks for an image.

--
185195531  by Zhichao Lu:

    Remove unstack and stack operations on features from third_party/object_detection/model.py.

--
185195017  by Zhichao Lu:

    Matrix multiplication based gather op implementation.

--
185187744  by Zhichao Lu:

    Fix eval_util minor issue.

--
185098733  by Zhichao Lu:

    Internal change

185076656  by Zhichao Lu:

    Increment the amount of boxes for coco17.

--
185074199  by Zhichao Lu:

    Add config for SSD Resnet50 v1 with FPN.

--
185060199  by Zhichao Lu:

    Fix a bug in clear_detections.
    This method set detection_keys to an empty dictionary instead of an empty set. I've refactored so that this method and the constructor use the same code path.

--
185031359  by Zhichao Lu:

    Eval TPU trained models continuously.

--
185016591  by Zhichao Lu:

    Use TPUEstimatorSpec for TPU

--
185013651  by Zhichao Lu:

    Add PreprocessorCache to record and duplicate augmentations.

--
184921763  by Zhichao Lu:

    Minor fixes for object detection.

--
184920610  by Zhichao Lu:

    Adds a model builder test for "embedded_ssd_mobilenet_v1" feature extractor.

--
184919284  by Zhichao Lu:

    Added unit tests for TPU, with optional training / eval.

--
184915910  by Zhichao Lu:

    Update third_party g3 doc with Mask RCNN detection models.

--
184914085  by Zhichao Lu:

    Slight change to WeightSharedConvolutionalBoxPredictor implementation to make things match more closely with RetinaNet.  Specifically we now construct the box encoding and class predictor towers separately rather than having them share weights until penultimate layer.

--
184913786  by Zhichao Lu:

    Plumbs SSD Resnet V1 with FPN models into model builder.

--
184910030  by Zhichao Lu:

    Add coco metrics to evaluator.

--
184897758  by Zhichao Lu:

    Merge changes from github.

--
184888736  by Zhichao Lu:

    Ensure groundtruth_weights are always 1-D.

--
184887256  by Zhichao Lu:

    Introduce an option to add summaries in the model so it can be turned off when necessary.

--
184865559  by Zhichao Lu:

    Updating inputs so that a dictionary of tensors is returned from input_fn. Moving unbatch/unpad to model.py.
    Also removing source_id key from features dictionary, and replacing with an integer hash.

--
184859205  by Zhichao Lu:

    This CL is trying to hide those differences by making the default settings work with the public code.

--
184769779  by Zhichao Lu:

    Pass groundtruth weights into ssd meta architecture all the way to target assigner.

    This will allow training ssd models with padded groundtruth tensors.

--
184767117  by Zhichao Lu:

    * Add `params` arg to make all input fns work with TPUEstimator
    * Add --master
    * Output eval results

--
184766244  by Zhichao Lu:

    Update create_coco_tf_record to include category indices

--
184752937  by Zhichao Lu:

    Create a third_party version of TPU compatible mobilenet_v2_focal_loss coco config.

--
184750174  by Zhichao Lu:

    A few small fixes for multiscale anchor generator and a test.

--
184746581  by Zhichao Lu:

    Update jupyter notebook to show mask if provided by model.

--
184728646  by Zhichao Lu:

    Adding a few more tests to make sure decoding with/without label maps performs as expected.

--
184624154  by Zhichao Lu:

    Add an object detection binary for TPU.

--
184622118  by Zhichao Lu:

    Batch, transform, and unbatch in the tflearn interface.

--
184595064  by Zhichao Lu:

    Add support for training grayscale models.

--
184532026  by Zhichao Lu:

    Change dataset_builder.build to perform optional batching using tf.data.Dataset API

--
184330239  by Zhichao Lu:

    Add augment_input_data and transform_input_data helper functions to third_party/tensorflow_models/object_detection/inputs.py

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184328681  by Zhichao Lu:

    Use an internal rgb to gray method that can be quantized.

--
184327909  by Zhichao Lu:

    Helper function to return padding shapes to use with Dataset.padded_batch.

--
184326291  by Zhichao Lu:

    Added decode_func for specialized decoding.

--
184314676  by Zhichao Lu:

    Add unstack_batch method to inputs.py.

    This will enable us to convert batched tensors to lists of tensors. This is compatible with OD API that consumes groundtruth batch as a list of tensors.

--
184281269  by Zhichao Lu:

    Internal test target changes.

--
184192851  by Zhichao Lu:

    Adding `Estimator` interface for object detection.

--
184187885  by Zhichao Lu:

    Add config_util functions to help with input pipeline.

    1. function to return expected shapes from the resizer config
    2. function to extract image_resizer_config from model_config.

--
184139892  by Zhichao Lu:

    Adding support for depthwise SSD (ssd-lite) and depthwise box predictions.

--
184089891  by Zhichao Lu:

    Fix third_party faster rcnn resnet101 coco config.

--
184083378  by Zhichao Lu:

    In the case when there is no object/weights field in tf.Example proto, return a default weight of 1.0 for all boxes.

--

PiperOrigin-RevId: 185215255

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.

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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

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    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

182391090  by Zhichao Lu:

    Internal change

182262339  by Zhichao Lu:

    Internal change

182244645  by Zhichao Lu:

    Internal change

182241613  by Zhichao Lu:

    Internal change

182133027  by Zhichao Lu:

    Internal change

182058807  by Zhichao Lu:

    Internal change

181812028  by Zhichao Lu:

    Internal change

181788857  by Zhichao Lu:

    Internal change

181656761  by Zhichao Lu:

    Internal change

181541125  by Zhichao Lu:

    Internal change

181538702  by Zhichao Lu:

    Internal change

181125385  by Zhichao Lu:

    Internal change

180957758  by Zhichao Lu:

    Internal change

180941434  by Zhichao Lu:

    Internal change

180852569  by Zhichao Lu:

    Internal change

180846001  by Zhichao Lu:

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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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