GitLab

318569851  by jonathanhuang:

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

--

PiperOrigin-RevId: 318569851

318545448  by jonathanhuang:

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

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318514741  by sbeery:

    Adding link to the blog post

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PiperOrigin-RevId: 318545448

318497061  by rathodv:

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

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318493408  by aom:

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

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PiperOrigin-RevId: 318497061

318417714  by jonathanhuang:

    Internal change.

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318367213  by sbeery:

    Pointing users to more documentation for beam

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318358685  by sbeery:

    Context R-CNN sample config for GPU

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318309800  by rathodv:

    Internal

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318303364  by ronnyvotel:

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

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318291319  by aom:

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

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318200598  by ronnyvotel:

    Updating the TF Example Decoder to parse DensePose annotations.

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318174065  by jonathanhuang:

    Internal change.

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318167805  by rathodv:

    Add use_tpu flag to TF2 binary.

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318145285  by aom:

    Adds option for convolutional keras box predictor to force use_bias.

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PiperOrigin-RevId: 318417714

318106429  by derekjchow:

    Add Dockerfiles for TF-OD API.

    1.15 and 2.2 supported currently.

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318083650  by rathodv:

    Internal Change.

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317893148  by Zhichao Lu:

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

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317753117  by Zhichao Lu:

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

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317613986  by Zhichao Lu:

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

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

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317136881  by Zhichao Lu:

    Clarifying documentation

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317097141  by Zhichao Lu:

    Adding Context R-CNN Release to TFODAPI ReadMe

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316999744  by Zhichao Lu:

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

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316964482  by Zhichao Lu:

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

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316944293  by Zhichao Lu:

    Adding install instructions for apache beam

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316917592  by lzc:

    Internal change.

--

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

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

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

Internal changes

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PiperOrigin-RevId: 316837667

* 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

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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.

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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

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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.

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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.

--
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.

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310178294  by Zhichao Lu:

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

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310094222  by lzc:

    Internal changes.

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310085250  by lzc:

    Internal Change.

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310016447  by huizhongc:

    Remove unrecognized classes from labeled_classes.

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310009470  by rathodv:

    Mark batcher.py as TF1 only.

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310001984  by rathodv:

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

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309455035  by Zhi...

The current android Dockerfile for object detectiion is not functional anymore. This commit fixes it by the following changes:
 - install gpg-agent, update google-cloud-sdk installation from https://cloud.google.com/sdk/docs/quickstart-debian-ubuntu
 - use non-interactive front end to set default tzdata configuration (required for TF object detection installation)
 - fix the tensorflow configuration

Leaving the base image untouched, although nightly-devel is no longer actively maintained. It may be worth upgrading as a separate effort later.

* fix TF_OD_API_LABELS_FILE name problem

* Fix variable TF_OD_API_LABELS_FILE in documention

Updated website addresses for MS COCO and Open Images.

It might seem redundant, but I followed this whole tutorial not knowing what <path-to-tensorflow> meant, and tried to install into the actual "tensorflow" package inside of my python installation.

* Update directory path 

- Update directory path with Tensorflow directoy folder: tensorflow/models/research/
- Add option to refresh source ~/.bashrc

* Update installation.md

* Fix maintainers list into a table for easy read.

* Taken duplicate name out of the maintainers table.

typo fixed

* Update README.md

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* Update README.md...

The colab and github link were in wrong hrefs.

280142968  by Zhichao Lu:

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

--
280134001  by Zhichao Lu:

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

--
278941778  by Zhichao Lu:

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

--
278933274  by Zhichao Lu:

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

--
278762192  by Zhichao Lu:

    Ensure correct number of iterations after training resumes.

--
278746440  by Zhichao Lu:

    Internal change.

--
278006953  by Zhichao Lu:

    Internal changes to tf.contrib symbols

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278006330  by Zhichao Lu:

    Internal changes to tf.contrib symbols

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277593959  by Zhichao Lu:

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

--
277344551  by Zhichao Lu:

    Internal change.

--
277154953  by Zhichao Lu:

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

--
277087572  by Zhichao Lu:

    Fix resizing boxes when using keep_aspect_ratio_rezier with padding.

--
275898543  by Zhichao Lu:

    Support label_map_proto as input in label_map_util.

--
275347137  by Zhichao Lu:

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

--

PiperOrigin-RevId: 280142968

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

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

--
274908068  by Sergio Guadarrama:

    Opensource MobilenetV3 detection models.

--
274697808  by Sergio Guadarrama:

    Fixed cases where tf.TensorShape was constructed with float dimensions

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

--
273577462  by Sergio Guadarrama:

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

--
272801298  by Sergio Guadarrama:

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

--
268928503  by Sergio Guadarrama:

    Mobilenet v2 with group normalization.

--
263492735  by Sergio Guadarrama:

    Internal change

260037126  by Sergio Guadarrama:

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

--
259997001  by Sergio Guadarrama:

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

--
252697685  by Sergio Guadarrama:

    Internal change

251918746  by Sergio Guadarrama:

    Internal change

251909704  by Sergio Guadarrama:

    Mobilenet V3 backbone implementation.

--
247510236  by Sergio Guadarrama:

    Internal change

246196802  by Sergio Guadarrama:

    Internal change

246014539  by Sergio Guadarrama:

    Internal change

245891435  by Sergio Guadarrama:

    Internal change

245834925  by Sergio Guadarrama:

    n/a

--

PiperOrigin-RevId: 275131829

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

    Update detection model zoo with MobilenetV3 SSD candidates.

--
274908068  by Zhichao Lu:

    Opensource MobilenetV3 detection models.

--
274695889  by richardmunoz:

    RandomPatchGaussian preprocessing step

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

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

--
274257872  by lzc:

    Internal change.

--
274114689  by Zhichao Lu:

    Pass native_resize flag to other FPN variants.

--
274112308  by lzc:

    Internal change.

--
274090763  by richardmunoz:

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

--
274069806  by Zhichao Lu:

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

--
273860828  by lzc:

    Internal change.

--
273380069  by richardmunoz:

    RandomImageDownscaleToTargetPixels preprocessing step

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

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

--
272987602  by Zhichao Lu:

    Avoid -inf when empty box list is passed.

--
272525836  by Zhichao Lu:

    Cleanup repeated resizing code in meta archs.

--
272458667  by richardmunoz:

    RandomJpegQuality preprocessing step

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

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

--
271412717  by Zhichao Lu:

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

--
270744153  by Zhichao Lu:

    Adding the offset and size target assigners for CenterNet.

--
269916081  by Zhichao Lu:

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

--
269376056  by Zhichao Lu:

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

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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.

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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.

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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

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263031163  by Zhichao Lu:

    Mark outside compilation for NMS as optional.

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263024916  by Zhichao Lu:

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

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262655894  by Zhichao Lu:

    Add the center heatmap target assigner for CenterNet

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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.

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261834966  by Zhichao Lu:

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

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261775941  by Zhichao Lu:

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

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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

* Updating python API to use CombinedNonMaxSuppresion TF operator

1. Adds a unit test to test post_processing python API
2. Currently sets clip_window to None as the kernel uses the default
   clip_window of [0,0,1,1]
3. Added use_static_shapes to the API. In old API if
   use_static_shapes is true, then it pads/clips outputs to max_total_size, if
specified. If not specified, it pads to num_classes*max_size_per_class.
 If use_static_shapes is false, it always pads/clips to max_total_size.

Update unit test to account for clipped bouding boxes

Changed the name to CombinedNonMaxSuppression based on feedback from Google

Added additional parameters to combinedNMS python function. They are currently
unused and required for networks like FasterRCNN and MaskRCNN

* Delete selected_indices from API

Because it was removed from CombinedNMS recently in the PR.

* Improve doc of function combined_non_max_suppression

* Enable CombinedNonMaxSuppression for first_stage_nms

* fix bug

* Ensure agnostic_nms is not used with combined_nms

Remove redundant arguments from combined_nms

* Fix pylint

* Add checks for unsupported args

* Fix pylint

* Move combined_non_max_suppression to batch_multiclass_non_max_suppression

Also rename combined_nms to use_combined_nms

* Delete combined_nms for first_stage_nms because it does not work

* Revert "Delete combined_nms for first_stage_nms because it does not work"

This reverts commit 2a3cc5145f17cee630a67ddedd20e90c2920fa9f.

* Use nmsed_additional_fields.get to avoid error

* Merge combined_non_max_suppression with main nms function

* Rename combined_nms for first stage nms

* Improve  docs

* Use assertListEqual for numpy arrays

* Fix pylint errors

* End comments with period

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 fo...

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...

np.uint8 to np.int64 for detection class label index overflow when using OIDv4 labels

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