GitLab

275538818  by Sergio Guadarrama:

    Support grayscale input images in Slim model training

--
275355841  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.

--
275131829  by Sergio Guadarrama:

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

--

PiperOrigin-RevId: 275538818

* 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

After Eager was moved to core Tensorflow, this notebook gives the error:
AttributeError: module 'tensorflow.contrib.eager' has no attribute 'Variable'
I just fixed it.

* 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

* Fix TensorRT test output and add int8 result.

* Fix comments

* Removing footnote declaration as well

* Remove TF-TRT examples and point users to new example repo

* Update urls

* Fix review comments and links

The reference implementation can be found at
https://github.com/tensorflow/minigo

This fork was originally created to experiment with performance upgrades
for MLPerf, but since MLPerf work is focused in the original repo,
this fork's existence only serves to confuse.

Add specification for what dataset link to use on the website.

* Merged commit includes the following changes:
263863588  by yongzhe:

    Fix a bug that the SetExternalContext for EdgeTPU wasn't called when initializing LSTD client.

--
263370193  by yongzhe:

    Internal change.

--

PiperOrigin-RevId: 263863588

* Revert changes in seq_dataset_builder_test.py

* Remove stale code

* Merged commit includes the following changes:
263863588  by yongzhe:

    Fix a bug that the SetExternalContext for EdgeTPU wasn't called when initializing LSTD client.

--
263370193  by yongzhe:

    Internal change.

--

PiperOrigin-RevId: 263863588

* Revert changes in seq_dataset_builder_test.py

libedgetpu.h was used instead of edgetpu.h:
https://coral.googlesource.com/edgetpu-native/+/refs/heads/release-diploria/libedgetpu/

PiperOrigin-RevId: 263176146

* Replace google3.pyglib modules with tf and absl

This now matches train.py and provides more publicly available libraries.

* Add example pipeline config for SSD Interleaved V2 Model.

Compiled from model_builder_test.py and lstm_ssd_mobilenet_v1_imagenet.config,
Removed data augmentation and tranfer learning (i.e. training from checkpoint) due to errors I was seeing when trying to run with it.

* Remove unused tfrecord creation.

This was also incorrectly specified, as the keys differed from the TFSequenceExample parser.

* correct key specified in docstring

* add tflite frozen graph exporter (cli and lib).

* add tflite model exporter

* add script to test the tflite model

* add mode export documentation

* correct docstring

* rename export files to be unique across detection research work

* correct number of channels for grayscale

* add and correct copyright

261196859  by yongzhe:

    Integrate EdgeTPU API into the Mobile SSD tflite client.

    Build command with EdgeTPU enabled:
    bazel build mobile_ssd_tflite_client  --define enable_edgetpu=true

    Build command with EdgeTPU disabled:
    bazel build mobile_ssd_tflite_client

--
259096620  by Menglong Zhu:

    Remove unused proto imports.

--

PiperOrigin-RevId: 261196859

* Merged commit includes the following changes:
257930561  by yongzhe:

    Mobile LSTD TfLite Client.

--
257928126  by yongzhe:

    Mobile SSD Tflite client.

--
257921181  by menglong:

    Fix discrepancy between pre_bottleneck = {true, false}

--
257561213  by yongzhe:

    File utils.

--
257449226  by yongzhe:

    Mobile SSD Client.

--
257264654  by yongzhe:

    SSD utils.

--
257235648  by yongzhe:

    Proto bazel build rules.

--
256437262  by Menglong Zhu:

    Fix check for FusedBatchNorm op to only verify it as a prefix.

--
256283755  by yongzhe:

    Bazel build and copybara changes.

--
251947295  by yinxiao:

    Add missing interleaved option in checkpoint restore.

--
251513479  by yongzhe:

    Conversion utils.

--
248783193  by yongzhe:

    Branch protos needed for the lstd client.

--
248200507  by menglong:

    Fix proto namespace in example config

--

P...

* Merged commit includes the following changes:
257930561  by yongzhe:

    Mobile LSTD TfLite Client.

--
257928126  by yongzhe:

    Mobile SSD Tflite client.

--
257921181  by menglong:

    Fix discrepancy between pre_bottleneck = {true, false}

--
257561213  by yongzhe:

    File utils.

--
257449226  by yongzhe:

    Mobile SSD Client.

--
257264654  by yongzhe:

    SSD utils.

--
257235648  by yongzhe:

    Proto bazel build rules.

--
256437262  by Menglong Zhu:

    Fix check for FusedBatchNorm op to only verify it as a prefix.

--
256283755  by yongzhe:

    Bazel build and copybara changes.

--
251947295  by yinxiao:

    Add missing interleaved option in checkpoint restore.

--
251513479  by yongzhe:

    Conversion utils.

--
248783193  by yongzhe:

    Branch protos needed for the lstd client.

--
248200507  by menglong:

    Fix proto namespace in example config

--

PiperOrigin-RevId: 257930561

* Delete BUILD

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...

* Update research/maskgan/README.md
Co-Authored-By: Andrew M Dai <andy.dai@gmail.com>

Update to tf 1.14 syntax, fix bug #7125 (needed additional expand for conv2d).  Suppress compat warnings by moving to compat.v1 versions of some functions.  Note that this code is not 2.0 compatible yet - that will be a future push. (#7177)

* Merged commit includes the following changes:
253126424  by Andre Araujo:

    Scripts to compute metrics for Google Landmarks dataset.

    Also, a small fix to metric in retrieval case: avoids duplicate predicted images.

--
253118971  by Andre Araujo:

    Metrics for Google Landmarks dataset.

--
253106953  by Andre Araujo:

    Library to read files from Google Landmarks challenges.

--
250700636  by Andre Araujo:

    Handle case of aggregation extraction with empty set of input features.

--
250516819  by Andre Araujo:

    Add minimum size for DELF extractor.

--
250435822  by Andre Araujo:

    Add max_image_size/min_image_size for open-source DELF proto / module.

--
250414606  by Andre Araujo:

    Refactor extract_aggregation to allow reuse with different datasets.

--
250356863  by Andre Araujo:

    Remove unnecessary cmd_args variable from boxes_and_features_extraction.

--
249783379  by Andre Araujo:

    Create directory for writing mapping file if it does not exist.

--
249581591  by Andre Araujo:

    Refactor scripts to extract boxes and features from images in Revisited datasets.
    Also, change tf.logging.info --> print for easier logging in open source code.

--
249511821  by Andre Araujo:

    Small change to function for file/directory handling.

--
249289499  by Andre Araujo:

    Internal change.

--

PiperOrigin-RevId: 253126424

* Updating DELF init to adjust to latest changes

* Editing init files for python packages

* Edit D2R dataset reader to work with py3.

PiperOrigin-RevId: 253135576

* DELF package: fix import ordering

* Moved VGGish code into its own directory.

* Moved most of old README.md into vggish/README.md.

* Add step 1 instructions for MaskGAN.

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

* Put all python dependencies into one line.

This makes it easier to copy, paste & install all dependencies at once. In addition many users have custom setups (virtualenv, conda, .etc). Having it in one line easily allows to grap the dependencies.

* Remove 'sudo' from all pip install commands and adjust troubleshooting section.

The ".mat" files loaded in the dataset are byte files. Python 3.7 requires them to be loaded using "rb".

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

* Initial feature aggregation code for Detect-to-Retrieve paper.

PiperOrigin-RevId: 246043144

* Add support for ASMK/ASMK*/R-ASMK/R-ASMK*.

PiperOrigin-RevId: 247337028

* Add DatumProto uint32 field, and limit datum_io to uint32 and float32/float64 types.

Also, introduce DatumPairProto, to be used for ASMK variants. Functions to read/write in this new format are added and tested.

PiperOrigin-RevId: 247515205

* Add batching option to feature aggregation extraction.

PiperOrigin-RevId: 247614627

* Script to perform local feature aggregation, with associated configs.

Also small edits to the aggregation extractor, for better handling of input features / avoiding OOM.

PiperOrigin-RevId: 248150750

* Tests to check that aggregation using regions with no local features works.

PiperOrigin-RevId: 248153275

* Include new library/proto for aggregation

* Merged commit includes the following changes:

PiperOrigin-RevId: 24817...

* Initial feature aggregation code for Detect-to-Retrieve paper.

PiperOrigin-RevId: 246043144

* Add support for ASMK/ASMK*/R-ASMK/R-ASMK*.

PiperOrigin-RevId: 247337028

* Add DatumProto uint32 field, and limit datum_io to uint32 and float32/float64 types.

Also, introduce DatumPairProto, to be used for ASMK variants. Functions to read/write in this new format are added and tested.

PiperOrigin-RevId: 247515205

* Add batching option to feature aggregation extraction.

PiperOrigin-RevId: 247614627

* Script to perform local feature aggregation, with associated configs.

Also small edits to the aggregation extractor, for better handling of input features / avoiding OOM.

PiperOrigin-RevId: 248150750

* Tests to check that aggregation using regions with no local features works.

PiperOrigin-RevId: 248153275

* Include new library/proto for aggregation

* Merged commit includes the following changes:

PiperOrigin-RevId: 248176511

* Merged commit includes the following changes:
248194572  by Andre Araujo:

    Change tf.tensor_scatter_nd_add --> tf.compat.v1.tensor_scatter_add to make it compatible with TF 1.X.

--

PiperOrigin-RevId: 248194572

* Functions to parse ground-truth and compute metrics for revisited datasets.

Unit tests are added.

PiperOrigin-RevId: 248561575

* Small change to argparse bool option, which does not work as expected.

PiperOrigin-RevId: 248805505

* Class to compute similarity between aggregated descriptors.

PiperOrigin-RevId: 249102986

* Script to perform retrieval and compute metrics.

PiperOrigin-RevId: 249104011

* feature_aggregation_similarity library in DELF init

* D2R instructions / README update

* Small edit to README

* Internal change.

PiperOrigin-RevId: 249113531

* Instructions to reproduce D2R paper results, and small edits to config files.

PiperOrigin-RevId: 249159850

* Revert "Internal change."

This reverts commit 0529f2b8471a20c88f1fbb37367f142965d098ee.

Undoing incorrect markdown deletion.

* Initial feature aggregation code for Detect-to-Retrieve paper.

PiperOrigin-RevId: 246043144

* Add support for ASMK/ASMK*/R-ASMK/R-ASMK*.

PiperOrigin-RevId: 247337028

* Add DatumProto uint32 field, and limit datum_io to uint32 and float32/float64 types.

Also, introduce DatumPairProto, to be used for ASMK variants. Functions to read/write in this new format are added and tested.

PiperOrigin-RevId: 247515205

* Add batching option to feature aggregation extraction.

PiperOrigin-RevId: 247614627

* Script to perform local feature aggregation, with associated configs.

Also small edits to the aggregation extractor, for better handling of input features / avoiding OOM.

PiperOrigin-RevId: 248150750

* Tests to check that aggregation using regions with no local features works.

PiperOrigin-RevId: 248153275

* Include new library/proto for aggregation

* Merged commit includes the following changes:

PiperOrigin-RevId: 248176511

* Merged commit includes the following changes:
248194572  by Andre Araujo:

    Change tf.tensor_scatter_nd_add --> tf.compat.v1.tensor_scatter_add to make it compatible with TF 1.X.

--

PiperOrigin-RevId: 248194572

* Functions to parse ground-truth and compute metrics for revisited datasets.

Unit tests are added.

PiperOrigin-RevId: 248561575

* Small change to argparse bool option, which does not work as expected.

PiperOrigin-RevId: 248805505

* Class to compute similarity between aggregated descriptors.

PiperOrigin-RevId: 249102986

* Script to perform retrieval and compute metrics.

PiperOrigin-RevId: 249104011

* feature_aggregation_similarity library in DELF init

* D2R instructions / README update

* Small edit to README

* Internal change.

PiperOrigin-RevId: 249113531

* Instructions to reproduce D2R paper results, and small edits to config files.

PiperOrigin-RevId: 249159850