- 04 Aug, 2020 1 commit
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Kaushik Shivakumar authored
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- 11 Jul, 2020 1 commit
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vivek rathod authored
320711412 by rathodv: Internal change -- 320707201 by lzc: Internal change 320690704 by TF Object Detection Team: Purely Google refactor -- 320665573 by TF Object Detection Team: Fallback to deprecated `experimental_run_v2` method if `run` does not exist. -- PiperOrigin-RevId: 320711412 Co-authored-by:TF Object Detection Team <no-reply@google.com>
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- 10 Jul, 2020 2 commits
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vivek rathod authored
320618558 by rathodv: Internal Change. -- 320597532 by ronnyvotel: Exposing DensePose visualizations to model_lib_v2.py. -- 320533669 by ronnyvotel: Adding utilities to visualize DensePose outputs. -- 320529647 by lzc: Fix saved_model issue in object_detection_tutorial notebook. -- 320510127 by aom: Internal change. -- 320490236 by derekjchow: Update Dockerfiles to use setup.py -- 320443572 by rathodv: Update `Tensorflow` to `TensorFlow` in documentation. -- 320426460 by ronnyvotel: DensePose proto and model builder. -- 320352611 by rathodv: Update documentation to reflect the support for TF1 and TF2. Provide separate sets of instructions to reduce confusion. -- 320350724 by rathodv: Internal Change. -- PiperOrigin-RevId: 320618558 Co-authored-by:kmindspark <kaushikshiv@google.com>
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kmindspark authored
* add ducks * add file * add file * add images * cleaning up to test * add colab * latest * add colab * clean up pr * change paths * fix colab * rename colab * remove config * fix more things in colab * clear outputs from colab * remove todos * for testing purposes * for testing purposes * PR for interactive ducks * add colab utils file * add colab utils file * add colab utils file * add colab utils file * add colab utils file * add colab utils file * add colab utils * add separate utils file * edit description * final * fix git repo url and remove installation test * temp config * add model checkpoint download * remove config
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- 08 Jul, 2020 1 commit
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vivek rathod authored
320117767 by ronnyvotel: DensePose postprocessing implementation. -- 320065853 by ronnyvotel: Updating how masks are reframed, so that it works on float and uint8 masks. -- 320061717 by yuhuic: Updated CenterNet restore_from_objects to allow the model to load the checkpoints saved during training. -- 319835172 by ronnyvotel: Updating how the DensePose UV Symmetries MAT file path is constructed and loaded. -- 319834678 by ronnyvotel: First update to CenterNetMetaArch for DensePose. Adding prediction and loss functionality. -- 319810261 by rathodv: Create a setup.py file to simplify installation. Usage: "python object_detection/packages/tf1/setup.py install" for TF1. "python object_detection/packages/tf2/setup.py install" for TF2. or to create source distribution "python object_detection/packages/tf1/setup.py sdist" for TF1. "python object_detection/packages/tf2/setup.py sdist" for TF2. -- 319803041 by sbeery: Updating documentation for export -- 319688087 by rathodv: Update as_matrix() to to_numpy() to avoid failures with python3.6 -- 319686183 by vighneshb: Require tpu_name when use_tpu is set. -- 319613327 by aom: EfficientDet-style Data Augmentation. -- 319572180 by rathodv: Add TF2 SSD FPN (a.k.a RetinaNet) configs. -- 319553823 by rathodv: Internal Change. -- PiperOrigin-RevId: 320117767 Co-authored-by:TF Object Detection Team <no-reply@google.com>
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- 30 Jun, 2020 2 commits
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vivek rathod authored
319052168 by rathodv: Change assertAllEqual to assertAllClose for Position Sensitive Crop and Resize to avoid flaky tests. -- 319044492 by rathodv: Internal change. -- 319039033 by ronnyvotel: Preprocessor ops for DensePose. -- 319035440 by sbeery: External beam code with DataFlow Support -- 318899436 by ronnyvotel: DensePose library for common operations like scaling, coordinate transformations, and flipping. -- 318833308 by Vivek Rathod: Internal Change -- PiperOrigin-RevId: 319052168 -
syiming authored
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- 29 Jun, 2020 3 commits
- 28 Jun, 2020 12 commits
- 26 Jun, 2020 2 commits
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vivek rathod authored
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. -- 318493408 by aom: Implements "Bidirectional Feature Pyramid Network Generators" for BiFPN-based feature extractors (e.g. EfficientDet). -- PiperOrigin-RevId: 318497061 -
vivek rathod authored
318417714 by jonathanhuang: Internal change. -- 318367213 by sbeery: Pointing users to more documentation for beam -- 318358685 by sbeery: Context R-CNN sample config for GPU -- 318309800 by rathodv: Internal -- 318303364 by ronnyvotel: Adding the option for parsing and including DensePose annotations. http://densepose.org/ -- 318291319 by aom: Adds conv_bn_act conv_block option, and naming convention changes for BiFPN utils. -- 318200598 by ronnyvotel: Updating the TF Example Decoder to parse DensePose annotations. -- 318174065 by jonathanhuang: Internal change. -- 318167805 by rathodv: Add use_tpu flag to TF2 binary. -- 318145285 by aom: Adds option for convolutional keras box predictor to force use_bias. -- PiperOrigin-RevId: 318417714
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- 24 Jun, 2020 1 commit
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vivek rathod authored
318106429 by derekjchow: Add Dockerfiles for TF-OD API. 1.15 and 2.2 supported currently. -- 318083650 by rathodv: Internal Change. -- 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. -- 317753117 by Zhichao Lu: Adds keras hyperparam option to force use_bias to True, even when using batch norm. -- 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. -- 317136881 by Zhichao Lu: Clarifying documentation -- 317097141 by Zhichao Lu: Adding Context R-CNN Release to TFODAPI ReadMe -- 316999744 by Zhichao Lu: Add import tensorflow.compat.v2 as tf2 in the model_lib to ensure tf1 compatibility. -- 316964482 by Zhichao Lu: adding a note about a config change needed for exporting detection features -- 316944293 by Zhichao Lu: Adding install instructions for apache beam -- 316917592 by lzc: Internal change. -- PiperOrigin-RevId: 318106429 Co-authored-by:Zhichao Lu <lzc@google.com>
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- 17 Jun, 2020 1 commit
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pkulzc authored
Internal changes -- PiperOrigin-RevId: 316837667
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- 26 May, 2020 1 commit
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pkulzc authored
* 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 -- 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 -- 308640...
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- 20 May, 2020 1 commit
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myproblemchild authored
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- 12 May, 2020 1 commit
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pkulzc authored
310447280 by lzc: Internal change 310420845 by Zhichao Lu: Open source the internal Context RCNN code. -- 310362339 by Zhichao Lu: Internal change 310259448 by lzc: Update required TF version for OD API. -- 310252159 by Zhichao Lu: Port patch_ops_test to TF1/TF2 as TPUs. -- 310247180 by Zhichao Lu: Ignore keypoint heatmap loss in the regions/bounding boxes with target keypoint class but no valid keypoint annotations. -- 310178294 by Zhichao Lu: Opensource MnasFPN https://arxiv.org/abs/1912.01106 -- 310094222 by lzc: Internal changes. -- 310085250 by lzc: Internal Change. -- 310016447 by huizhongc: Remove unrecognized classes from labeled_classes. -- 310009470 by rathodv: Mark batcher.py as TF1 only. -- 310001984 by rathodv: Update core/preprocessor.py to be compatible with TF1/TF2.. -- 309455035 by Zhichao Lu: Makes the freezable_batch_norm_test run w/ v2 behavior. The main change is in v2 updates will happen right away when running batchnorm in training mode. So, we need to restore the weights between batchnorm calls to make sure the numerical checks all start from the same place. -- 309425881 by Zhichao Lu: Make TF1/TF2 optimizer builder tests explicit. -- 309408646 by Zhichao Lu: Make dataset builder tests TF1 and TF2 compatible. -- 309246305 by Zhichao Lu: Added the functionality of combining the person keypoints and object detection annotations in the binary that converts the COCO raw data to TfRecord. -- 309125076 by Zhichao Lu: Convert target_assigner_utils to TF1/TF2. -- 308966359 by huizhongc: Support SSD training with partially labeled groundtruth. -- 308937159 by rathodv: Update core/target_assigner.py to be compatible with TF1/TF2. -- 308774302 by Zhichao Lu: Internal -- 308732860 by rathodv: Make core/prefetcher.py compatible with TF1 only. -- 308726984 by rathodv: Update core/multiclass_nms_test.py to be TF1/TF2 compatible. -- 308714718 by rathodv: Update core/region_similarity_calculator_test.py to be TF1/TF2 compatible. -- 308707960 by rathodv: Update core/minibatch_sampler_test.py to be TF1/TF2 compatible. -- 308700595 by rathodv: Update core/losses_test.py to be TF1/TF2 compatible and remove losses_test_v2.py -- 308361472 by rathodv: Update core/matcher_test.py to be TF1/TF2 compatible. -- 308335846 by Zhichao Lu: Updated the COCO evaluation logics and populated the groundturth area information through. This change matches the groundtruth format expected by the COCO keypoint evaluation. -- 308256924 by rathodv: Update core/keypoints_ops_test.py to be TF1/TF2 compatible. -- 308256826 by rathodv: Update class_agnostic_nms_test.py to be TF1/TF2 compatible. -- 308256112 by rathodv: Update box_list_ops_test.py to be TF1/TF2 compatible. -- 308159360 by Zhichao Lu: Internal change 308145008 by Zhichao Lu: Added 'image/class/confidence' field in the TFExample decoder. -- 307651875 by rathodv: Refactor core/box_list.py to support TF1/TF2. -- 307651798 by rathodv: Modify box_coder.py base class to work with with TF1/TF2 -- 307651652 by rathodv: Refactor core/balanced_positive_negative_sampler.py to support TF1/TF2. -- 307651571 by rathodv: Modify BoxCoders tests to use test_case:execute method to allow testing with TF1.X and TF2.X -- 307651480 by rathodv: Modify Matcher tests to use test_case:execute method to allow testing with TF1.X and TF2.X -- 307651409 by rathodv: Modify AnchorGenerator tests to use test_case:execute method to allow testing with TF1.X and TF2.X -- 307651314 by rathodv: Refactor model_builder to support TF1 or TF2 models based on TensorFlow version. -- 307092053 by Zhichao Lu: Use manager to save checkpoint. -- 307071352 by ronnyvotel: Fixing keypoint visibilities. Now by default, the visibility is marked True if the keypoint is labeled (regardless of whether it is visible or not). Also, if visibilities are not present in the dataset, they will be created based on whether the keypoint coordinates are finite (vis = True) or NaN (vis = False). -- 307069557 by Zhichao Lu: Internal change to add few fields related to postprocessing parameters in center_net.proto and populate those parameters to the keypoint postprocessing functions. -- 307012091 by Zhichao Lu: Make Adam Optimizer's epsilon proto configurable. Potential issue: tf.compat.v1's AdamOptimizer has a default epsilon on 1e-08 ([doc-link](https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/AdamOptimizer)) whereas tf.keras's AdamOptimizer has default epsilon 1e-07 ([doc-link](https://www.tensorflow.org/api_docs/python/tf/keras/optimizers/Adam)) -- 306858598 by Zhichao Lu: Internal changes to update the CenterNet model: 1) Modified eval job loss computation to avoid averaging over batches with zero loss. 2) Updated CenterNet keypoint heatmap target assigner to apply box size to heatmap Guassian standard deviation. 3) Updated the CenterNet meta arch keypoint losses computation to apply weights outside of loss function. -- 306731223 by jonathanhuang: Internal change. -- 306549183 by rathodv: Internal Update. -- 306542930 by rathodv: Internal Update -- 306322697 by rathodv: Internal. -- 305345036 by Zhichao Lu: Adding COCO Camera Traps Json to tf.Example beam code -- 304104869 by lzc: Internal changes. -- 304068971 by jonathanhuang: Internal change. -- 304050469 by Zhichao Lu: Internal change. -- 303880642 by huizhongc: Support parsing partially labeled groundtruth. -- 303841743 by Zhichao Lu: Deprecate nms_on_host in SSDMetaArch. -- 303803204 by rathodv: Internal change. -- 303793895 by jonathanhuang: Internal change. -- 303467631 by rathodv: Py3 update for detection inference test. -- 303444542 by rathodv: Py3 update to metrics module -- 303421960 by rathodv: Update json_utils to python3. -- 302787583 by ronnyvotel: Coco results generator for submission to the coco test server. -- 302719091 by Zhichao Lu: Internal change to add the ResNet50 image feature extractor for CenterNet model. -- 302116230 by Zhichao Lu: Added the functions to overlay the heatmaps with images in visualization util library. -- 301888316 by Zhichao Lu: Fix checkpoint_filepath not defined error. -- 301840312 by ronnyvotel: Adding keypoint_scores to visualizations. -- 301683475 by ronnyvotel: Introducing the ability to preprocess `keypoint_visibilities`. Some data augmentation ops such as random crop can filter instances and keypoints. It's important to also filter keypoint visibilities, so that the groundtruth tensors are always in alignment. -- 301532344 by Zhichao Lu: Don't use tf.divide since "Quantization not yet supported for op: DIV" -- 301480348 by ronnyvotel: Introducing keypoint evaluation into model lib v2. Also, making some fixes to coco keypoint evaluation. -- 301454018 by Zhichao Lu: Added the image summary to visualize the train/eval input images and eval's prediction/groundtruth side-by-side image. -- 301317527 by Zhichao Lu: Updated the random_absolute_pad_image function in the preprocessor library to support the keypoints argument. -- 301300324 by Zhichao Lu: Apply name change(experimental_run_v2 -> run) for all callers in Tensorflow. -- 301297115 by ronnyvotel: Utility function for setting keypoint visibilities based on keypoint coordinates. -- 301248885 by Zhichao Lu: Allow MultiworkerMirroredStrategy(MWMS) use by adding checkpoint handling with temporary directories in model_lib_v2. Added missing WeakKeyDictionary cfer_fn_cache field in CollectiveAllReduceStrategyExtended. -- 301224559 by Zhichao Lu: ...1) Fixes model_lib to also use keypoints while preparing model groundtruth. ...2) Tests model_lib with newly added keypoint metrics config. -- 300836556 by Zhichao Lu: Internal changes to add keypoint estimation parameters in CenterNet proto. -- 300795208 by Zhichao Lu: Updated the eval_util library to populate the keypoint groundtruth to eval_dict. -- 299474766 by Zhichao Lu: ...Modifies eval_util to create Keypoint Evaluator objects when configured in eval config. -- 299453920 by Zhichao Lu: Add swish activation as a hyperperams option. -- 299240093 by ronnyvotel: Keypoint postprocessing for CenterNetMetaArch. -- 299176395 by Zhichao Lu: Internal change. -- 299135608 by Zhichao Lu: Internal changes to refactor the CenterNet model in preparation for keypoint estimation tasks. -- 298915482 by Zhichao Lu: Make dataset_builder aware of input_context for distributed training. -- 298713595 by Zhichao Lu: Handling data with negative size boxes. -- 298695964 by Zhichao Lu: Expose change_coordinate_frame as a config parameter; fix multiclass_scores optional field. -- 298492150 by Zhichao Lu: Rename optimizer_builder_test_v2.py -> optimizer_builder_v2_test.py -- 298476471 by Zhichao Lu: Internal changes to support CenterNet keypoint estimation. -- 298365851 by ronnyvotel: Fixing a bug where groundtruth_keypoint_weights were being padded with a dynamic dimension. -- 297843700 by Zhichao Lu: Internal change. -- 297706988 by lzc: Internal change. -- 297705287 by ronnyvotel: Creating the "snapping" behavior in CenterNet, where regressed keypoints are refined with updated candidate keypoints from a heatmap. -- 297700447 by Zhichao Lu: Improve checkpoint checking logic with TF2 loop. -- 297686094 by Zhichao Lu: Convert "import tensorflow as tf" to "import tensorflow.compat.v1". -- 297670468 by lzc: Internal change. -- 297241327 by Zhichao Lu: Convert "import tensorflow as tf" to "import tensorflow.compat.v1". -- 297205959 by Zhichao Lu: Internal changes to support refactored the centernet object detection target assigner into a separate library. -- 297143806 by Zhichao Lu: Convert "import tensorflow as tf" to "import tensorflow.compat.v1". -- 297129625 by Zhichao Lu: Explicitly replace "import tensorflow" with "tensorflow.compat.v1" for TF2.x migration -- 297117070 by Zhichao Lu: Explicitly replace "import tensorflow" with "tensorflow.compat.v1" for TF2.x migration -- 297030190 by Zhichao Lu: Add configuration options for visualizing keypoint edges -- 296359649 by Zhichao Lu: Support DepthwiseConv2dNative (of separable conv) in weight equalization loss. -- 296290582 by Zhichao Lu: Internal change. -- 296093857 by Zhichao Lu: Internal changes to add general target assigner utilities. -- 295975116 by Zhichao Lu: Fix visualize_boxes_and_labels_on_image_array to show max_boxes_to_draw correctly. -- 295819711 by Zhichao Lu: Adds a flag to visualize_boxes_and_labels_on_image_array to skip the drawing of axis aligned bounding boxes. -- 295811929 by Zhichao Lu: Keypoint support in random_square_crop_by_scale. -- 295788458 by rathodv: Remove unused checkpoint to reduce repo size on github -- 295787184 by Zhichao Lu: Enable visualization of edges between keypoints -- 295763508 by Zhichao Lu: [Context RCNN] Add an option to enable / disable cropping feature in the post process step in the meta archtecture. -- 295605344 by Zhichao Lu: internal change. -- 294926050 by ronnyvotel: Adding per-keypoint groundtruth weights. These weights are intended to be used as multipliers in a keypoint loss function. Groundtruth keypoint weights are constructed as follows: - Initialize the weight for each keypoint type based on user-specified weights in the input_reader proto - Mask out (i.e. make zero) all keypoint weights that are not visible. -- 294829061 by lzc: Internal change. -- 294566503 by Zhichao Lu: Changed internal CenterNet Model configuration. -- 294346662 by ronnyvotel: Using NaN values in keypoint coordinates that are not visible. -- 294333339 by Zhichao Lu: Change experimetna_distribute_dataset -> experimental_distribute_dataset_from_function -- 293928752 by Zhichao Lu: Internal change -- 293909384 by Zhichao Lu: Add capabilities to train 1024x1024 CenterNet models. -- 293637554 by ronnyvotel: Adding keypoint visibilities to TfExampleDecoder. -- 293501558 by lzc: Internal change. -- 293252851 by Zhichao Lu: Change tf.gfile.GFile to tf.io.gfile.GFile. -- 292730217 by Zhichao Lu: Internal change. -- 292456563 by lzc: Internal changes. -- 292355612 by Zhichao Lu: Use tf.gather and tf.scatter_nd instead of matrix ops. -- 292245265 by rathodv: Internal -- 291989323 by richardmunoz: Refactor out building a DataDecoder from building a tf.data.Dataset. -- 291950147 by Zhichao Lu: Flip bounding boxes in arbitrary shaped tensors. -- 291401052 by huizhongc: Fix multiscale grid anchor generator to allow fully convolutional inference. When exporting model with identity_resizer as image_resizer, there is an incorrect box offset on the detection results. We add the anchor offset to address this problem. -- 291298871 by Zhichao Lu: Py3 compatibility changes. -- 290957957 by Zhichao Lu: Hourglass feature extractor for CenterNet. -- 290564372 by Zhichao Lu: Internal change. -- 290155278 by rathodv: Remove Dataset Explorer. -- 290155153 by Zhichao Lu: Internal change -- 290122054 by Zhichao Lu: Unify the format in the faster_rcnn.proto -- 290116084 by Zhichao Lu: Deprecate tensorflow.contrib. -- 290100672 by Zhichao Lu: Update MobilenetV3 SSD candidates -- 289926392 by Zhichao Lu: Internal change -- 289553440 by Zhichao Lu: [Object Detection API] Fix the comments about the dimension of the rpn_box_encodings from 4-D to 3-D. -- 288994128 by lzc: Internal changes. -- 288942194 by lzc: Internal change. -- 288746124 by Zhichao Lu: Configurable channel mean/std. dev in CenterNet feature extractors. -- 288552509 by rathodv: Internal. -- 288541285 by rathodv: Internal update. -- 288396396 by Zhichao Lu: Make object detection import contrib explicitly -- 288255791 by rathodv: Internal -- 288078600 by Zhichao Lu: Fix model_lib_v2 test -- 287952244 by rathodv: Internal -- 287921774 by Zhichao Lu: internal change -- 287906173 by Zhichao Lu: internal change -- 287889407 by jonathanhuang: PY3 compatibility -- 287889042 by rathodv: Internal -- 287876178 by Zhichao Lu: Internal change. -- 287770490 by Zhichao Lu: Add CenterNet proto and builder -- 287694213 by Zhichao Lu: Support for running multiple steps per tf.function call. -- 287377183 by jonathanhuang: PY3 compatibility -- 287371344 by rathodv: Support loading keypoint labels and ids. -- 287368213 by rathodv: Add protos supporting keypoint evaluation. -- 286673200 by rathodv: dataset_tools PY3 migration -- 286635106 by Zhichao Lu: Update code for upcoming tf.contrib removal -- 286479439 by Zhichao Lu: Internal change -- 286311711 by Zhichao Lu: Skeleton of context model within TFODAPI -- 286005546 by Zhichao Lu: Fix Faster-RCNN training when using keep_aspect_ratio_resizer with pad_to_max_dimension -- 285906400 by derekjchow: Internal change -- 285822795 by Zhichao Lu: Add CenterNet meta arch target assigners. -- 285447238 by Zhichao Lu: Internal changes. -- 285016927 by Zhichao Lu: Make _dummy_computation a tf.function. This fixes breakage caused by cl/284256438 -- 284827274 by Zhichao Lu: Convert to python 3. -- 284645593 by rathodv: Internal change -- 284639893 by rathodv: Add missing documentation for keypoints in eval_util.py. -- 284323712 by Zhichao Lu: Internal changes. -- 284295290 by Zhichao Lu: Updating input config proto and dataset builder to include context fields Updating standard_fields and tf_example_decoder to include context features -- 284226821 by derekjchow: Update exporter. -- 284211030 by Zhichao Lu: API changes in CenterNet informed by the experiments with hourlgass network. -- 284190451 by Zhichao Lu: Add support for CenterNet losses in protos and builders. -- 284093961 by lzc: Internal changes. -- 284028174 by Zhichao Lu: Internal change -- 284014719 by derekjchow: Do not pad top_down feature maps unnecessarily. -- 284005765 by Zhichao Lu: Add new pad_to_multiple_resizer -- 283858233 by Zhichao Lu: Make target assigner work when under tf.function. -- 283836611 by Zhichao Lu: Make config getters more general. -- 283808990 by Zhichao Lu: Internal change -- 283754588 by Zhichao Lu: Internal changes. -- 282460301 by Zhichao Lu: Add ability to restore v2 style checkpoints. -- 281605842 by lzc: Add option to disable loss computation in OD API eval job. -- 280298212 by Zhichao Lu: Add backwards compatible change -- 280237857 by Zhichao Lu: internal change -- PiperOrigin-RevId: 310447280
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- 13 Nov, 2019 1 commit
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Mark Sandler authored
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 -- 278006330 by Zhichao Lu: Internal changes to tf.contrib symbols -- 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
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- 17 Oct, 2019 1 commit
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pkulzc authored
* 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
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- 15 Jul, 2019 1 commit
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pkulzc authored
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...
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- 31 May, 2019 1 commit
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pkulzc authored
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
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- 22 May, 2019 1 commit
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Zhuoran Liu authored
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
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- 07 Mar, 2019 1 commit
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pkulzc authored
236813471 by lzc: Internal change. -- 236507310 by lzc: Fix preprocess.random_resize_method config type issue. The target height and width will be passed as "size" to tf.image.resize_images which only accepts integer. -- 236409989 by Zhichao Lu: Config export_to_tpu from function parameter instead of HParams for TPU inference. -- 236403186 by Zhichao Lu: Make graph file names optional arguments. -- 236237072 by Zhichao Lu: Minor bugfix for keyword args. -- 236209602 by Zhichao Lu: Add support for PartitionedVariable to get_variables_available_in_checkpoint. -- 235828658 by Zhichao Lu: Automatically stop evaluation jobs when training is finished. -- 235817964 by Zhichao Lu: Add an optional process_metrics_fn callback to eval_util, it gets called with evaluation results once each evaluation is complete. -- 235788721 by lzc: Fix yml file tf runtime version. -- 235262897 by Zhichao Lu: Add keypoint support to the random_pad_image preprocessor method. -- 235257380 by Zhichao Lu: Support InputDataFields.groundtruth_confidences in retain_groundtruth(), retain_groundtruth_with_positive_classes(), filter_groundtruth_with_crowd_boxes(), filter_groundtruth_with_nan_box_coordinates(), filter_unrecognized_classes(). -- 235109188 by Zhichao Lu: Fix bug in pad_input_data_to_static_shapes for num_additional_channels > 0; make color-specific data augmentation only touch RGB channels. -- 235045010 by Zhichao Lu: Don't slice class_predictions_with_background when add_background_class is false. -- 235026189 by lzc: Fix import in g3doc. -- 234863426 by Zhichao Lu: Added fixes in exporter to allow writing a checkpoint to a specified temporary directory. -- 234671886 by lzc: Internal Change. -- 234630803 by rathodv: Internal Change. -- 233985896 by Zhichao Lu: Add Neumann optimizer to object detection. -- 233560911 by Zhichao Lu: Add NAS-FPN object detection with Resnet and Mobilenet v2. -- 233513536 by Zhichao Lu: Export TPU compatible object detection model -- 233495772 by lzc: Internal change. -- 233453557 by Zhichao Lu: Create Keras-based SSD+MobilenetV1 for object detection. -- 233220074 by lzc: Update release notes date. -- 233165761 by Zhichao Lu: Support depth_multiplier and min_depth in _SSDResnetV1FpnFeatureExtractor. -- 233160046 by lzc: Internal change. -- 232926599 by Zhichao Lu: [tf.data] Switching tf.data functions to use `defun`, providing an escape hatch to continue using the legacy `Defun`. There are subtle differences between the implementation of `defun` and `Defun` (such as resources handling or control flow) and it is possible that input pipelines that use control flow or resources in their functions might be affected by this change. To migrate majority of existing pipelines to the recommended way of creating functions in TF 2.0 world, while allowing (a small number of) existing pipelines to continue relying on the deprecated behavior, this CL provides an escape hatch. If your input pipeline is affected by this CL, it should apply the escape hatch by replacing `foo.map(...)` with `foo.map_with_legacy_function(...)`. -- 232891621 by Zhichao Lu: Modify faster_rcnn meta architecture to normalize raw detections. -- 232875817 by Zhichao Lu: Make calibration a post-processing step. Specifically: - Move the calibration config from pipeline.proto --> post_processing.proto - Edit post_processing_builder.py to return a calibration function. If no calibration config is provided, it None. - Edit SSD and FasterRCNN meta architectures to optionally call the calibration function on detection scores after score conversion and before NMS. -- 232704481 by Zhichao Lu: Edit calibration builder to build a function that will be used within a detection model's `postprocess` method, after score conversion and before non-maxima suppression. Specific Edits: - The returned function now accepts class_predictions_with_background as its argument instead of detection_scores and detection_classes. - Class-specific calibration was temporarily removed, as it requires more significant refactoring. Will be added later. -- 232615379 by Zhichao Lu: Internal change -- 232483345 by ronnyvotel: Making the use of bfloat16 restricted to TPUs. -- 232399572 by Zhichao Lu: Edit calibration builder and proto to support class-agnostic calibration. Specifically: - Edit calibration protos to include path to relevant label map if required for class-specific calibration. Previously, label maps were inferred from other parts of the pipeline proto; this allows all information required by the builder stay within the calibration proto and remove extraneous information from being passed with class-agnostic calibration. - Add class-agnostic protos to the calibration config. Note that the proto supports sigmoid and linear interpolation parameters, but the builder currently only supports linear interpolation. -- 231613048 by Zhichao Lu: Add calibration builder for applying calibration transformations from output of object detection models. Specifically: - Add calibration proto to support sigmoid and isotonic regression (stepwise function) calibration. - Add a builder to support calibration from isotonic regression outputs. -- 231519786 by lzc: model_builder test refactor. - removed proto text boilerplate in each test case and let them call a create_default_proto function instead. - consolidated all separate ssd model creation tests into one. - consolidated all separate faster rcnn model creation tests into one. - used parameterized test for testing mask rcnn models and use_matmul_crop_and_resize - added all failures test. -- 231448169 by Zhichao Lu: Return static shape as a constant tensor. -- 231423126 by lzc: Add a release note for OID v4 models. -- 231401941 by Zhichao Lu: Adding correct labelmap for the models trained on Open Images V4 (*oid_v4 config suffix). -- 231320357 by Zhichao Lu: Add scope to Nearest Neighbor Resize op so that it stays in the same name scope as the original resize ops. -- 231257699 by Zhichao Lu: Switch to using preserve_aspect_ratio in tf.image.resize_images rather than using a custom implementation. -- 231247368 by rathodv: Internal change. -- 231004874 by lzc: Update documentations to use tf 1.12 for object detection API. -- 230999911 by rathodv: Use tf.batch_gather instead of ops.batch_gather -- 230999720 by huizhongc: Fix weight equalization test in ops_test. -- 230984728 by rathodv: Internal update. -- 230929019 by lzc: Add an option to replace preprocess operation with placeholder for ssd feature extractor. -- 230845266 by lzc: Require tensorflow version 1.12 for object detection API and rename keras_applications to keras_models -- 230392064 by lzc: Add RetinaNet 101 checkpoint trained on OID v4 to detection model zoo. -- 230014128 by derekjchow: This file was re-located below the tensorflow/lite/g3doc/convert -- 229941449 by lzc: Update SSD mobilenet v2 quantized model download path. -- 229843662 by lzc: Add an option to use native resize tf op in fpn top-down feature map generation. -- 229636034 by rathodv: Add deprecation notice to a few old parameters in train.proto -- 228959078 by derekjchow: Remove duplicate elif case in _check_and_convert_legacy_input_config_key -- 228749719 by rathodv: Minor refactoring to make exporter's `build_detection_graph` method public. -- 228573828 by rathodv: Mofity model.postprocess to return raw detections and raw scores. Modify, post-process methods in core/model.py and the meta architectures to export raw detection (without any non-max suppression) and raw multiclass score logits for those detections. -- 228420670 by Zhichao Lu: Add shims for custom architectures for object detection models. -- 228241692 by Zhichao Lu: Fix the comment on "losses_mask" in "Loss" class. -- 228223810 by Zhichao Lu: Support other_heads' predictions in WeightSharedConvolutionalBoxPredictor. Also remove a few unused parameters and fix a couple of comments in convolutional_box_predictor.py. -- 228200588 by Zhichao Lu: Add Expected Calibration Error and an evaluator that calculates the metric for object detections. -- 228167740 by lzc: Add option to use bounded activations in FPN top-down feature map generation. -- 227767700 by rathodv: Internal. -- 226295236 by Zhichao Lu: Add Open Image V4 Resnet101-FPN training config to third_party -- 226254842 by Zhichao Lu: Fix typo in documentation. -- 225833971 by Zhichao Lu: Option to have no resizer in object detection model. -- 225824890 by lzc: Fixes p3 compatibility for model_lib.py -- 225760897 by menglong: normalizer should be at least 1. -- 225559842 by menglong: Add extra logic filtering unrecognized classes. -- 225379421 by lzc: Add faster_rcnn_inception_resnet_v2_atrous_oid_v4 config to third_party -- 225368337 by Zhichao Lu: Add extra logic filtering unrecognized classes. -- 225341095 by Zhichao Lu: Adding Open Images V4 models to OD API model zoo and corresponding configs to the configs. -- 225218450 by menglong: Add extra logic filtering unrecognized classes. -- 225057591 by Zhichao Lu: Internal change. -- 224895417 by rathodv: Internal change. -- 224209282 by Zhichao Lu: Add two data augmentations to object detection: (1) Self-concat (2) Absolute pads. -- 224073762 by Zhichao Lu: Do not create tf.constant until _generate() is actually called in the object detector. -- PiperOrigin-RevId: 236813471
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- 11 Jan, 2019 1 commit
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Red Daly authored
* Remove duplicate elif case in _check_and_convert_legacy_input_config_key * Remove duplicate eval_input_path case.
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- 30 Nov, 2018 1 commit
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Zhichao Lu authored
223075771 by lzc: Bring in external fixes. -- 222919755 by ronnyvotel: Bug fix in faster r-cnn model builder. Was previously using `inplace_batchnorm_update` for `reuse_weights`. -- 222885680 by Zhichao Lu: Use the result_dict_for_batched_example in models_lib Also fixes the visualization size on when eval is on GPU -- 222883648 by Zhichao Lu: Fix _unmatched_class_label for the _add_background_class == False case in ssd_meta_arch.py. -- 222836663 by Zhichao Lu: Adding support for visualizing grayscale images. Without this change, the images are black-red instead of grayscale. -- 222501978 by Zhichao Lu: Fix a bug that caused convert_to_grayscale flag not to be respected. -- 222432846 by richardmunoz: Fix mapping of groundtruth_confidences from shape [num_boxes] to [num_boxes, num_classes] when the input contains the groundtruth_confidences field. -- 221725755 by richardmunoz: Internal change. -- 221458536 by Zhichao Lu: Fix saver defer build bug in object detection train codepath. -- 221391590 by Zhichao Lu: Add support for group normalization in the object detection API. Just adding MobileNet-v1 SSD currently. This may serve as a road map for other models that wish to support group normalization as an option. -- 221367993 by Zhichao Lu: Bug fixes (1) Make RandomPadImage work, (2) Fix keep_checkpoint_every_n_hours. -- 221266403 by rathodv: Use detection boxes as proposals to compute correct mask loss in eval jobs. -- 220845934 by lzc: Internal change. -- 220778850 by Zhichao Lu: Incorporating existing metrics into Estimator framework. Should restore: -oid_challenge_detection_metrics -pascal_voc_detection_metrics -weighted_pascal_voc_detection_metrics -pascal_voc_instance_segmentation_metrics -weighted_pascal_voc_instance_segmentation_metrics -oid_V2_detection_metrics -- 220370391 by alirezafathi: Adding precision and recall to the metrics. -- 220321268 by Zhichao Lu: Allow the option of setting max_examples_to_draw to zero. -- 220193337 by Zhichao Lu: This CL fixes a bug where the Keras convolutional box predictor was applying heads in the non-deterministic dict order. The consequence of this bug was that variables were created in non-deterministic orders. This in turn led different workers in a multi-gpu training setup to have slightly different graphs which had variables assigned to mismatched parameter servers. As a result, roughly half of all workers were unable to initialize and did no work, and training time was slowed down approximately 2x. -- 220136508 by huizhongc: Add weight equalization loss to SSD meta arch. -- 220125875 by pengchong: Rename label_scores to label_weights -- 219730108 by Zhichao Lu: Add description of detection_keypoints in postprocessed_tensors to docstring. -- 219577519 by pengchong: Support parsing the class confidences and training using them. -- 219547611 by lzc: Stop using static shapes in GPU eval jobs. -- 219536476 by Zhichao Lu: Migrate TensorFlow Lite out of tensorflow/contrib This change moves //tensorflow/contrib/lite to //tensorflow/lite in preparation for TensorFlow 2.0's deprecation of contrib/. If you refer to TF Lite build targets or headers, you will need to update them manually. If you use TF Lite from the TensorFlow python package, "tf.contrib.lite" now points to "tf.lite". Please update your imports as soon as possible. For more details, see https://groups.google.com/a/tensorflow.org/forum/#!topic/tflite/iIIXOTOFvwQ @angersson and @aselle are conducting this migration. Please contact them if you have any further questions. -- 219190083 by Zhichao Lu: Add a second expected_loss_weights function using an alternative expectation calculation compared to previous. Integrate this op into ssd_meta_arch and losses builder. Affects files that use losses_builder.build to handle the returning of an additional element. -- 218924451 by pengchong: Add a new way to assign training targets using groundtruth confidences. -- 218760524 by chowdhery: Modify export script to add option for regular NMS in TFLite post-processing op. -- PiperOrigin-RevId: 223075771
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- 02 Nov, 2018 1 commit
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pkulzc authored
* 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. Adds test for faster_rcnn_meta_arch for predict and postprocess in inference mode for first and second stages. PiperOrigin-RevId: 214329565 * Fix model_lib eval_spec_names assignment (integer->string). PiperOrigin-RevId: 214335461 * Refactor Mask HEAD to optionally upsample after applying convolutions on ROI crops. PiperOrigin-RevId: 214338440 * Uses final_exporter_name as exporter_name for the first eval spec for backward compatibility. PiperOrigin-RevId: 214522032 * Add reshaped `mask_predictions` tensor to the prediction dictionary in `_predict_third_stage` method to allow computing mask loss in eval job. PiperOrigin-RevId: 214620716 * Add support for fully conv training to fpn. PiperOrigin-RevId: 214626274 * Fix the proprocess() function in Resnet v1 to make it work for any number of input channels. Note: If the #channels != 3, this will simply skip the mean subtraction in preprocess() function. PiperOrigin-RevId: 214635428 * Wrap result_dict_for_single_example in eval_util to run for batched examples. PiperOrigin-RevId: 214678514 * Adds PNASNet-based (ImageNet model) feature extractor for SSD. PiperOrigin-RevId: 214988331 * Update documentation PiperOrigin-RevId: 215243502 * Correct index used to compute number of groundtruth/detection boxes in COCOMaskEvaluator. Due to an incorrect indexing in cl/214295305 only the first detection mask and first groundtruth mask for a given image are fed to the COCO Mask evaluation library. Since groundtruth masks are arranged in no particular order, the first and highest scoring detection mask (detection masks are ordered by score) won't match the the first and only groundtruth retained in all cases. This is I think why mask evaluation metrics do not get better than ~11 mAP. Note that this code path is only active when using model_main.py binary for evaluation. This change fixes the indices and modifies an existing test case to cover it. PiperOrigin-RevId: 215275936 * Fixing grayscale_image_resizer to accept mask as input. PiperOrigin-RevId: 215345836 * Add an option not to clip groundtruth boxes during preprocessing. Clipping boxes adversely affects training for partially occluded or large objects, especially for fully conv models. Clipping already occurs during postprocessing, and should not occur during training. PiperOrigin-RevId: 215613379 * Always return recalls and precisions with length equal to the number of classes. The previous behavior of ObjectDetectionEvaluation was somewhat dangerous: when no groundtruth boxes were present, the lists of per-class precisions and recalls were simply truncated. Unless you were aware of this phenomenon (and consulted the `num_gt_instances_per_class` vector) it was difficult to associate each metric with each class. PiperOrigin-RevId: 215633711 * Expose the box feature node in SSD. PiperOrigin-RevId: 215653316 * Fix ssd mobilenet v2 _CONV_DEFS overwriting issue. PiperOrigin-RevId: 215654160 * More documentation updates PiperOrigin-RevId: 215656580 * Add pooling + residual option in multi_resolution_feature_maps. It adds an average pooling and a residual layer between feature maps with matching depth. Designed to be used with WeightSharedBoxPredictor. PiperOrigin-RevId: 215665619 * Only call create_modificed_mobilenet_config on init if use_depthwise is true. PiperOrigin-RevId: 215784290 * Only call create_modificed_mobilenet_config on init if use_depthwise is true. PiperOrigin-RevId: 215837524 * Don't prune keypoints if clip_boxes is false. PiperOrigin-RevId: 216187642 * Makes sure "key" field exists in the result dictionary. PiperOrigin-RevId: 216456543 * Add add_background_class parameter to allow disabling the inclusion of a background class. PiperOrigin-RevId: 216567612 * Update expected_classification_loss_under_sampling to better account for expected sampling. PiperOrigin-RevId: 216712287 * Let the evaluation receive a evaluation class in its constructor. PiperOrigin-RevId: 216769374 * This CL adds model building & training support for end-to-end Keras-based SSD models. If a Keras feature extractor's name is specified in the model config (e.g. 'ssd_mobilenet_v2_keras'), the model will use that feature extractor and a corresponding Keras-based box predictor. This CL makes sure regularization losses & batch norm updates work correctly when training models that have Keras-based components. It also updates the default hyperparameter settings of the keras-based mobilenetV2 (when not overriding hyperparams) to more closely match the legacy Slim training scope. PiperOrigin-RevId: 216938707 * Adding the ability in the coco evaluator to indicate whether an image has been annotated. For a non-annotated image, detections and groundtruth are not supplied. PiperOrigin-RevId: 217316342 * Release the 8k minival dataset ids for MSCOCO, used in Huang et al. "Speed/accuracy trade-offs for modern convolutional object detectors" (https://arxiv.org/abs/1611.10012) PiperOrigin-RevId: 217549353 * Exposes weighted_sigmoid_focal loss for faster rcnn classifier PiperOrigin-RevId: 217601740 * Add detection_features to output nodes. The shape of the feature is [batch_size, max_detections, depth]. PiperOrigin-RevId: 217629905 * FPN uses a custom NN resize op for TPU-compatibility. Replace this op with the Tensorflow version at export time for TFLite-compatibility. PiperOrigin-RevId: 217721184 * Compute `num_groundtruth_boxes` in inputs.tranform_input_data_fn after data augmentation instead of decoders. PiperOrigin-RevId: 217733432 * 1. Stop gradients from flowing into groundtruth masks with zero paddings. 2. Normalize pixelwise cross entropy loss across the whole batch. PiperOrigin-RevId: 217735114 * Optimize Input pipeline for Mask R-CNN on TPU with blfoat16: improve the step time from: 1663.6 ms -> 1184.2 ms, about 28.8% improvement. PiperOrigin-RevId: 217748833 * Fixes to export a TPU compatible model Adds nodes to each of the output tensor. Also increments the value of class labels by 1. PiperOrigin-RevId: 217856760 * API changes: - change the interface of target assigner to return per-class weights. - change the interface of classification loss to take per-class weights. PiperOrigin-RevId: 217968393 * Add an option to override pipeline config in export_saved_model using command line arg PiperOrigin-RevId: 218429292 * Include Quantized trained MobileNet V2 SSD and FaceSsd in model zoo. PiperOrigin-RevId: 218530947 * Write final config to disk in `train` mode only. PiperOrigin-RevId: 218735512
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- 21 Sep, 2018 2 commits
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pkulzc authored
214018767 by Zhichao Lu: Add original_image_spatial_shape tensor in input dictionary to store shape of the original input image -- 213914693 by lzc: Internal change. -- 213872175 by Zhichao Lu: This CL adds a Keras-based mobilenet_v2 feature extractor for object detection models. As part of this CL, we use the Keras mobilenet_v2 application's keyword argument layer injection API to allow the generated network to support the object detection hyperparameters. -- 213848499 by Zhichao Lu: Replace tf.image.resize_nearest_neighbor with tf.image.resize_images. tf.image.resize_nearest_neighbor only supports 4-D tensors but masks is a 3-D tensor. -- 213758622 by lzc: Internal change. -- PiperOrigin-RevId: 214018767 -
pkulzc authored
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
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