GitLab

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

Leaving the base image untouched, although nightly-devel is no longer actively maintained.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

* fix TF_OD_API_LABELS_FILE name problem

* Fix variable TF_OD_API_LABELS_FILE in documention

Updated website addresses for MS COCO and Open Images.

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

* Update directory path 

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

* Update installation.md

* Fix maintainers list into a table for easy read.

* Taken duplicate name out of the maintainers table.

typo fixed

* Update README.md

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The colab and github link were in wrong hrefs.

280142968  by Zhichao Lu:

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

--
280134001  by Zhichao Lu:

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

--
278941778  by Zhichao Lu:

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

--
278933274  by Zhichao Lu:

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

--
278762192  by Zhichao Lu:

    Ensure correct number of iterations after training resumes.

--
278746440  by Zhichao Lu:

    Internal change.

--
278006953  by Zhichao Lu:

    Internal changes to tf.contrib symbols

--
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

* 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

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263031163  by Zhichao Lu:

    Mark outside compilation for NMS as optional.

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263024916  by Zhichao Lu:

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

--
262655894  by Zhichao Lu:

    Add the center heatmap target assigner for CenterNet

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262431036  by Zhichao Lu:

    Adding add_eval_dict to allow for evaluation on model_v2

--
262035351  by ronnyvotel:

    Removing any non-Tensor predictions from the third stage of Mask R-CNN.

--
261953416  by Zhichao Lu:

    Internal change.

--
261834966  by Zhichao Lu:

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

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261775941  by Zhichao Lu:

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

--
261775633  by Zhichao Lu:

    Visualize additional channels with ground-truth bounding boxes.

--
261768117  by lzc:

    Internal change.

--
261766773  by ronnyvotel:

    Exposing `return_raw_detections_during_predict` in Faster R-CNN Proto.

--
260975089  by ronnyvotel:

    Moving calculation of batched prediction tensor names after all tensors in prediction dictionary are created.

--
259816913  by ronnyvotel:

    Adding raw detection boxes and feature map indices to SSD

--
259791955  by Zhichao Lu:

    Added a flag to control the use partitioned_non_max_suppression.

--
259580475  by Zhichao Lu:

    Tweak quantization-aware training re-writer to support NasFpn model architecture.

--
259579943  by rathodv:

    Add a meta target assigner proto and builders in OD API.

--
259577741  by Zhichao Lu:

    Internal change.

--
259366315  by lzc:

    Internal change.

--
259344310  by ronnyvotel:

    Updating faster rcnn so that raw_detection_boxes from predict() are in normalized coordinates.

--
259338670  by Zhichao Lu:

    Add support for use_native_resize_op to more feature extractors. Use dynamic shapes when static shapes are not available.

--
259083543  by ronnyvotel:

    Updating/fixing documentation.

--
259078937  by rathodv:

    Add prediction fields for tensors returned from detection_model.predict.

--
259044601  by Zhichao Lu:

    Add protocol buffer and builders for temperature scaling calibration.

--
259036770  by lzc:

    Internal changes.

--
259006223  by ronnyvotel:

    Adding detection anchor indices to Faster R-CNN Config. This is useful when one wishes to associate final detections and the anchors (or pre-nms boxes) from which they originated.

--
258872501  by Zhichao Lu:

    Run the training pipeline of ssd + resnet_v1_50 + fpn with a checkpoint.

--
258840686  by ronnyvotel:

    Adding standard outputs to DetectionModel.predict(). This CL only updates Faster R-CNN. Other meta architectures will be updated in future CLs.

--
258672969  by lzc:

    Internal change.

--
258649494  by lzc:

    Internal changes.

--
258630321  by ronnyvotel:

    Fixing documentation in shape_utils.flatten_dimensions().

--
258468145  by Zhichao Lu:

    Add additional output tensors parameter to Postprocess op.

--
258099219  by Zhichao Lu:

    Internal changes

--

PiperOrigin-RevId: 274959989

* Updating python API to use CombinedNonMaxSuppresion TF operator

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

Update unit test to account for clipped bouding boxes

Changed the name to CombinedNonMaxSuppression based on feedback from Google

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

* Delete selected_indices from API

Because it was removed from CombinedNMS recently in the PR.

* Improve doc of function combined_non_max_suppression

* Enable CombinedNonMaxSuppression for first_stage_nms

* fix bug

* Ensure agnostic_nms is not used with combined_nms

Remove redundant arguments from combined_nms

* Fix pylint

* Add checks for unsupported args

* Fix pylint

* Move combined_non_max_suppression to batch_multiclass_non_max_suppression

Also rename combined_nms to use_combined_nms

* Delete combined_nms for first_stage_nms because it does not work

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

This reverts commit 2a3cc5145f17cee630a67ddedd20e90c2920fa9f.

* Use nmsed_additional_fields.get to avoid error

* Merge combined_non_max_suppression with main nms function

* Rename combined_nms for first stage nms

* Improve  docs

* Use assertListEqual for numpy arrays

* Fix pylint errors

* End comments with period

257914648  by lzc:

    Internal changes

--
257525973  by Zhichao Lu:

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

--
257296614  by Zhichao Lu:

    Adding detection_features to model outputs

--
257234565  by Zhichao Lu:

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

--
257232002  by ronnyvotel:

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

--
257198282  by Zhichao Lu:

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

--
257089535  by Zhichao Lu:

    Create Keras based ssd + resnetv1 + fpn.

--
257087407  by Zhichao Lu:

    Make object_detection/data_decoders Python3-compatible.

--
257004582  by Zhichao Lu:

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

250447559  by Zhichao Lu:

    Update expected files format for Instance Segmentation challenge:
    - add fields ImageWidth, ImageHeight and store the values per prediction
    - as mask, store only encoded image and assume its size is ImageWidth x ImageHeight

--
250402780  by rathodv:

    Fix failing Mask R-CNN TPU convergence test.

    Cast second stage prediction tensors from bfloat16 to float32 to prevent errors in third target assignment (Mask Prediction) - Concat with different types bfloat16 and bfloat32 isn't allowed.

--
250300240  by Zhichao Lu:

    Addion Open Images Challenge 2019 object detection and instance segmentation
    support into Estimator framework.

--
249944839  by rathodv:

    Modify exporter.py to add multiclass score nodes in exported inference graphs.

--
249935201  by rathodv:

    Modify postprocess methods to preserve multiclass scores after non max suppression.

--
249878079  by Zhichao Lu:

    This CL slightly refactors some Object Detection helper functions for data creation, evaluation, and groundtruth providing.

    This will allow the eager+function custom loops to share code with the existing estimator training loops.

    Concretely we make the following changes:
    1. In input creation we separate dataset-creation into top-level helpers, and allow it to optionally accept a pre-constructed model directly instead of always creating a model from the config just for feature preprocessing.

    2. In coco evaluation we split the update_op creation into its own function, which the custom loops will call directly.

    3. In model_lib we move groundtruth providing/ datastructure munging into a helper function

    4. For now we put an escape hatch in `_summarize_target_assignment` when executing in tf v2.0 behavior because the summary apis used only work w/ tf 1.x

--
249673507  by rathodv:

    Use explicit casts instead of tf.to_float and tf.to_int32 to avoid warnings.

--
249656006  by Zhichao Lu:

    Add named "raw_keypoint_locations" node that corresponds with the "raw_box_locations" node.

--
249651674  by rathodv:

    Keep proposal boxes in float format. MatMulCropAndResize can handle the type even when feature themselves are bfloat16s.

--
249568633  by rathodv:

    Support q > 1 in class agnostic NMS.
    Break post_processing_test.py into 3 separate files to avoid linter errors.

--
249535530  by rathodv:

    Update some deprecated arguments to tf ops.

--
249368223  by rathodv:

    Modify MatMulCropAndResize to use MultiLevelRoIAlign method and move the tests to spatial_transform_ops.py module.

    This cl establishes that CropAndResize and RoIAlign are equivalent and only differ in the sampling point grid within the boxes. CropAndResize uses a uniform size x size point grid such that the corner points exactly overlap box corners, while RoiAlign divides boxes into size x size cells and uses their centers as sampling points. In this cl, we switch MatMulCropAndResize to use the MultiLevelRoIAlign implementation with `align_corner` option as MultiLevelRoIAlign implementation is more memory efficient on TPU when compared to the original MatMulCropAndResize.

--
249337338  by chowdhery:

    Add class-agnostic non-max-suppression in post_processing

--
249139196  by Zhichao Lu:

    Fix positional argument bug in export_tflite_ssd_graph

--
249120219  by Zhichao Lu:

    Add evaluator for computing precision limited to a given recall range.

--
249030593  by Zhichao Lu:

    Evaluation util to run segmentation and detection challenge evaluation.

--
248554358  by Zhichao Lu:

    This change contains the auxiliary changes required for TF 2.0 style training with eager+functions+dist strat loops, but not the loops themselves.

    It includes:
    - Updates to shape usage to support both tensorshape v1 and tensorshape v2
    - A fix to FreezableBatchNorm to not override the `training` arg in call when `None` was passed to the constructor (Not an issue in the estimator loops but it was in the custom loops)
    - Puts some constants in init_scope so they work in eager + functions
    - Makes learning rate schedules return a callable in eager mode (required so they update when the global_step changes)
    - Makes DetectionModel a tf.module so it tracks variables (e.g. ones nested in layers)
    - Removes some references to `op.name` for some losses and replaces it w/ explicit names
    - A small part of the change to allow the coco evaluation metrics to work in eager mode

--
248271226  by rathodv:

    Add MultiLevel RoIAlign op.

--
248229103  by rathodv:

    Add functions to 1. pad features maps 2. ravel 5-D indices

--
248206769  by rathodv:

    Add utilities needed to introduce RoI Align op.

--
248177733  by pengchong:

    Internal changes

--
247742582  by Zhichao Lu:

    Open Images Challenge 2019 instance segmentation metric: part 2

--
247525401  by Zhichao Lu:

    Update comments on max_class_per_detection.

--
247520753  by rathodv:

    Add multilevel crop and resize operation that builds on top of matmul_crop_and_resize.

--
247391600  by Zhichao Lu:

    Open Images Challenge 2019 instance segmentation metric

--
247325813  by chowdhery:

    Quantized MobileNet v2 SSD FPNLite config with depth multiplier 0.75

--

PiperOrigin-RevId: 250447559

247226201  by ronnyvotel:

    Updating the visualization tools to accept unique_ids for color coding.

--
247067830  by Zhichao Lu:

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

--
246888475  by Zhichao Lu:

    Remove unused _update_eval_steps function.

--
246163259  by lzc:

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

--
246084944  by Zhichao Lu:

    Keras based implementation for SSD + MobilenetV2 + FPN.

--
245544227  by rathodv:

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

--
245540854  by rathodv:

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

--
245434441  by Zhichao Lu:

    Add README for tpu_exporters package.

--
245381834  by lzc:

    Internal change.

--
245298983  by 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

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

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

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

This import from google3.third_party doesn't work.

This file was inadvertantly renamed in #6071.

As discussed here: https://github.com/tensorflow/tensorflow/issues/11312, this change allows this script to work in Python 3.

This file was re-located below the tensorflow/lite/g3doc/convert
Signed-off-by: MyungSung Kwak <yesmung@gmail.com>

* Remove duplicate elif case in _check_and_convert_legacy_input_config_key

* Remove duplicate eval_input_path case.

Fixes the variable name for the tf proto example function.

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