GitLab

257914648  by lzc:

    Internal changes

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257525973  by Zhichao Lu:

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

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257296614  by Zhichao Lu:

    Adding detection_features to model outputs

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257234565  by Zhichao Lu:

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

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257232002  by ronnyvotel:

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

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257198282  by Zhichao Lu:

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

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257089535  by Zhichao Lu:

    Create Keras based ssd + resnetv1 + fpn.

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257087407  by Zhichao Lu:

    Make object_detection/data_decoders Python3-compatible.

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257004582  by Zhichao Lu:

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

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257002124  by Zhichao Lu:

    Make object_detection/utils Python3-compatible, except json_utils.

    The patching trick used in json_utils is not going to work in Python 3.

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256795056  by lzc:

    Add a detection_anchor_indices field to detection outputs.

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256477542  by Zhichao Lu:

    Make object_detection/core Python3-compatible.

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256387593  by Zhichao Lu:

    Edit class_id_function_approximations builder to skip class ids not present in label map.

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256259039  by Zhichao Lu:

    Move NMS to TPU for FasterRCNN.

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256071360  by rathodv:

    When multiclass_scores is empty, add one-hot encoding of groundtruth_classes as multiclass scores so that data_augmentation ops that expect the presence of multiclass_scores don't have to individually handle this case.

    Also copy input tensor_dict to out_tensor_dict first to avoid inplace modification.

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256023645  by Zhichao Lu:

    Adds the first WIP iterations of TensorFlow v2 eager + functions style custom training & evaluation loops.

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255980623  by Zhichao Lu:

    Adds a new data augmentation operation "remap_labels" which remaps a set of labels to a new label.

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255753259  by Zhichao Lu:

    Announcement of the released evaluation tutorial for Open Images Challenge
    2019.

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255698776  by lzc:

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

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255623150  by Zhichao Lu:

    Add Keras-based ResnetV1 models.

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255504992  by Zhichao Lu:

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

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255470768  by Zhichao Lu:

    1. Fixing Python bug with parsed arguments.
    2. Adding capability to parse relevant columns from CSV header.
    3. Fixing bug with duplicated labels expansion.

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255462432  by Zhichao Lu:

    Adds a new data augmentation operation "drop_label_probabilistically" which drops a given label with the given probability. This supports experiments on training in the presence of label noise.

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255441632  by rathodv:

    Fallback on groundtruth classes when multiclass_scores tensor is empty.

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255434899  by Zhichao Lu:

    Ensuring evaluation binary can run even with big files by synchronizing
    processing of ground truth and predictions: in this way, ground truth is not stored but immediatly
    used for evaluation. In case gt of object masks, this allows to run
    evaluations on relatively large sets.

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255337855  by lzc:

    Internal change.

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255308908  by Zhichao Lu:

    Add comment to clarify usage of calibration parameters proto.

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255266371  by Zhichao Lu:

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

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255236648  by Zhichao Lu:

    Refactor model_builder in faster_rcnn.py to a util_map, so that it's possible to be overwritten.

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255093285  by Zhichao Lu:

    Updating capability to subsample data during evaluation

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255081222  by rathodv:

    Convert groundtruth masks to be of type float32 before its used in the loss function.

    When using mixed precision training, masks are represented using bfloat16 tensors in the input pipeline for performance reasons. We need to convert them to float32 before using it in the loss function.

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254788436  by Zhichao Lu:

    Add forward_compatible to non_max_suppression_with_scores to make it is
    compatible with older tensorflow version.

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254442362  by Zhichao Lu:

    Add num_layer field to ssd feature extractor proto.

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253911582  by jonathanhuang:

    Plumbs Soft-NMS options (using the new tf.image.non_max_suppression_with_scores op) into the TF Object Detection API.  It adds a `soft_nms_sigma` field to the postprocessing proto file and plumbs this through to both the multiclass and class_agnostic versions of NMS. Note that there is no effect on behavior of NMS when soft_nms_sigma=0 (which it is set to by default).

    See also "Soft-NMS -- Improving Object Detection With One Line of Code" by Bodla et al (https://arxiv.org/abs/1704.04503)

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253703949  by Zhichao Lu:

    Internal test fixes.

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253151266  by Zhichao Lu:

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

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252718956  by Zhichao Lu:

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

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252158593  by Zhichao Lu:

    Make object_detection/core Python3-compatible.

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252150717  by Zhichao Lu:

    Make object_detection/core Python3-compatible.

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251967048  by Zhichao Lu:

    Make GraphRewriter proto extensible.

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251950039  by Zhichao Lu:

    Remove experimental_export_device_assignment from TPUEstimator.export_savedmodel(), so as to remove rewrite_for_inference().

    As a replacement, export_savedmodel() V2 API supports device_assignment where user call tpu.rewrite in model_fn and pass in device_assigment there.

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251890697  by rathodv:

    Updated docstring to include new output nodes.

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251662894  by Zhichao Lu:

    Add autoaugment augmentation option to objection detection api codebase. This
    is an available option in preprocessor.py.

    The intended usage of autoaugment is to be done along with random flipping and
    cropping for best results.

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251532908  by Zhichao Lu:

    Add TrainingDataType enum to track whether class-specific or agnostic data was used to fit the calibration function.

    This is useful, since classes with few observations may require a calibration function fit on all classes.

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251511339  by Zhichao Lu:

    Add multiclass isotonic regression to the calibration builder.

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251317769  by pengchong:

    Internal Change.

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250729989  by Zhichao Lu:

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

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250729627  by Zhichao Lu:

    Label expansion for segmentation.

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250724905  by Zhichao Lu:

    Fix use_depthwise in fpn and test it with fpnlite on ssd + mobilenet v2.

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250670379  by Zhichao Lu:

    Internal change

250630364  by lzc:

    Fix detection_model_zoo footnotes

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250560654  by Zhichao Lu:

    Fix static shape issue in matmul_crop_and_resize.

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250534857  by Zhichao Lu:

    Edit class agnostic calibration function docstring to more accurately describe the function's outputs.

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250533277  by Zhichao Lu:

    Edit the multiclass messages to use class ids instead of labels.

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PiperOrigin-RevId: 257914648

* Merged commit includes the following changes:
204316992  by Zhichao Lu:

    Update docs to prepare inputs

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204309254  by Zhichao Lu:

    Update running_pets.md to use new binaries and correct a few things in running_on_cloud.md

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204306734  by Zhichao Lu:

    Move old binaries into legacy folder and add deprecation notice.

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204267757  by Zhichao Lu:

    Fixing a problem in VRD evaluation with missing ground truth annotations for
    images that do not contain objects from 62 groundtruth classes.

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204167430  by Zhichao Lu:

    This fixes a flaky losses test failure.

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203670721  by Zhichao Lu:

    Internal change.

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203569388  by Zhichao Lu:

    Internal change

203546580  by Zhichao Lu:

    * Expand TPU compatibility g3doc with config snippets
    * Change mscoco dataset path in sample configs to the sharded versions

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203325694  by Zhichao Lu:

    Make merge_multiple_label_boxes work for model_main code path.

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203305655  by Zhichao Lu:

    Remove the 1x1 conv layer before pooling in MobileNet-v1-PPN feature extractor.

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203139608  by Zhichao Lu:

    - Support exponential_decay with burnin learning rate schedule.
    - Add the minimum learning rate option.
    - Make the exponential decay start only after the burnin steps.

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203068703  by Zhichao Lu:

    Modify create_coco_tf_record.py to output sharded files.

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203025308  by Zhichao Lu:

    Add an option to share the prediction tower in WeightSharedBoxPredictor.

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203024942  by Zhichao Lu:

    Move ssd mobilenet v1 ppn configs to third party.

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202901259  by Zhichao Lu:

    Delete obsolete ssd mobilenet v1 focal loss configs and update pets dataset path

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202894154  by Zhichao Lu:

    Move all TPU compatible ssd mobilenet v1 coco14/pet configs to third party.

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202861774  by Zhichao Lu:

    Move Retinanet (SSD + FPN + Shared box predictor) configs to third_party.

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PiperOrigin-RevId: 204316992

* Add original files back.

* Merged commit includes the following changes:
202804536  by Zhichao Lu:

    Return tf.data.Dataset from input_fn that goes into the estimator and use PER_HOST_V2 option for tpu input pipeline config.

    This change shaves off 100ms per step resulting in 25 minutes of total reduced training time for ssd mobilenet v1 (15k steps to convergence).

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202769340  by Zhichao Lu:

    Adding as_matrix() transformation for image-level labels.

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202768721  by Zhichao Lu:

    Challenge evaluation protocol modification: adding labelmaps creation.

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202750966  by Zhichao Lu:

    Add the explicit names to two output nodes.

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202732783  by Zhichao Lu:

    Enforcing that batch size is 1 for evaluation, and no original images are retained during evaluation when use_tpu=False (to avoid dynamic shapes).

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202425430  by Zhichao Lu:

    Refactor input pipeline to improve performance.

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202406389  by Zhichao Lu:

    Only check the validity of `warmup_learning_rate` if it will be used.

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202330450  by Zhichao Lu:

    Adding the description of the flag input_image_label_annotations_csv to add
      image-level labels to tf.Example.

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202029012  by Zhichao Lu:

    Enabling displaying relationship name in the final metrics output.

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202024010  by Zhichao Lu:

    Update to the public README.

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201999677  by Zhichao Lu:

    Fixing the way negative labels are handled in VRD evaluation.

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201962313  by Zhichao Lu:

    Fix a bug in resize_to_range.

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201808488  by Zhichao Lu:

    Update ssd_inception_v2_pets.config to use right filename of pets dataset tf records.

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201779225  by Zhichao Lu:

    Update object detection API installation doc

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201766518  by Zhichao Lu:

    Add shell script to create pycocotools package for CMLE.

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201722377  by Zhichao Lu:

    Removes verified_labels field and uses groundtruth_image_classes field instead.

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201616819  by Zhichao Lu:

    Disable eval_on_tpu since eval_metrics is not setup to execute on TPU.
    Do not use run_config.task_type to switch tpu mode for EVAL,
    since that won't work in unit test.
    Expand unit test to verify that the same instantiation of the Estimator can independently disable eval on TPU whereas training is enabled on TPU.

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201524716  by Zhichao Lu:

    Disable export model to TPU, inference is not compatible with TPU.
    Add GOOGLE_INTERNAL support in object detection copy.bara.sky

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201453347  by Zhichao Lu:

    Fixing bug when evaluating the quantized model.

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200795826  by Zhichao Lu:

    Fixing parsing bug: image-level labels are parsed as tuples instead of numpy
    array.

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200746134  by Zhichao Lu:

    Adding image_class_text and image_class_label fields into tf_example_decoder.py

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200743003  by Zhichao Lu:

    Changes to model_main.py and model_tpu_main to enable training and continuous eval.

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200736324  by Zhichao Lu:

    Replace deprecated squeeze_dims argument.

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200730072  by Zhichao Lu:

    Make detections only during predict and eval mode while creating model function

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200729699  by Zhichao Lu:

    Minor correction to internal documentation (definition of Huber loss)

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200727142  by Zhichao Lu:

    Add command line parsing as a set of flags using argparse and add header to the
    resulting file.

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200726169  by Zhichao Lu:

    A tutorial on running evaluation for the Open Images Challenge 2018.

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200665093  by Zhichao Lu:

    Cleanup on variables_helper_test.py.

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200652145  by Zhichao Lu:

    Add an option to write (non-frozen) graph when exporting inference graph.

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200573810  by Zhichao Lu:

    Update ssd_mobilenet_v1_coco and ssd_inception_v2_coco download links to point to a newer version.

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200498014  by Zhichao Lu:

    Add test for groundtruth mask resizing.

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200453245  by Zhichao Lu:

    Cleaning up exporting_models.md along with exporting scripts

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200311747  by Zhichao Lu:

    Resize groundtruth mask to match the size of the original image.

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200287269  by Zhichao Lu:

    Having a option to use custom MatMul based crop_and_resize op as an alternate to the TF op in Faster-RCNN

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200127859  by Zhichao Lu:

    Updating the instructions to run locally with new binary. Also updating pets configs since file path naming has changed.

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200127044  by Zhichao Lu:

    A simpler evaluation util to compute Open Images Challenge
    2018 metric (object detection track).

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200124019  by Zhichao Lu:

    Freshening up configuring_jobs.md

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200086825  by Zhichao Lu:

    Make merge_multiple_label_boxes work for ssd model.

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199843258  by Zhichao Lu:

    Allows inconsistent feature channels to be compatible with WeightSharedConvolutionalBoxPredictor.

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199676082  by Zhichao Lu:

    Enable an override for `InputReader.shuffle` for object detection pipelines.

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199599212  by Zhichao Lu:

    Markdown fixes.

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199535432  by Zhichao Lu:

    Pass num_additional_channels to tf.example decoder in predict_input_fn.

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199399439  by Zhichao Lu:

    Adding `num_additional_channels` field to specify how many additional channels to use in the model.

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PiperOrigin-RevId: 202804536

* Add original model builder and docs back.

199348852  by Zhichao Lu:

    Small typos fixes in VRD evaluation.

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199315191  by Zhichao Lu:

    Change padding shapes when additional channels are available.

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199309180  by Zhichao Lu:

    Adds minor fixes to the Object Detection API implementation.

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199298605  by Zhichao Lu:

    Force num_readers to be 1 when only input file is not sharded.

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199292952  by Zhichao Lu:

    Adds image-level labels parsing into TfExampleDetectionAndGTParser.

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199259866  by Zhichao Lu:

    Visual Relationships Evaluation executable.

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199208330  by Zhichao Lu:

    Infer train_config.batch_size as the effective batch size. Therefore we need to divide the effective batch size in trainer by train_config.replica_to_aggregate to get per worker batch size.

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199207842  by Zhichao Lu:

    Internal change.

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199204222  by Zhichao Lu:

    In case the image has more than three channels, we only take the first three channels for visualization.

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199194388  by Zhichao Lu:

    Correcting protocols description: VOC 2007 -> VOC 2012.

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199188290  by Zhichao Lu:

    Adds per-relationship APs and mAP computation to VRD evaluation.

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199158801  by Zhichao Lu:

    If available, additional channels are merged with input image.

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199099637  by Zhichao Lu:

    OpenImages Challenge metric support:
    -adding verified labels standard field for TFExample;
    -adding tfrecord creation functionality.

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198957391  by Zhichao Lu:

    Allow tf record sharding when creating pets dataset.

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198925184  by Zhichao Lu:

    Introduce moving average support for evaluation. Also adding the ability to override this configuration via config_util.

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198918186  by Zhichao Lu:

    Handles the case where there are 0 box masks.

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198809009  by Zhichao Lu:

    Plumb groundtruth weights into target assigner for Faster RCNN.

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198759987  by Zhichao Lu:

    Fix object detection test broken by shape inference.

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198668602  by Zhichao Lu:

    Adding a new input field in data_decoders/tf_example_decoder.py for storing additional channels.

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198530013  by Zhichao Lu:

    An util for hierarchical expandion of boxes and labels of OID dataset.

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198503124  by Zhichao Lu:

    Fix dimension mismatch error introduced by
    https://github.com/tensorflow/tensorflow/pull/18251, or cl/194031845.
    After above change, conv2d strictly checks for conv_dims + 2 == input_rank.

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198445807  by Zhichao Lu:

    Enabling Object Detection Challenge 2018 metric in evaluator.py framework for
    running eval job.
    Renaming old OpenImages V2 metric.

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198413950  by Zhichao Lu:

    Support generic configuration override using namespaced keys

    Useful for adding custom hyper-parameter tuning fields without having to add custom override methods to config_utils.py.

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198106437  by Zhichao Lu:

    Enable fused batchnorm now that quantization is supported.

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198048364  by Zhichao Lu:

    Add support for keypoints in tf sequence examples and some util ops.

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198004736  by Zhichao Lu:

    Relax postprocessing unit tests that are based on assumption that tf.image.non_max_suppression are stable with respect to input.

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197997513  by Zhichao Lu:

    More lenient validation for normalized box boundaries.

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197940068  by Zhichao Lu:

    A couple of minor updates/fixes:
    - Updating input reader proto with option to use display_name when decoding data.
    - Updating visualization tool to specify whether using absolute or normalized box coordinates. Appropriate boxes will now appear in TB when using model_main.py

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197920152  by Zhichao Lu:

    Add quantized training support in the new OD binaries and a config for SSD Mobilenet v1 quantized training that is TPU compatible.

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197213563  by Zhichao Lu:

    Do not share batch_norm for classification and regression tower in weight shared box predictor.

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197196757  by Zhichao Lu:

    Relax the box_predictor api to return box_prediction of shape [batch_size, num_anchors, code_size] in addition to [batch_size, num_anchors, (1|q), code_size].

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196898361  by Zhichao Lu:

    Allow per-channel scalar value to pad input image with when using keep aspect ratio resizer (when pad_to_max_dimension=True).

    In Object Detection Pipeline, we pad image before normalization and this skews batch_norm statistics during training. The option to set per channel pad value lets us truly pad with zeros.

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196592101  by Zhichao Lu:

    Fix bug regarding tfrecord shuffling in object_detection

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196320138  by Zhichao Lu:

    Fix typo in exporting_models.md

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PiperOrigin-RevId: 199348852