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* 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.

196161788  by Zhichao Lu:

    Add eval_on_train_steps parameter.

    Since the number of samples in train dataset is usually different to the number of samples in the eval dataset.

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196151742  by Zhichao Lu:

    Add an optional random sampling process for SSD meta arch and update mean stddev coder to use default std dev when corresponding tensor is not added to boxlist field.

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196148940  by Zhichao Lu:

    Release ssdlite mobilenet v2 coco trained model.

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196058528  by Zhichao Lu:

    Apply FPN feature map generation before we add additional layers on top of resnet feature extractor.

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195818367  by Zhichao Lu:

    Add support for exporting detection keypoints.

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195745420  by Zhichao Lu:

    Introduce include_metrics_per_category option to Object Detection eval_config.

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195734733  by Zhichao Lu:

    Rename SSDLite config to be more explicit.

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195717383  by Zhichao Lu:

    Add quantized training to object_detection.

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195683542  by Zhichao Lu:

    Fix documentation for the interaction of fine_tune_checkpoint_type and load_all_detection_checkpoint_vars interaction.

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195668233  by Zhichao Lu:

    Using batch size from params dictionary if present.

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195570173  by Zhichao Lu:

    A few fixes to get new estimator API eval to match legacy detection eval binary by (1) plumbing `is_crowd` annotations through to COCO evaluator, (2) setting the `sloppy` flag in tf.contrib.data.parallel_interleave based on whether shuffling is enabled, and (3) saving the original image instead of the resized original image, which allows for small/medium/large mAP metrics to be properly computed.

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195316756  by Zhichao Lu:

    Internal change

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PiperOrigin-RevId: 196161788

PiperOrigin-RevId: 185222703

184048729  by Zhichao Lu:

    Modify target_assigner so that it creates regression targets taking keypoints into account.

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184027183  by Zhichao Lu:

    Resnet V1 FPN based feature extractors for SSD meta architecture in Object Detection V2 API.

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184004730  by Zhichao Lu:

    Expose a lever to override the configured mask_type.

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183933113  by Zhichao Lu:

    Weight shared convolutional box predictor as described in https://arxiv.org/abs/1708.02002

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183929669  by Zhichao Lu:

    Expanding box list operations for future data augmentations.

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183916792  by Zhichao Lu:

    Fix unrecognized assertion function in tests.

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183906851  by Zhichao Lu:

    - Change ssd meta architecture to use regression weights to compute loss normalizer.

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183871003  by Zhichao Lu:

    Fix config_util_test wrong dependency.

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183782120  by Zhichao Lu:

    Add __init__ file to third_party directories.

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183779109  by Zhichao Lu:

    Setup regular version s...

For details see our paper:
"Speed/accuracy trade-offs for modern convolutional object detectors."
Huang J, Rathod V, Sun C, Zhu M, Korattikara A, Fathi A, Fischer I,
Wojna Z, Song Y, Guadarrama S, Murphy K, CVPR 2017
https://arxiv.org/abs/1611.10012