GitLab

PiperOrigin-RevId: 190996725

PiperOrigin-RevId: 190972737

Updating model to infer when labels are padded, rather than relying solely on the mode. This is necessary for evaluating on train data.

PiperOrigin-RevId: 190960173

Use keyword arguments in model builder for ssd feature extractor. This was incorreclty setting reuse argument.

PiperOrigin-RevId: 190940462

PiperOrigin-RevId: 190790653

Removing flag defaults for train steps and eval steps. If not provided, will revert to the values specified in the config.

PiperOrigin-RevId: 190706470

PiperOrigin-RevId: 190705850

PiperOrigin-RevId: 190688309

PiperOrigin-RevId: 190682119

Add warning if shuffle=false but num_readers > 1. The latter would cause the input data stream to still be shuffled.

PiperOrigin-RevId: 190678792

PiperOrigin-RevId: 190651873

PiperOrigin-RevId: 190636417

Cython is must installed package for building cocoapi. else the build will not
initiate.

PiperOrigin-RevId: 190553060

Tfmini requires positive values for the dimensions. Therefore, we need to test for no paddings in both width and height direction.

PiperOrigin-RevId: 190520529

PiperOrigin-RevId: 190505306

Switch line orders in trainer so that restore_map is called after moving average variables are created.

Moving averages are now properly loaded during fine-tuning, instead of being recreated.

PiperOrigin-RevId: 190496046

PiperOrigin-RevId: 190292280

PiperOrigin-RevId: 190115628

PiperOrigin-RevId: 190098000

The C API improves static shape inference, making more errors caught at graph construction time instead of runtime.

PiperOrigin-RevId: 190095450

PiperOrigin-RevId: 190068159

PiperOrigin-RevId: 190002150

PiperOrigin-RevId: 189997094

PiperOrigin-RevId: 189933390

PiperOrigin-RevId: 189929413

PiperOrigin-RevId: 189815553

Updating transform_input_data to resize original image. This is necessary for result_dict_for_single_example(), since it expects the input image and groundtruth masks to be of the same spatial dimensions.

PiperOrigin-RevId: 189786443

Enabling both train and eval image summaries. Note that eval summaries are not created tf-learn environment. To get them to show up, added the summary image into the eval_metric_ops.

PiperOrigin-RevId: 189658259

syntax error : download_and_convert_VOC2012.sh

Add mobilenetv2 support in deeplab

Fix DeprecationWarning

Update comment on folder structure

Updated README run instructions

Add a tf.summary.scalar call for L2 loss in resnet

from six.moves import xrange (en masse) YET AGAIN

* Force cast of num_classes to integer

PiperOrigin-RevId: 188335318

* Updating config util to allow overwriting of cosine decay learning rates.

PiperOrigin-RevId: 188338852

* Make box_list_ops.py and box_list_ops_test.py work with C API enabled.

The C API has improved shape inference over the original Python
code. This causes some previously-working conds to fail. Switching to smart_cond fixes this.

Another effect of the improved shape inference is that one of the
failures tested gets caught earlier, so I modified the test to reflect
this.

PiperOrigin-RevId: 188409792

* Fix parallel event file writing issue.

Without this change, the event files might get corrupted when multiple evaluations are run in parallel.

PiperOrigin-RevId: 188502560

* Deprecating the boolean flag of from_detection_checkpoint.

Replace with a string field fine_tune_checkpoint_type to train_config to provide extensibility. The fine_tune_checkpoint_type can currently take value of `detection`, `classification`, or others when the restore_map is overwritten.

PiperOrigin-RevId: 188518685

* Automated g4 rollback of changelist 188502560

PiperOrigin-RevId: 188519969

* Introducing eval metrics specs for Coco Mask metrics. This allows metrics to be computed in tensorflow using the tf.learn Estimator.

PiperOrigin-RevId: 188528485

* Minor fix to make object_detection/metrics/coco_evaluation.py python3 compatible.

PiperOrigin-RevId: 188550683

* Updating eval_util to handle eval_metric_ops from multiple `DetectionEvaluator`s.

PiperOrigin-RevId: 188560474

* Allow tensor input for new_height and new_width for resize_image.

PiperOrigin-RevId: 188561908

* Fix typo in fine_tune_checkpoint_type name in trainer.

PiperOrigin-RevId: 188799033

* Adding mobilenet feature extractor to object detection.

PiperOrigin-RevId: 188916897

* Allow label maps to optionally contain an explicit background class with id zero.

PiperOrigin-RevId: 188951089

* Fix boundary conditions in random_pad_to_aspect_ratio to ensure that min_scale is always less than max_scale.

PiperOrigin-RevId: 189026868

* Fallback on from_detection_checkpoint option if fine_tune_checkpoint_type isn't set.

PiperOrigin-RevId: 189052833

* Add proper names for learning rate schedules so we don't see cryptic names on tensorboard.

PiperOrigin-RevId: 189069837

* Enforcing that all datasets are batched (and then unbatched in the model) with batch_size >= 1.

PiperOrigin-RevId: 189117178

* Adding regularization to total loss returned from DetectionModel.loss().

PiperOrigin-RevId: 189189123

* Standardize the names of loss scalars (for SSD, Faster R-CNN and R-FCN) in both training and eval so they can be compared on tensorboard.

Log localization and classification losses in evaluation.

PiperOrigin-RevId: 189189940

* Remove negative test from box list ops test.

PiperOrigin-RevId: 189229327

* Add an option to warmup learning rate in manual stepping schedule.

PiperOrigin-RevId: 189361039

* Replace tf.contrib.slim.tfexample_decoder.LookupTensor with object_detection.data_decoders.tf_example_decoder.LookupTensor.

PiperOrigin-RevId: 189388556

* Force regularization summary variables under specific family names.

PiperOrigin-RevId: 189393190

* Automated g4 rollback of changelist 188619139

PiperOrigin-RevId: 189396001

* Remove step 0 schedule since we do a hard check for it after cl/189361039

PiperOrigin-RevId: 189396697

* PiperOrigin-RevId: 189040463

* PiperOrigin-RevId: 189059229

* PiperOrigin-RevId: 189214402

* Force regularization summary variables under specific family names.

PiperOrigin-RevId: 189393190

* Automated g4 rollback of changelist 188619139

PiperOrigin-RevId: 189396001

* Make slim python3 compatible.

* Monir fixes.

* Add TargetAssignment summaries in a separate family.

PiperOrigin-RevId: 189407487

* 1. Setting `family` keyword arg prepends the summary names twice with the same name. Directly adding family suffix to the name gets rid of this problem.
2. Make sure the eval losses have the same name.

PiperOrigin-RevId: 189434618

* Minor fixes to make object detection tf 1.4 compatible.

PiperOrigin-RevId: 189437519

* Call the base of mobilenet_v1 feature extractor under the right arg scope and set batchnorm is_training based on the value passed in the constructor.

PiperOrigin-RevId: 189460890

* Automated g4 rollback of changelist 188409792

PiperOrigin-RevId: 189463882

* Update object detection syncing.

PiperOrigin-RevId: 189601955

* Add an option to warmup learning rate, hold it constant for a certain number of steps and cosine decay it.

PiperOrigin-RevId: 189606169

* Let the proposal feature extractor function in faster_rcnn meta architectures return the activations (end_points).

PiperOrigin-RevId: 189619301

* Fixed bug which caused masks to be mostly zeros (caused by detection_boxes being in absolute coordinates if scale_to_absolute=True.

PiperOrigin-RevId: 189641294

* Open sourcing Mobilenetv2 + SSDLite.

PiperOrigin-RevId: 189654520

* Remove unused files.

fix bugs in Python 3.X

Edit comment on folder structure to match actual folder structure.