- 08 3月, 2019 1 次提交
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由 pkulzc 提交于
236813471 by lzc: Internal change. -- 236507310 by lzc: Fix preprocess.random_resize_method config type issue. The target height and width will be passed as "size" to tf.image.resize_images which only accepts integer. -- 236409989 by Zhichao Lu: Config export_to_tpu from function parameter instead of HParams for TPU inference. -- 236403186 by Zhichao Lu: Make graph file names optional arguments. -- 236237072 by Zhichao Lu: Minor bugfix for keyword args. -- 236209602 by Zhichao Lu: Add support for PartitionedVariable to get_variables_available_in_checkpoint. -- 235828658 by Zhichao Lu: Automatically stop evaluation jobs when training is finished. -- 235817964 by Zhichao Lu: Add an optional process_metrics_fn callback to eval_util, it gets called with evaluation results once each evaluation is complete. -- 235788721 by lzc: Fix yml file tf runtime version. -- 235262897 by Zhichao Lu: Add keypoint support to the random_pad_image preprocessor method. -- 235257380 by Zhichao Lu: Support InputDataFields.groundtruth_confidences in retain_groundtruth(), retain_groundtruth_with_positive_classes(), filter_groundtruth_with_crowd_boxes(), filter_groundtruth_with_nan_box_coordinates(), filter_unrecognized_classes(). -- 235109188 by Zhichao Lu: Fix bug in pad_input_data_to_static_shapes for num_additional_channels > 0; make color-specific data augmentation only touch RGB channels. -- 235045010 by Zhichao Lu: Don't slice class_predictions_with_background when add_background_class is false. -- 235026189 by lzc: Fix import in g3doc. -- 234863426 by Zhichao Lu: Added fixes in exporter to allow writing a checkpoint to a specified temporary directory. -- 234671886 by lzc: Internal Change. -- 234630803 by rathodv: Internal Change. -- 233985896 by Zhichao Lu: Add Neumann optimizer to object detection. -- 233560911 by Zhichao Lu: Add NAS-FPN object detection with Resnet and Mobilenet v2. -- 233513536 by Zhichao Lu: Export TPU compatible object detection model -- 233495772 by lzc: Internal change. -- 233453557 by Zhichao Lu: Create Keras-based SSD+MobilenetV1 for object detection. -- 233220074 by lzc: Update release notes date. -- 233165761 by Zhichao Lu: Support depth_multiplier and min_depth in _SSDResnetV1FpnFeatureExtractor. -- 233160046 by lzc: Internal change. -- 232926599 by Zhichao Lu: [tf.data] Switching tf.data functions to use `defun`, providing an escape hatch to continue using the legacy `Defun`. There are subtle differences between the implementation of `defun` and `Defun` (such as resources handling or control flow) and it is possible that input pipelines that use control flow or resources in their functions might be affected by this change. To migrate majority of existing pipelines to the recommended way of creating functions in TF 2.0 world, while allowing (a small number of) existing pipelines to continue relying on the deprecated behavior, this CL provides an escape hatch. If your input pipeline is affected by this CL, it should apply the escape hatch by replacing `foo.map(...)` with `foo.map_with_legacy_function(...)`. -- 232891621 by Zhichao Lu: Modify faster_rcnn meta architecture to normalize raw detections. -- 232875817 by Zhichao Lu: Make calibration a post-processing step. Specifically: - Move the calibration config from pipeline.proto --> post_processing.proto - Edit post_processing_builder.py to return a calibration function. If no calibration config is provided, it None. - Edit SSD and FasterRCNN meta architectures to optionally call the calibration function on detection scores after score conversion and before NMS. -- 232704481 by Zhichao Lu: Edit calibration builder to build a function that will be used within a detection model's `postprocess` method, after score conversion and before non-maxima suppression. Specific Edits: - The returned function now accepts class_predictions_with_background as its argument instead of detection_scores and detection_classes. - Class-specific calibration was temporarily removed, as it requires more significant refactoring. Will be added later. -- 232615379 by Zhichao Lu: Internal change -- 232483345 by ronnyvotel: Making the use of bfloat16 restricted to TPUs. -- 232399572 by Zhichao Lu: Edit calibration builder and proto to support class-agnostic calibration. Specifically: - Edit calibration protos to include path to relevant label map if required for class-specific calibration. Previously, label maps were inferred from other parts of the pipeline proto; this allows all information required by the builder stay within the calibration proto and remove extraneous information from being passed with class-agnostic calibration. - Add class-agnostic protos to the calibration config. Note that the proto supports sigmoid and linear interpolation parameters, but the builder currently only supports linear interpolation. -- 231613048 by Zhichao Lu: Add calibration builder for applying calibration transformations from output of object detection models. Specifically: - Add calibration proto to support sigmoid and isotonic regression (stepwise function) calibration. - Add a builder to support calibration from isotonic regression outputs. -- 231519786 by lzc: model_builder test refactor. - removed proto text boilerplate in each test case and let them call a create_default_proto function instead. - consolidated all separate ssd model creation tests into one. - consolidated all separate faster rcnn model creation tests into one. - used parameterized test for testing mask rcnn models and use_matmul_crop_and_resize - added all failures test. -- 231448169 by Zhichao Lu: Return static shape as a constant tensor. -- 231423126 by lzc: Add a release note for OID v4 models. -- 231401941 by Zhichao Lu: Adding correct labelmap for the models trained on Open Images V4 (*oid_v4 config suffix). -- 231320357 by Zhichao Lu: Add scope to Nearest Neighbor Resize op so that it stays in the same name scope as the original resize ops. -- 231257699 by Zhichao Lu: Switch to using preserve_aspect_ratio in tf.image.resize_images rather than using a custom implementation. -- 231247368 by rathodv: Internal change. -- 231004874 by lzc: Update documentations to use tf 1.12 for object detection API. -- 230999911 by rathodv: Use tf.batch_gather instead of ops.batch_gather -- 230999720 by huizhongc: Fix weight equalization test in ops_test. -- 230984728 by rathodv: Internal update. -- 230929019 by lzc: Add an option to replace preprocess operation with placeholder for ssd feature extractor. -- 230845266 by lzc: Require tensorflow version 1.12 for object detection API and rename keras_applications to keras_models -- 230392064 by lzc: Add RetinaNet 101 checkpoint trained on OID v4 to detection model zoo. -- 230014128 by derekjchow: This file was re-located below the tensorflow/lite/g3doc/convert -- 229941449 by lzc: Update SSD mobilenet v2 quantized model download path. -- 229843662 by lzc: Add an option to use native resize tf op in fpn top-down feature map generation. -- 229636034 by rathodv: Add deprecation notice to a few old parameters in train.proto -- 228959078 by derekjchow: Remove duplicate elif case in _check_and_convert_legacy_input_config_key -- 228749719 by rathodv: Minor refactoring to make exporter's `build_detection_graph` method public. -- 228573828 by rathodv: Mofity model.postprocess to return raw detections and raw scores. Modify, post-process methods in core/model.py and the meta architectures to export raw detection (without any non-max suppression) and raw multiclass score logits for those detections. -- 228420670 by Zhichao Lu: Add shims for custom architectures for object detection models. -- 228241692 by Zhichao Lu: Fix the comment on "losses_mask" in "Loss" class. -- 228223810 by Zhichao Lu: Support other_heads' predictions in WeightSharedConvolutionalBoxPredictor. Also remove a few unused parameters and fix a couple of comments in convolutional_box_predictor.py. -- 228200588 by Zhichao Lu: Add Expected Calibration Error and an evaluator that calculates the metric for object detections. -- 228167740 by lzc: Add option to use bounded activations in FPN top-down feature map generation. -- 227767700 by rathodv: Internal. -- 226295236 by Zhichao Lu: Add Open Image V4 Resnet101-FPN training config to third_party -- 226254842 by Zhichao Lu: Fix typo in documentation. -- 225833971 by Zhichao Lu: Option to have no resizer in object detection model. -- 225824890 by lzc: Fixes p3 compatibility for model_lib.py -- 225760897 by menglong: normalizer should be at least 1. -- 225559842 by menglong: Add extra logic filtering unrecognized classes. -- 225379421 by lzc: Add faster_rcnn_inception_resnet_v2_atrous_oid_v4 config to third_party -- 225368337 by Zhichao Lu: Add extra logic filtering unrecognized classes. -- 225341095 by Zhichao Lu: Adding Open Images V4 models to OD API model zoo and corresponding configs to the configs. -- 225218450 by menglong: Add extra logic filtering unrecognized classes. -- 225057591 by Zhichao Lu: Internal change. -- 224895417 by rathodv: Internal change. -- 224209282 by Zhichao Lu: Add two data augmentations to object detection: (1) Self-concat (2) Absolute pads. -- 224073762 by Zhichao Lu: Do not create tf.constant until _generate() is actually called in the object detector. -- PiperOrigin-RevId: 236813471
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- 22 9月, 2018 2 次提交
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由 pkulzc 提交于
214018767 by Zhichao Lu: Add original_image_spatial_shape tensor in input dictionary to store shape of the original input image -- 213914693 by lzc: Internal change. -- 213872175 by Zhichao Lu: This CL adds a Keras-based mobilenet_v2 feature extractor for object detection models. As part of this CL, we use the Keras mobilenet_v2 application's keyword argument layer injection API to allow the generated network to support the object detection hyperparameters. -- 213848499 by Zhichao Lu: Replace tf.image.resize_nearest_neighbor with tf.image.resize_images. tf.image.resize_nearest_neighbor only supports 4-D tensors but masks is a 3-D tensor. -- 213758622 by lzc: Internal change. -- PiperOrigin-RevId: 214018767
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由 pkulzc 提交于
Release iNaturalist Species-trained models, refactor of evaluation, box predictor for object detection. (#5289) * Merged commit includes the following changes: 212389173 by Zhichao Lu: 1. Replace tf.boolean_mask with tf.where -- 212282646 by Zhichao Lu: 1. Fix a typo in model_builder.py and add a test to cover it. -- 212142989 by Zhichao Lu: Only resize masks in meta architecture if it has not already been resized in the input pipeline. -- 212136935 by Zhichao Lu: Choose matmul or native crop_and_resize in the model builder instead of faster r-cnn meta architecture. -- 211907984 by Zhichao Lu: Make eval input reader repeated field and update config util to handle this field. -- 211858098 by Zhichao Lu: Change the implementation of merge_boxes_with_multiple_labels. -- 211843915 by Zhichao Lu: Add Mobilenet v2 + FPN support. -- 211655076 by Zhichao Lu: Bug fix for generic keys in config overrides In generic configuration overrides, we had a duplicate entry for train_input_config and we were missing the eval_input_config and eval_config. This change also introduces testing for all config overrides. -- 211157501 by Zhichao Lu: Make the locally-modified conv defs a copy. So that it doesn't modify MobileNet conv defs globally for other code that transitively imports this package. -- 211112813 by Zhichao Lu: Refactoring visualization tools for Estimator's eval_metric_ops. This will make it easier for future models to take advantage of a single interface and mechanics. -- 211109571 by Zhichao Lu: A test decorator. -- 210747685 by Zhichao Lu: For FPN, when use_depthwise is set to true, use slightly modified mobilenet v1 config. -- 210723882 by Zhichao Lu: Integrating the losses mask into the meta architectures. When providing groundtruth, one can optionally specify annotation information (i.e. which images are labeled vs. unlabeled). For any image that is unlabeled, there is no loss accumulation. -- 210673675 by Zhichao Lu: Internal change. -- 210546590 by Zhichao Lu: Internal change. -- 210529752 by Zhichao Lu: Support batched inputs with ops.matmul_crop_and_resize. With this change the new inputs are images of shape [batch, heigh, width, depth] and boxes of shape [batch, num_boxes, 4]. The output tensor is of the shape [batch, num_boxes, crop_height, crop_width, depth]. -- 210485912 by Zhichao Lu: Fix TensorFlow version check in object_detection_tutorial.ipynb -- 210484076 by Zhichao Lu: Reduce TPU memory required for single image matmul_crop_and_resize. Using tf.einsum eliminates intermediate tensors, tiling and expansion. for an image of size [40, 40, 1024] and boxes of shape [300, 4] HBM memory usage goes down from 3.52G to 1.67G. -- 210468361 by Zhichao Lu: Remove PositiveAnchorLossCDF/NegativeAnchorLossCDF to resolve "Main thread is not in main loop error" issue in local training. -- 210100253 by Zhichao Lu: Pooling pyramid feature maps: add option to replace max pool with convolution layers. -- 209995842 by Zhichao Lu: Fix a bug which prevents variable sharing in Faster RCNN. -- 209965526 by Zhichao Lu: Add support for enabling export_to_tpu through the estimator. -- 209946440 by Zhichao Lu: Replace deprecated tf.train.Supervisor with tf.train.MonitoredSession. MonitoredSession also takes away the hassle of starting queue runners. -- 209888003 by Zhichao Lu: Implement function to handle data where source_id is not set. If the field source_id is found to be the empty string for any image during runtime, it will be replaced with a random string. This avoids hash-collisions on dataset where many examples do not have source_id set. Those hash-collisions have unintended site effects and may lead to bugs in the detection pipeline. -- 209842134 by Zhichao Lu: Converting loss mask into multiplier, rather than using it as a boolean mask (which changes tensor shape). This is necessary, since other utilities (e.g. hard example miner) require a loss matrix with the same dimensions as the original prediction tensor. -- 209768066 by Zhichao Lu: Adding ability to remove loss computation from specific images in a batch, via an optional boolean mask. -- 209722556 by Zhichao Lu: Remove dead code. (_USE_C_API was flipped to True by default in TensorFlow 1.8) -- 209701861 by Zhichao Lu: This CL cleans-up some tf.Example creation snippets, by reusing the convenient tf.train.Feature building functions in dataset_util. -- 209697893 by Zhichao Lu: Do not overwrite num_epoch for eval input. This leads to errors in some cases. -- 209694652 by Zhichao Lu: Sample boxes by jittering around the currently given boxes. -- 209550300 by Zhichao Lu: `create_category_index_from_labelmap()` function now accepts `use_display_name` parameter. Also added create_categories_from_labelmap function for convenience -- 209490273 by Zhichao Lu: Check result_dict type before accessing image_id via key. -- 209442529 by Zhichao Lu: Introducing the capability to sample examples for evaluation. This makes it easy to specify one full epoch of evaluation, or a subset (e.g. sample 1 of every N examples). -- 208941150 by Zhichao Lu: Adding the capability of exporting the results in json format. -- 208888798 by Zhichao Lu: Fixes wrong dictionary key for num_det_boxes_per_image. -- 208873549 by Zhichao Lu: Reduce the number of HLO ops created by matmul_crop_and_resize. Do not unroll along the channels dimension. Instead, transpose the input image dimensions, apply tf.matmul and transpose back. The number of HLO instructions for 1024 channels reduce from 12368 to 110. -- 208844315 by Zhichao Lu: Add an option to use tf.non_maximal_supression_padded in SSD post-process -- 208731380 by Zhichao Lu: Add field in box_predictor config to enable mask prediction and update builders accordingly. -- 208699405 by Zhichao Lu: This CL creates a keras-based multi-resolution feature map extractor. -- 208557208 by Zhichao Lu: Add TPU tests for Faster R-CNN Meta arch. * Tests that two_stage_predict and total_loss tests run successfully on TPU. * Small mods to multiclass_non_max_suppression to preserve static shapes. -- 208499278 by Zhichao Lu: This CL makes sure the Keras convolutional box predictor & head layers apply activation layers *after* normalization (as opposed to before). -- 208391694 by Zhichao Lu: Updating visualization tool to produce multiple evaluation images. -- 208275961 by Zhichao Lu: This CL adds a Keras version of the Convolutional Box Predictor, as well as more general infrastructure for making Keras Prediction heads & Keras box predictors. -- 208275585 by Zhichao Lu: This CL enables the Keras layer hyperparameter object to build a dedicated activation layer, and to disable activation by default in the op layer construction kwargs. This is necessary because in most cases the normalization layer must be applied before the activation layer. So, in Keras models we must set the convolution activation in a dedicated layer after normalization is applied, rather than setting it in the convolution layer construction args. -- 208263792 by Zhichao Lu: Add a new SSD mask meta arch that can predict masks for SSD models. Changes including: - overwrite loss function to add mask loss computation. - update ssd_meta_arch to handle masks if predicted in predict and postprocessing. -- 208000218 by Zhichao Lu: Make FasterRCNN choose static shape operations only in training mode. -- 207997797 by Zhichao Lu: Add static boolean_mask op to box_list_ops.py and use that in faster_rcnn_meta_arch.py to support use_static_shapes option. -- 207993460 by Zhichao Lu: Include FGVC detection models in model zoo. -- 207971213 by Zhichao Lu: remove the restriction to run tf.nn.top_k op on CPU -- 207961187 by Zhichao Lu: Build the first stage NMS function in the model builder and pass it to FasterRCNN meta arch. -- 207960608 by Zhichao Lu: Internal Change. -- 207927015 by Zhichao Lu: Have an option to use the TPU compatible NMS op cl/206673787, in the batch_multiclass_non_max_suppression function. On setting pad_to_max_output_size to true, the output nmsed boxes are padded to be of length max_size_per_class. This can be used in first stage Region Proposal Network in FasterRCNN model by setting the first_stage_nms_pad_to_max_proposals field to true in config proto. -- 207809668 by Zhichao Lu: Add option to use depthwise separable conv instead of conv2d in FPN and WeightSharedBoxPredictor. More specifically, there are two related configs: - SsdFeatureExtractor.use_depthwise - WeightSharedConvolutionalBoxPredictor.use_depthwise -- 207808651 by Zhichao Lu: Fix the static balanced positive negative sampler's TPU tests -- 207798658 by Zhichao Lu: Fixes a post-refactoring bug where the pre-prediction convolution layers in the convolutional box predictor are ignored. -- 207796470 by Zhichao Lu: Make slim endpoints visible in FasterRCNNMetaArch. -- 207787053 by Zhichao Lu: Refactor ssd_meta_arch so that the target assigner instance is passed into the SSDMetaArch constructor rather than constructed inside. -- PiperOrigin-RevId: 212389173 * Fix detection model zoo typo. * Modify tf example decoder to handle label maps with either `display_name` or `name` fields seamlessly. Currently, tf example decoder uses only `name` field to look up ids for class text field present in the data. This change uses both `display_name` and `name` fields in the label map to fetch ids for class text. PiperOrigin-RevId: 212672223 * Modify create_coco_tf_record tool to write out class text instead of class labels. PiperOrigin-RevId: 212679112 * Fix detection model zoo typo. PiperOrigin-RevId: 212715692 * Adding the following two optional flags to WeightSharedConvolutionalBoxHead: 1) In the box head, apply clipping to box encodings in the box head. 2) In the class head, apply sigmoid to class predictions at inference time. PiperOrigin-RevId: 212723242 * Support class confidences in merge boxes with multiple labels. PiperOrigin-RevId: 212884998 * Creates multiple eval specs for object detection. PiperOrigin-RevId: 212894556 * Set batch_norm on last layer in Mask Head to None. PiperOrigin-RevId: 213030087 * Enable bfloat16 training for object detection models. PiperOrigin-RevId: 213053547 * Skip padding op when unnecessary. PiperOrigin-RevId: 213065869 * Modify `Matchers` to use groundtruth weights before performing matching. Groundtruth weights tensor is used to indicate padding in groundtruth box tensor. It is handled in `TargetAssigner` by creating appropriate classification and regression target weights based on the groundtruth box each anchor matches to. However, options such as `force_match_all_rows` in `ArgmaxMatcher` force certain anchors to match to groundtruth boxes that are just paddings thereby reducing the number of anchors that could otherwise match to real groundtruth boxes. For single stage models like SSD the effect of this is negligible as there are two orders of magnitude more anchors than the number of padded groundtruth boxes. But for Faster R-CNN and Mask R-CNN where there are only 300 anchors in the second stage, a significant number of these match to groundtruth paddings reducing the number of anchors regressing to real groundtruth boxes degrading the performance severely. Therefore, this change introduces an additional boolean argument `valid_rows` to `Matcher.match` methods and the implementations now ignore such padded groudtruth boxes during matching. PiperOrigin-RevId: 213345395 * Add release note for iNaturalist Species trained models. PiperOrigin-RevId: 213347179 * Fix the bug of uninitialized gt_is_crowd_list variable. PiperOrigin-RevId: 213364858 * ...text exposed to open source public git repo... PiperOrigin-RevId: 213554260
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- 08 8月, 2018 1 次提交
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由 pkulzc 提交于
* Merged commit includes the following changes: 207771702 by Zhichao Lu: Refactoring evaluation utilities so that it is easier to introduce new DetectionEvaluators with eval_metric_ops. -- 207758641 by Zhichao Lu: Require tensorflow version 1.9+ for running object detection API. -- 207641470 by Zhichao Lu: Clip `num_groundtruth_boxes` in pad_input_data_to_static_shapes() to `max_num_boxes`. This prevents a scenario where tensors are sliced to an invalid range in model_lib.unstack_batch(). -- 207621728 by Zhichao Lu: This CL adds a FreezableBatchNorm that inherits from the Keras BatchNormalization layer, but supports freezing the `training` parameter at construction time instead of having to do it in the `call` method. It also adds a method to the `KerasLayerHyperparams` class that will build an appropriate FreezableBatchNorm layer according to the hyperparameter configuration. If batch_norm is disabled, this method returns and Identity layer. These will be used to simplify the conversion to Keras APIs. -- 207610524 by Zhichao Lu: Update anchor generators and box predictors for python3 compatibility. -- 207585122 by Zhichao Lu: Refactoring convolutional box predictor into separate prediction heads. -- 207549305 by Zhichao Lu: Pass all 1s for batch weights if nothing is specified in GT. -- 207336575 by Zhichao Lu: Move the new argument 'target_assigner_instance' to the end of the list of arguments to the ssd_meta_arch constructor for backwards compatibility. -- 207327862 by Zhichao Lu: Enable support for float output in quantized custom op for postprocessing in SSD Mobilenet model. -- 207323154 by Zhichao Lu: Bug fix: change dict.iteritems() to dict.items() -- 207301109 by Zhichao Lu: Integrating expected_classification_loss_under_sampling op as an option in the ssd_meta_arch -- 207286221 by Zhichao Lu: Adding an option to weight regression loss with foreground scores from the ground truth labels. -- 207231739 by Zhichao Lu: Explicitly mentioning the argument names when calling the batch target assigner. -- 207206356 by Zhichao Lu: Add include_trainable_variables field to train config to better handle trainable variables. -- 207135930 by Zhichao Lu: Internal change. -- 206862541 by Zhichao Lu: Do not unpad the outputs from batch_non_max_suppression before sampling. Since BalancedPositiveNegativeSampler takes an indicator for valid positions to sample from we can pass the output from NMS directly into Sampler. -- PiperOrigin-RevId: 207771702 * Remove unused doc.
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- 01 2月, 2018 1 次提交
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由 Zhichao Lu 提交于
184048729 by Zhichao Lu: Modify target_assigner so that it creates regression targets taking keypoints into account. -- 184027183 by Zhichao Lu: Resnet V1 FPN based feature extractors for SSD meta architecture in Object Detection V2 API. -- 184004730 by Zhichao Lu: Expose a lever to override the configured mask_type. -- 183933113 by Zhichao Lu: Weight shared convolutional box predictor as described in https://arxiv.org/abs/1708.02002 -- 183929669 by Zhichao Lu: Expanding box list operations for future data augmentations. -- 183916792 by Zhichao Lu: Fix unrecognized assertion function in tests. -- 183906851 by Zhichao Lu: - Change ssd meta architecture to use regression weights to compute loss normalizer. -- 183871003 by Zhichao Lu: Fix config_util_test wrong dependency. -- 183782120 by Zhichao Lu: Add __init__ file to third_party directories. -- 183779109 by Zhichao Lu: Setup regular version sync. -- 183768772 by Zhichao Lu: Make test compatible with numpy 1.12 and higher -- 183767893 by Zhichao Lu: Make test compatible with numpy 1.12 and higher -- 183719318 by Zhichao Lu: Use the new test interface in ssd feature extractor. -- 183714671 by Zhichao Lu: Use the new test_case interface for all anchor generators. -- 183708155 by Zhichao Lu: Change variable scopes in ConvolutionalBoxPredictor such that previously trained checkpoints are still compatible after the change in BoxPredictor interface -- 183705798 by Zhichao Lu: Internal change. -- 183636023 by Zhichao Lu: Fixing argument name for np_box_list_ops.concatenate() function. -- 183490404 by Zhichao Lu: Make sure code that relies in SSD older code still works. -- 183426762 by Zhichao Lu: Internal change 183412315 by Zhichao Lu: Internal change 183337814 by Zhichao Lu: Internal change 183303933 by Zhichao Lu: Internal change 183257349 by Zhichao Lu: Internal change 183254447 by Zhichao Lu: Internal change 183251200 by Zhichao Lu: Internal change 183135002 by Zhichao Lu: Internal change 182851500 by Zhichao Lu: 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174065370 by Zhichao Lu: Internal change 174048035 by Zhichao Lu: Fix the pointer for downloading the NAS Faster-RCNN model. -- 174042677 by Zhichao Lu: Internal change 173964116 by Zhichao Lu: Internal change 173790182 by Zhichao Lu: Internal change 173779919 by Zhichao Lu: Internal change 173753775 by Zhichao Lu: Internal change 173753160 by Zhichao Lu: Internal change 173737519 by Zhichao Lu: Internal change 173696066 by Zhichao Lu: Internal change 173611554 by Zhichao Lu: Internal change 173475124 by Zhichao Lu: Internal change 173412497 by Zhichao Lu: Internal change 173404010 by Zhichao Lu: Internal change 173375014 by Zhichao Lu: Internal change 173345107 by Zhichao Lu: Internal change 173298413 by Zhichao Lu: Internal change 173289754 by Zhichao Lu: Internal change 173275544 by Zhichao Lu: Internal change 173273275 by Zhichao Lu: Internal change 173271885 by Zhichao Lu: Internal change 173264856 by Zhichao Lu: Internal change 173263791 by Zhichao Lu: Internal change 173261215 by Zhichao Lu: Internal change 173175740 by Zhichao Lu: Internal change 173010193 by Zhichao Lu: Internal change 172815204 by Zhichao Lu: Allow for label maps in tf.Example decoding. -- 172696028 by Zhichao Lu: Internal change 172509113 by Zhichao Lu: Allow for label maps in tf.Example decoding. -- 172475999 by Zhichao Lu: Internal change 172166621 by Zhichao Lu: Internal change 172151758 by Zhichao Lu: Minor updates to some README files. As a result of these friendly issues: https://github.com/tensorflow/models/issues/2530 https://github.com/tensorflow/models/issues/2534 -- 172147420 by Zhichao Lu: Fix illegal summary name and move from slim's get_or_create_global_step deprecated use of tf.contrib.framework* to tf.train*. -- 172111377 by Zhichao Lu: Internal change 172004247 by Zhichao Lu: Internal change 171996881 by Zhichao Lu: Internal change 171835204 by Zhichao Lu: Internal change 171826090 by Zhichao Lu: Internal change 171784016 by Zhichao Lu: Internal change 171699876 by Zhichao Lu: Internal change 171053425 by Zhichao Lu: Internal change 170905734 by Zhichao Lu: Internal change 170889179 by Zhichao Lu: Internal change 170734389 by Zhichao Lu: Internal change 170705852 by Zhichao Lu: Internal change 170401574 by Zhichao Lu: Internal change 170352571 by Zhichao Lu: Internal change 170215443 by Zhichao Lu: Internal change 170184288 by Zhichao Lu: Internal change 169936898 by Zhichao Lu: Internal change 169763373 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- 29 10月, 2017 1 次提交
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由 Vivek Rathod 提交于
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- 22 9月, 2017 1 次提交
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由 Neal Wu 提交于
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- 19 7月, 2017 2 次提交
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由 Derek Chow 提交于
A few change to prepare for batch inference: * Modify the return type of batch non max suppression to be tuple of tensors so it can be reused for both stages of faster rcnn without any confusion in the semantics implied the the keys used to represent the tensors. * Allow dynamic number of anchors (boxes) in addition to dynamic batch size. * Remove a redundant dynamic batch size test.
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由 Derek Chow 提交于
This change is required to enable object detection export and inference with dynamic batch size.
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- 15 6月, 2017 1 次提交
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由 derekjchow 提交于
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
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