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  1. 17 Jul, 2020 7 commits
  3. 16 Jul, 2020 3 commits
  5. 13 Jul, 2020 8 commits
  7. 11 Jul, 2020 1 commit
  9. 10 Jul, 2020 7 commits
  11. 09 Jul, 2020 6 commits
  13. 08 Jul, 2020 3 commits
    • Kaushik Shivakumar's avatar
      save some changes · bbcfd6ba
      Kaushik Shivakumar authored
      bbcfd6ba
    • kmindspark's avatar
      TF2 eager object detection colab · c96e5d5b
      kmindspark authored
      c96e5d5b
    • vivek rathod's avatar
      Merged commit includes the following changes: (#8803) · 52bb4ab1
      vivek rathod authored 
      

320117767  by ronnyvotel:

    DensePose postprocessing implementation.

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320065853  by ronnyvotel:

    Updating how masks are reframed, so that it works on float and uint8 masks.

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320061717  by yuhuic:

    Updated CenterNet restore_from_objects to allow the model to load the
    checkpoints saved during training.

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319835172  by ronnyvotel:

    Updating how the DensePose UV Symmetries MAT file path is constructed and loaded.

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319834678  by ronnyvotel:

    First update to CenterNetMetaArch for DensePose. Adding prediction and loss functionality.

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319810261  by rathodv:

    Create a setup.py file to simplify installation.

    Usage:
    "python object_detection/packages/tf1/setup.py install" for TF1.
    "python object_detection/packages/tf2/setup.py install" for TF2.

    or to create source distribution
    "python object_detection/packages/tf1/setup.py sdist" for TF1.
    "python object_detection/packages/tf2/setup.py sdist" for TF2.

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319803041  by sbeery:

    Updating documentation for export

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319688087  by rathodv:

    Update as_matrix() to to_numpy() to avoid failures with python3.6

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319686183  by vighneshb:

    Require tpu_name when use_tpu is set.

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319613327  by aom:

    EfficientDet-style Data Augmentation.

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319572180  by rathodv:

    Add TF2 SSD FPN (a.k.a RetinaNet) configs.

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319553823  by rathodv:

    Internal Change.

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PiperOrigin-RevId: 320117767
Co-authored-by: default avatarTF Object Detection Team <no-reply@google.com>
      52bb4ab1
  15. 04 Jul, 2020 1 commit
  17. 01 Jul, 2020 3 commits
  19. 30 Jun, 2020 1 commit
    • Yiming Shi's avatar
      Add Faster RCNN Resnet V1 FPN Keras feature extractor (#8716) · 3300fa04
      Yiming Shi authored 
      * Initial commit for faster rcnn resnet v1 fpn feature extractor.

1. Setup code structure for fpn feature extractor

* draft for faster rcnn resnet vi fpn feature extractor

* draft for faster rcnn resnet v1 fpn feature extractor

* add seperated class for resnet 50 101 152

* draft for get_box_classifier_feature_extractor_model

* remove unused code

* Init test file for faster_rcnn_fpn_keras_feature extractor

* add unit test for get_proposal_feature_extractor_model

* add unit test for get_proposal_feature_extractor_model smaller input size

* add unit test for get_proposal_feature_extractor_model incorrect dimension

* change keras model output format

* Update size on extract_proposal_features tests

* change default fpn_min_level to 2

* fix error in get_box_classifier_feature_extractor_model

* add shape test for get_box_classifier_feature_extractor_model

* fix coding style

* Fix coding style for feature extractor.

* add faster rcnn resnet v1 fpn feature extractor to model builder

* rename fpn feature extractors

* modify doc string for Feature extractor:

drop word "implementation"

* add todo in get_box_classifier_feature_extractor_model

* remove enable_v2_behavior

* drop unittest test_extract_proposal_features_dies_with_incorrect_rank_inputs

* modify feature extractor name

* remove min_depth and depth_multiplier feature

* Add coarse layers for faster rcnn fpn keras model

1. Add coarse layers
2. Update corresponding unit test to check the size of the coarse layer
is correct

* change the default max_fpn_level to 6

* change unittest since default max_fpn_level is change to 6
      3300fa04