GitLab

* 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