1. 03 9月, 2019 1 次提交
  2. 12 4月, 2019 1 次提交
  3. 20 2月, 2019 1 次提交
    • S
      Supported FBNet architecture. (#463) · b23eee0c
      Stzpz 提交于
      * Supported any feature map size for average pool.
      * Different models may have different feature map size.
      
      * Used registry to register keypoint and mask heads.
      
      * Passing in/out channels between modules when creating the model.
      
      Passing in/out channels between modules when creating the model. This simplifies the code to compute the input channels for feature extractors and makes the predictors independent of the backbone architectures.
      * Passed in_channels to rpn and head builders.
      * Set out_channels to model modules including backbone and feature extractors.
      * Moved cfg.MODEL.BACKBONE.OUT_CHANNELS to cfg.MODEL.RESNETS.BACKBONE_OUT_CHANNELS as it is not used by all architectures. Updated config files accordingly.
      
      For new architecture modules, the return module needs to contain a field called 'out_channels' to indicate the output channel size.
      
      * Added unit test for box_coder and nms.
      
      * Added FBNet architecture.
      
      * FBNet is a general architecture definition to support efficient architecture search and MaskRCNN2GO.
      * Included various efficient building blocks (inverted residual, shuffle, separate dw conv, dw upsampling etc.)
      * Supported building backbone, rpn, detection, keypoint and mask heads using efficient building blocks.
      * Architecture could be defined in `fbnet_modeldef.py` or in `cfg.MODEL.FBNET.ARCH_DEF` directly.
      * A few baseline architectures are included.
      
      * Added various unit tests.
      
      * build and run backbones.
      * build and run feature extractors.
      * build and run predictors.
      
      * Added a unit test to verify all config files are loadable.
      b23eee0c
  4. 12 2月, 2019 2 次提交
    • F
      Add RPN configs (#66) · 6286a6c8
      Francisco Massa 提交于
      * Add RPN config files
      
      * Add more RPN models
      6286a6c8
    • F
      [WIP] Add Keypoint R-CNN (#69) · e0a525a0
      Francisco Massa 提交于
      * [WIP] Keypoints inference on C2 models work
      
      * Training seems to work
      
      Still gives slightly worse results
      
      * e2e training works but gives 3 and 5 mAP less
      
      * Add modification proposed by @ChangErgou
      
      Improves mAP by 1.5 points, to 0.514 and 0.609
      
      * Keypoints reproduce expected results
      
      * Clean coco.py
      
      * Linter + remove unnecessary code
      
      * Merge criteria for empty bboxes in has_valid_annotation
      
      * Remove trailing print
      
      * Add demo support for keypoints
      
      Still need further cleanups and improvements, like adding fields support for the other ops in Keypoints
      
      * More cleanups and misc improvements
      
      * Fixes after rebase
      
      * Add information to the readme
      
      * Fix md formatting
      e0a525a0
  5. 25 10月, 2018 1 次提交