To perform Amodal Instance Segmentation

[masa-suke]

Thank you for your great work!

I am trying to train a model to perform Amodal Instance Segmentation and input my own images to see the prediction results of hidden regions.
I would like to receive the following and other predicted results.
However, I am unable to detect hidden regions.
So, please let me ask some questions.

Questions

• About the label data

  • datasets/coco/annotations/instances_train_2017_transform_slight_correct.json
    Which of the following ABCs is appropriate?
    I did C but did not get good results.
    • A. Use a file downloaded from google drive or onedrive.
    • B. Run BCNet/process.h to the json file downloaded from google drive or onedrive and use the output file.
    • C. Run BCNet/process.h to the instance_train.json contained in the 2017 Train/Val annotations [241MB] and use the output file.
  • datasets/coco/annotations/instances_val2017.json
    I used the instances_val2017.json included in the 2017Train/Val annotation [241MB],
    Do I also need to run BCNet/process.h against instances_val2017.json?

• About config file
  I am currently running BCNet/all.sh and using the BCNet/configs/fcos/fcos_imprv_R_50_FPN.yaml listed in it as the training config.
  Would BCNet/configs/fcos/fcos_imprv_R_101_FPN.yaml be more appropriate?

• About visualize.sh
  Is the same setting as for `all.sh' correct?
  I am concerned that the config used for visualize.sh and all.sh is different.