text: ## BlendMask instance detection
  
  ```
  coco/
    thing_train2017/
      # thing class label maps for auxiliary semantic loss
  lvis/
    thing_train/
      # semantic labels for LVIS
  ```
  
  Run `python prepare_thing_sem_from_instance.py`, to extract semantic labels from instance annotations.
  
  Run `python prepare_thing_sem_from_lvis.py`, to extract semantic labels from LVIS annotations.
  
  ## Text Recognition
  
  - Totaltext training, testing images, and annotations [[link]](https://universityofadelaide.box.com/shared/static/3eq5ti7z45qfq5gu96gg5t1xwh1yrrt7.zip) [[paper]](https://ieeexplore.ieee.org/abstract/document/8270088/) [[code]](https://github.com/cs-chan/Total-Text-Dataset). 
  - CTW1500 training, testing images, and annotations [[link]](https://universityofadelaide.box.com/s/yb9red8pi9eszuzqompo593b6zhz87qw) [[paper]](https://www.sciencedirect.com/science/article/pii/S0031320319300664) [[code]](https://github.com/Yuliang-Liu/Curve-Text-Detector).
  - MLT [[dataset]](https://universityofadelaide.box.com/s/tsiimvp65tkf7dw1nuh8l71cjcs0fyif) [[paper]](https://ieeexplore.ieee.org/abstract/document/8270168).
  - Syntext-150k: 
    - Part1: 94,723 [[dataset]](https://universityofadelaide.box.com/s/alta996w4fym6arh977h3k3xv55clhg3) 
    - Part2: 54,327 [[dataset]](https://universityofadelaide.box.com/s/7k7d6nvf951s4i01szs4udpu2yv5dlqe)
  
  ```
  text/
    totaltext/
      annotations/
      train_images/
      test_images/
    mlt2017/
      annotations/train.json
      images/
      ...
    syntext1/
    syntext2/
    ...
    evaluation/
      gt_ctw1500.zip
      gt_totaltext.zip
  ```
  
  To evaluate on Total Text and CTW1500, first download the zipped annotations with
  
  ```
  mkdir evaluation
  cd evaluation
  wget -O gt_ctw1500.zip https://cloudstor.aarnet.edu.au/plus/s/uoeFl0pCN9BOCN5/download
  wget -O gt_totaltext.zip https://cloudstor.aarnet.edu.au/plus/s/pEMs0KjCocL2nvV/download
  ```
  
  ## Person In Context instance detection
  
  ```
  pic/
    thing_train/
      # thing class label maps for auxiliary semantic loss
    annotations/
      train_person.json
      val_person.json
    image/
      train/
      ...
    
  ```
  
  First link the PIC_2.0 dataset to this folder with `ln -s \path\to\PIC_2.0 pic`. Then use the `python gen_coco_person.py` to generate train and validation annotation jsons.
  
  Run `python prepare_thing_sem_from_instance.py --dataset-name pic`, to extract semantic labels from instance annotations.
  