# 1. Choose your workspace and download our repository.
cd ${CUSTOMIZED_WORKSPACE}
git clone https://github.com/zzz1515151/self-supervised_learning_sketch

# 2. Enter this repository.
cd self-supervised_learning_sketch

# 3. Clone our environment, and activate it.
conda-env create --name ${CUSTOMIZED_ENVIRONMENT_NAME} --file ./conda_environment.yml
conda activate ${CUSTOMIZED_ENVIRONMENT_NAME}

# 4. Download our image and stroke pretraining datasets
chmod +x download.sh
./download.sh
# If this script fails to work well for you,
# please feel free to email both peng.xu[at]ntu.edu.sg and szy2014[at]bupt.edu.cn .
# Please tell us your name and organization in the email.

# 1. Enter config folder.
cd config 

# 2. Set dataset path or other settings in 'cnn_rotation.py'.
dataset_root = ${CUSTOMIZED_IMAGE_PRETRAIN_ROOT}

# 3. Run script.
cd ..
python train_cnn.py 
    --exp cnn_rotation
    --num_workers ${CUSTOMIZED_NUM_WORKERS} 
    --gpu ${CUSTOMIZED_GPU_ID}

# 1. Enter config folder.
cd config 

# 2. Set dataset path or other settings in 'cnn_deform.py'. 
dataset_root = ${CUSTOMIZED_IMAGE_PRETRAIN_ROOT}

# 3. Run script.
cd ..
python train_cnn.py 
    --exp cnn_deform
    --num_workers ${CUSTOMIZED_NUM_WORKERS} 
    --gpu ${CUSTOMIZED_GPU_ID}

# 1. Enter config folder.
cd config 

# 2. Set dataset path or other settings in 'tcn_rotation.py'. 
dataset_root = ${CUSTOMIZED_STROKE_PRETRAIN_ROOT}

# 3. Run script.
cd ..
python train_tcn.py 
    --exp tcn_rotation
    --num_workers ${CUSTOMIZED_NUM_WORKERS} 
    --gpu ${CUSTOMIZED_GPU_ID}

# 1. Enter config folder.
cd config 

# 2. Set dataset path or other settings in 'tcn_deform.py'. 
dataset_root = ${CUSTOMIZED_STROKE_PRETRAIN_ROOT}

# 3. Run script.
cd ..
python train_tcn.py 
    --exp tcn_deform
    --num_workers ${CUSTOMIZED_NUM_WORKERS} 
    --gpu ${CUSTOMIZED_GPU_ID}

@article{selfsupervisedsketch2020,
  title={Deep Self-Supervised Representation Learning for Free-Hand Sketch},
  author={Xu, Peng and Song, Zeyu and Yin, Qiyue and Song, Yi-Zhe and Wang, Liang},
  journal={arXiv preprint arXiv:2002.00867},
  year={2020}
}