This is pytorch-self-supervised-learning repository.

Table of contents:

1. tutorial
2. experimental result

1. clone this repo.

   git clone https://github.com/hankyul2/pytorch-ssl.git
   cd pytorch-ssl
   pip3 install requirements.txt 

2. run following command.

1. run following command.

1. run following command.

   KNN classifier

   # Single-GPU
   python3 valid.py -es imagenet1k_knn_224_v1 -ws dino_official
   # Multi-GPU 
   torchrun --nproc_per_node=4 --master_port=12345 valid.py -es imagenet1k_knn_224_v1 -ws dino_official

   FC classifier

   # Single-GPU
   python3 valid.py -es imagenet1k_fc_224_v1 -ws dino_official
   # Multi-GPU 
   torchrun --nproc_per_node=4 --master_port=12345 valid.py -es imagenet1k_fc_224_v1 -ws dino_official

   Tips

   1. For large sized train dataset, we recommend to run multi-gpu command because, extracting whole features takes too much time in single gpu.
   2. If you have extracted features once, please specify the extracted feature path at feature_path in config/valid.json.
   3. If you don't specify weight settings (-ws), whole weight settings will be used in validation.
   4. If you don't specify model name (-m), whole model in model_weight will be used in validation.