Install

$ git clone git@github.com:yeyeck/classic_nets.git
$ cd classic_nets
$ pip install -r requirements.txt

Dataset

Since the limit of my hardware, the models are trained on Caltech256 dataset. Caltech256 can be download here or in Kaggle which had been splited into train set and validate set. The directory as follow

|--data_root
    |--train
        |--category1
            --**.jpg
        |--category2
            --**.jpg
        |...
    |--val
        |--category1
            --**.jpg
        |--category2
            --**.jpg
        |...

Training

$ python train.py --data /caltech256 --hyper ./config/hyper.yaml --class-num 256 --batch-size 256 --name exp