Metadata-Version: 2.1
Name: wk-classify
Version: 0.0.0.2
Summary: A package of tools for building deep-learning classification programs.
Home-page: https://github.com/Peiiii/wk-classify
Author: Wang Pei
Author-email: 1535376447@qq.com
License: UNKNOWN
Description: # wk-classify
        A package of tools for building deep-learning classification programs. Easy to use, light and powerful.
        
        # Install
        ```shell script
        pip3 install wk-classify
        ```
        
        # Usage
        
        ### quick experience
        ```python
        from wcf.packages.resnet.training import train, BaseConfig
        class Config(BaseConfig):
            TRAIN_DIR = 'path for train set'
            VAL_DIR = 'path for val set'
        cfg=Config()
        train(cfg)
        ```
        ### a real example
        ```python
        from wcf.packages.resnet.training import train, BaseConfig
        from torchvision import transforms
        class Config(BaseConfig):
            GEN_CLASSES_FILE = True
            USE_tqdm_TRAIN = False # use tqdm to format output
            INPUT_SIZE = (252,196)
            BATCH_SIZE = 16
            NUM_EPOCHS = 50
            BALANCE_CLASSES = True
            VAL_INTERVAL = 0.2 # val time insterval: 0.2 epoch (0.2* num_batches_per_epoch)
            WEIGHTS_SAVE_INTERVAL = 0.2 #  the same as above
            TRAIN_DIR = '<your train path>'
            VAL_DIR = '<your val path>'
            train_transform = transforms.Compose([
                transforms.ColorJitter(brightness=0.1, contrast=0.1, saturation=0.1, hue=0.5),
                transforms.Resize(INPUT_SIZE),
                transforms.ToTensor(),
                transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
            ])
            val_transform = transforms.Compose([
                transforms.Resize(INPUT_SIZE),
                transforms.ToTensor(),
                transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
            ])
        cfg=Config()
        train(cfg)
        ```
        
        ### all options
        check out the `BaseConfig` class for all options
        
        ### how to predict?
        check out `demo_predict.py`
        
        
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.0
Description-Content-Type: text/markdown
