image_augmentation

augment image data by using different augmentation techniques and save for training.

1. create an environment with conda and install the dependencies using: pip install requirements.txt

2. run python main.py with 4 arguments to start augmentation:

   1. img_type: (str), choose from: "jpg", "png".

   2. generate: (int) how many image per sample.

   3. choose_augment_methods_randomly: (str), choose from: "T","F".

   4. specify method(if 'choose_augment_methods_randomly' is "F"): (str), choose from:"rotate","blur","occlusion","brightness","contrast","distortion". If the 3rd argument is "T" or True then the pipeline will use all the available augmentation techniques.