/data_augmentation_yolov7

Apply data augmentation techniques on YOLO v7 format dataset.

Primary LanguagePython

Data Augmentation on YOLO

Data augmentation techniques:

  • Translation *
  • Cropping
  • Noise *
  • Brightness *
  • Contrast *
  • Saturation *
  • Gaussian blur *

Build virtual environment:

python -m venv ./venv
source ./venv/bin/activate
pip install -r requirements.txt

Run

python3 main.py --images <IMAGES_FOLDER> --labels <LABELS_FOLDER> 
--output <OUTPUT_FOLDER> --nprocess <NUMBER_OF_AUGMENTED_IMAGES>