How to Use Generative AI to Augment Computer Vision Data

Kopikat.co, a tool developed by OpenCV.ai, is highlighted in this blog post as an effective solution for data augmentation, particularly beneficial for small datasets in machine learning. Using the custom Hard Hat Workers dataset from Roboflow Universe, the post demonstrates how Kopikat can enhance model performance by generating augmented data while retaining original annotations. The Ultralytics YOLOv8-nano model is trained on this augmented data, resulting in improved metrics, notably an increase in the mAP metric from 64.4 to 65.5 after augmentation. The process does not require changes in model architecture or hyperparameters, showcasing how generative AI can significantly boost machine learning outcomes. Kopikat's ability to expand datasets with realistic data augmentation is emphasized as a critical tool for achieving better results without altering the underlying model, thus providing a practical solution for engineers dealing with limited data resources.