#Image Augmentation

Discover a set of TensorFlow tutorials created specifically for beginners with clear examples for both TF v1 and v2. Learn traditional and modern practices, such as layers, estimators, and dataset APIs. The project includes instructions on basic operations, linear and logistic regressions, word embedding models, gradient boosting, and various neural network architectures. Additional guides cover data management, multi-GPU training, and customized layers. Keep up-to-date with the latest TensorFlow methods and enhance your skills with practical, hands-on experiences.

OneTrainer serves as a comprehensive hub for stable diffusion model training, compatible with an array of models from Stable Diffusion 1.5 to 3.5 and SDXL, among others. It incorporates advanced training strategies including full fine-tuning, LoRA, and embeddings, alongside features like masked training and image augmentation. Users gain from functionality such as automatic backups, Tensorboard tracking, and tools facilitating multi-resolution training. This versatile toolkit smooths model management with intuitive format conversion and real-time model sampling, tailored for both CLI and GUI preferences.

Image-Augmentation software improves image quality and diversity using advanced techniques, including arithmetic, artistic, and geometric transformations. The ImgAug library allows customization, enhancing compatibility and processing speed. Version 3.4 resolves Numpy incompatibility issues and supports new formats like ppm, bmp, and tif. Integrated error logging aids debugging, making it suitable for developers and researchers focused on detailed image manipulation.