Object and Bounding Box Detection with Vision Models Using Florence 2

Learn to implement object detection and bounding box capabilities using Florence 2 vision models in this comprehensive tutorial video. Master the Florence 2 architecture, understand the mechanics of bounding boxes and segmentation, and gain hands-on experience with Google Colab implementation. Follow step-by-step instructions for annotating custom datasets with bounding boxes, fine-tuning Florence 2 models, and setting up LoRA adapters. Explore practical aspects like selecting optimal learning rates and training arguments, while evaluating fine-tuning results and performance metrics. Access complete resources including Colab notebooks, datasets, research papers, and code templates to enhance your computer vision development skills.