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Learn to build an advanced Object Detection system using the DETR (DEtection TRansformer) model in this 46-minute tutorial. Explore data preparation, model training, and inference using Python libraries such as PyTorch, Transformers, PyTorch Lightning, and Supervision. Master custom dataset handling with torchvision, implement DETR with PyTorch Lightning, set up a training pipeline, perform inference on new images, and visualize detection results. Follow along with provided code examples and gain practical experience in modern computer vision techniques for object detection on bone fraction datasets.
Syllabus
Introduction
Installation
Prepare the data
Build the model
Train the model
Test the model
Taught by
Eran Feit