Faster R-CNN Object Detection with PyTorch - Custom Dataset Training Guide

Learn to implement Faster R-CNN object detection using PyTorch in this comprehensive 49-minute tutorial video. Master the complete workflow from dataset preparation to model deployment, including creating COCO format datasets, annotating images, and structuring data properly. Follow detailed instructions for training a Faster R-CNN model with ResNet-50 FPN backbone on custom datasets containing objects like chairs, tables, and humans. Gain practical experience in preparing annotations, utilizing pre-trained backbones, and performing inference on new images. Explore evaluation techniques and testing procedures for assessing model performance on unseen data. Access complementary resources through the provided GitHub repository for hands-on practice and implementation.