How to Use the Detectron2 Model Zoo (for Object Detection)

Detectron2, introduced by Facebook in 2019, is an open-source library built on PyTorch for implementing advanced computer vision techniques, succeeding the original Detectron which was based on Caffe. Widely utilized across Facebook's products like Portal, Detectron2 enhances the transition from research to production. The Facebook AI Research team also launched a model zoo alongside Detectron2's release, offering pre-trained models for tasks such as object detection, semantic segmentation, and keypoint detection. Roboflow provides a tutorial on using Detectron2 for object detection, demonstrating how to customize training models by modifying the YAML file configuration in a Colab notebook. This flexibility allows users to interchange models like Faster R-CNN and RetinaNet from the model zoo, facilitating straightforward adjustments and training processes.