Learn how to train Object Detection Transformers using DETR on custom datasets in this comprehensive tutorial. Set up a Python environment, perform DETR model inference on example images, and download custom datasets from Roboflow Universe. Build custom PyTorch COCO Detection datasets, visualize COCO dataset entries, and create custom PyTorch data loaders. Construct a custom PyTorch Lightning DETR module for training your own object detection model. Follow step-by-step instructions for training DETR on your custom dataset, performing custom DETR model inference, and evaluating the model's performance. Gain practical insights into implementing advanced object detection techniques using transformers and custom datasets.
How to Train Object Detection Transformer on Custom Dataset
Overview
Syllabus
Introduction
Setting up the Python environment
DETR model inference on example images
Download custom dataset from Roboflow Universe
Building custom PyTorch COCO Detection datasets
Visualising COCO datasets entry
Building custom PyTorch Data Loaders
Building custom PyTorch Lightning DETR Module
Training DETR on custom dataset
Custom DETR model inference
Evaluating custom DETR model
Outro
Taught by
Roboflow
Related Courses
Related articles
Reviews
4.0 rating, based on 1 Class Central review
-
Avnish PanwarA great introduction on how to use DETR on custom dataset.
But could have given a more thorough description of the internal workings or components of the model.
