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1
Introduction
2
Setting up the Python environment
3
DETR model inference on example images
4
Download custom dataset from Roboflow Universe
5
Building custom PyTorch COCO Detection datasets
6
Visualising COCO datasets entry
7
Building custom PyTorch Data Loaders
8
Building custom PyTorch Lightning DETR Module
9
Training DETR on custom dataset
10
Custom DETR model inference
11
Evaluating custom DETR model
12
Outro
Description:
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

Roboflow
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