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Learn how to train a custom object detection model using Detectron2, a powerful deep learning framework in Python. Follow a step-by-step guide covering installation, dataset preparation, model training, and making predictions on new images. Discover the process of setting up Detectron2, preparing custom object detection datasets with annotations and images, configuring and training the model, and using the trained model for object detection. Visualize results with bounding boxes and class labels. Suitable for beginners, this 37-minute tutorial provides hands-on experience in building a custom object detector, complete with code examples and practical tips.
Syllabus
Introduction
Installation
Annotate the data
Discover and load the data
Train the model
Test the model
Taught by
Eran Feit