Train Custom YOLOv10 Model and Run Inference

In the video titled ‘YOLOv10: Train a Custom Model and Run Inference on Live Webcam,’ Nicolai Nielsen demonstrates how to train a custom YOLOv10 model and run inference on a live webcam. The tutorial covers the entire computer vision training pipeline, starting with dataset generation using a webcam, labeling images with Roboflow, exporting the dataset, and training the model in a Google Colab notebook with a free GPU. After training, the video shows how to evaluate the model and write a Python script to run live inference on a webcam. Nicolai provides a step-by-step guide, including setting up the YOLOv10 GitHub repository, generating and annotating images, creating and exporting the dataset, installing YOLOv10, and running inference on a pretrained model. The video also includes practical examples of using the model for object detection and visualizing the results. By following this tutorial, viewers can set up and train their own YOLOv10 models for various applications and projects.