How to Draw a Bounding Box Prediction Label with Python
Blog post from Roboflow
James Gallagher's tutorial on Roboflow's blog outlines the process of drawing bounding box predictions and labels on images using Python, specifically employing the cv2 library. The guide explains that computer vision models typically output prediction positions rather than visual bounding boxes, necessitating a post-processing step to draw these boxes and add labels. It details the required code to create bounding boxes using coordinate data and labels above each box, specifying elements such as text color, font, and thickness. Additionally, the tutorial provides instructions for utilizing a pre-trained model from Roboflow Universe, detailing how to set up the model, retrieve predictions, and implement bounding boxes and labels on images with a confidence threshold. By following these steps, users can effectively visualize numerical data from computer vision models in their projects.