Python Deep Learning - Second Edition

A code example of YOLOv3 with OpenCV

In this section, we'll demonstrate how to use the YOLOv3 object detector with OpenCV. For this example, you'll need OpenCV 3.4.2 or higher, and 250 MB of disk space for the pre-trained YOLO network. Let's begin with the following steps:

1. Start with the imports:

import os.pathimport cv2  # opencv importimport numpy as npimport requests

2. Add some boilerplate code, which downloads and stores the following:
   • The YOLOv3 network configuration. We'll use the YOLO author's GitHub and personal website to do this.
   • The names of the classes that the network can detect. We'll also load them from the file.
   • A test image from Wikipedia. We'll also load the image from the file:

# Download YOLO net config file# We'll ...