In this recipe, we are going to use the YOLOv3 DNN algorithm, which performs object detection. Object detection in an image is a common task in computer vision; with deep learning techniques, we can achieve highly accurate detections. YOLOv3 reaches a 60.6 mAP in the COCO dataset (80 classes and more than 300,000 images), which has a very good precision with 20 fps or 33 mAP with 220 fps.
Object detection with YOLOv3
How to do it...
In this recipe, we are going to use the same functions and classes to load the model, convert the images, and predict, but we are going to introduce one more important function – non-maximum suppression – and a few util functions to draw the predictions with their labels:
- Create...
