YOLO object detection with OpenCV

Let’s say we not only want to know whether there is cat in the image, but where exactly is the cat. Object localization algorithms not only label the class of an object, but also draw a bounding box around position of object in the image.

DNN (Deep Neural Network) module was initially part of opencv_contrib repo. It has been moved to the master branch of opencv repo last year, giving users the ability to run inference on pre-trained deep learning models within OpenCV itself. (One thing to note here is, dnn module is not meant be used for training. It’s just for running inference on images/videos.)Initially only Caffe and Torch models were supported. Over the period support for different frameworks/libraries like TensorFlow is being added. Support for YOLO/DarkNet has been added recently. We are going to use the OpenCV dnn module with a pre-trained YOLO model for detecting common objects.