Java Deep Learning Projects

Step 4 – Object detection from image frames

Tiny YOLO extracts the features from each frame as an n-dimensional, dense, numerical multi-channel array. Then each image is split into a smaller number of rectangles (boxes):

public void markObjectWithBoundingBox(Mat file, int imageWidth, int imageHeight, boolean newBoundingBOx,                                      String winName) throws Exception { 
        // parameters matching the pretrained TinyYOLO model        int W = 416; // width of the video frame  
        int H = 416; // Height of the video frame 
        int gW = 13; // Grid width 
        int gH = 13; // Grid Height 
        double dT = 0.5; // Detection threshold         Yolo2OutputLayer outputLayer = (Yolo2OutputLayer) model.getOutputLayer(0); 
        if (newBoundingBOx) { 
            INDArray indArray = prepareImage(file, W, H); 
            INDArray results ...