Hi Bashir,
When working with YOLO for object detection on video frames, it is important to ensure that your setup is correctly configured and optimized for the task at hand.
Ensure that your YOLO detector is properly loaded and compatible with your MATLAB version. If you have a pretrained detector saved in a MAT file, you can load it using:
pretrained = load('yolov2ResNet50VehicleExample_19b.mat');
detector = pretrained.detector;
If you do not have a pretrained network, you can train your own model by referring to the following documentations:
To create your own YOLO detection network, refer the following documentation:
Here is how you can use object detection with a pretrained network for vehicle detection:
Video = VideoReader("sampleVideo_640x480.mp4");
player = vision.VideoPlayer;
pretrained = load('yolov2ResNet50VehicleExample_19b.mat');
detector = pretrained.detector;
detections = {};
measurementNoise = 10;
while hasFrame(Video)
frame = readFrame(Video);
frameIndex = round(Video.CurrentTime * Video.FrameRate);
% Perform detection on the frame
[bbox, score, label] = detect(detector, frame);
% Store detections
if length(detections) < frameIndex
detections{frameIndex} = {};
end
for i = 1:length(score)
detections{frameIndex}{end+1} = objectDetection(frameIndex, bbox(i,:), ...
"MeasurementNoise", measurementNoise, "ObjectAttributes", struct("Score", score(i)));
end
% Annotate and display frame
Object = insertObjectAnnotation(frame, "rectangle", bbox, cellstr(label), "Color", "green");
step(player, Object);
end
