deply yolo net with a raspberry in matlab

To deploy YOLO net on a raspberry pi using MATLAB, follow these steps:

1. Install MATLAB support package for Raspberry Pi.
2. Create a new MATLAB function and copy the YOLO code into it.
3. Load the pre-trained YOLOv2 network. You can either download the network or train it yourself.
4. Load the input image on which you want to run the YOLO network.
5. Process the input image and predict the bounding boxes for any object in the image.
6. Display the output image with the bounding boxes surrounding the objects.

Here is an example code:

main.m
% Configure the Raspberry Pi
r = raspi('ip','username','password');

% Load the pre-trained YOLOv2 network
yolov2 = coder.loadDeepLearningNetwork('yolov2.mat');

% Load the input image
img = imread('input_image.jpg');

% Process the image
inputSize = yolov2.Layers(1).InputSize;
img = imresize(img,inputSize(1:2));
[bboxes,scores,labels] = detect(yolov2,img);

% Display the output image with bounding boxes
if ~isempty(bboxes)
    detectedImg = insertObjectAnnotation(img,'rectangle',bboxes,scores);
    figure
    imshow(detectedImg)
end
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Note: You may need to adjust the configuration parameters based on your specific use case.