Un esempio di Matlab, che puoi eseguire, in questo caso rileva il segnale di stop
%% Train Fast R-CNN Stop Sign Detector
%%
% Load training data.
data = load('rcnnStopSigns.mat', 'stopSigns', 'fastRCNNLayers');
stopSigns = data.stopSigns;
fastRCNNLayers = data.fastRCNNLayers;
%%
% Add fullpath to image files.
stopSigns.imageFilename = fullfile(toolboxdir('vision'),'visiondata', ...
stopSigns.imageFilename);
%%
% Set network training options:
%
% * Lower the InitialLearningRate to reduce the rate at which network
% parameters are changed.
% * Set the CheckpointPath to save detector checkpoints to a temporary
% directory. Change this to another location if required.
options = trainingOptions('sgdm', ...
'InitialLearnRate', 1e-6, ...
'MaxEpochs', 10, ...
'CheckpointPath', tempdir);
%%
% Train the Fast R-CNN detector. Training can take a few minutes to complete.
frcnn = trainFastRCNNObjectDetector(stopSigns, fastRCNNLayers , options, ...
'NegativeOverlapRange', [0 0.1], ...
'PositiveOverlapRange', [0.7 1], ...
'SmallestImageDimension', 600);
%%
% Test the Fast R-CNN detector on a test image.
img = imread('stopSignTest.jpg');
%%
% Run the detector.
[bbox, score, label] = detect(frcnn, img);
%%
% Display detection results.
detectedImg = insertShape(img, 'Rectangle', bbox);
figure
imshow(detectedImg)