To my understanding, you want to learn how the dataset is loaded and used in Yolo v3 object detection MATLAB example. Further, you want to use your own data to train Yolo v3 object detection model.
Part 1:
%% download pretrained network (set to 'true' to train the network)
doTraining = false;
if ~doTraining
preTrainedDetector = downloadPretrainedYOLOv3Detector();
end
This part of code is used to decide whether you want to train the network or use the pretrained network. Set 'doTraining' to 'true' to train the network.
Part 2:
%% load data (modify to faces dataset)
data = load('vehicleDatasetGroundTruth.mat');
vehicleDataset = data.vehicleDataset;
Here, 'data' variable will store mat file which in turn is a 1×1 struct with 1 field i.e. vehicleDataset.
Now, 'vehicleDataset' variable will store main dataset which is a 295*2 table. Column 1 contain location path of image files and column 2 contain bounding box coordinates. This bounding boxes specifies the upper left corner and the size of the bounding box in pixels. The bounding boxes are in the form [x y width height].
Now, if you want to use your data you have to apply following changes.
Step 1: You create a table in which:
- first column should contain the location paths of your images.
- second column should contain the bounding box vector as per specified format.
Step 2: Set 'vehicleDataset' variable to this newly created table.
