Detect vehicles using Faster R-CNN
returns a trained Faster R-CNN (regions with convolution neural networks) object
detector for detecting vehicles. Faster R-CNN is a deep learning object
detection framework that uses a convolutional neural network (CNN) for
detector = vehicleDetectorFasterRCNN
The detector is trained using unoccluded images of the front, rear, left, and right sides of vehicles. The CNN used with the vehicle detector uses a modified version of the MobileNet-v2 network architecture.
Use of this function requires Deep Learning Toolbox™.
Detect cars in a single image and annotate the image with the detection scores. To detect cars, use a Faster R-CNN object detector that was trained using images of vehicles.
Load the pretrained detector.
fasterRCNN = vehicleDetectorFasterRCNN('full-view');
Use the detector on a loaded image. Store the locations of the bounding boxes and their detection scores.
I = imread('highway.png'); [bboxes,scores] = detect(fasterRCNN,I);
Annotate the image with the detections and their scores.
I = insertObjectAnnotation(I,'rectangle',bboxes,scores); figure imshow(I) title('Detected Vehicles and Detection Scores')
modelNameinput argument is not recommended
Behavior change in future release
modelName input argument is not recommended. To update your
code, remove all instances of
|Discouraged Usage||Recommended Replacement|
modelName = 'front-rear-view' detector = vehicleDetectorFasterRCNN(modelName);
detector = vehicleDetectorFasterRCNN;