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fasterRCNNObjectDetector class

Detect objects using Faster R-CNN deep learning detector


The fasterRCNNObjectDetector object contains a Faster R-CNN (regions with convolution neural networks) object detector returned by the trainFasterRCNNObjectDetector function. Use of the fasterRCNNObjectDetector object requires the Neural Network Toolbox™.

When using the detect method, use of a CUDA®-enabled NVIDIA® GPU with compute capability 3.0 or higher is highly recommended. The GPU reduces computation time significantly. Usage of the GPU requires Parallel Computing Toolbox™.


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Name of the trained object detector, specified as a character vector. By default, the trainFasterRCNNObjectDetector function sets the name. You can modify the name after training.

Trained Faster R-CNN object detection network, specified as a vision.cnn.FastRCNN object. The object stores the layers that define the convolutional neural network used within the R-CNN detector. This network classifies region proposals produced by RegionProposalFcn.

Trained region proposal network (RPN), specified as a vision.cnn.RegionProposalNetwork object. This object represents the RPN used in the R-CNN detector. The RPN shares weights with the network stored in Network property.

Names of the object classes that the Faster R-CNN detected was trained to find, specified as a cell array.

Minimum anchor box sizes used to build the anchor box pyramid of the region proposal network (RPN), specified as a matrix. Each row defines the [height width] of an anchor box.

Anchor box pyramid scale factor used to successively upscale anchor box sizes, specified as a scalar.

Number of levels in each anchor box pyramid, specified as a scalar.

Minimum object size supported by the R-CNN network, specified as a [height width] vector. The minimum size depends on the network architecture.


detectDetect objects using Faster R-CNN object detector

Introduced in R2017a