roiInputLayer

(Not recommended) ROI input layer for Fast R-CNN

ROIInputLayer is not recommended. Instead, use a different type of object detector, such as a yoloxObjectDetector or yolov4ObjectDetector detector. For more information, see Version History.

Description

An ROI input layer inputs images to a Fast R-CNN object detection network.

Creation

Syntax

layer = roiInputLayer

layer = roiInputLayer('Name',Name)

Description

layer = roiInputLayer creates an ROI input layer.

layer = roiInputLayer('Name',Name) creates an ROI input layer and sets the optional Name property.

Properties

Name — Layer name

"" (default) | character vector | string scalar

Layer name, specified as a character vector or string scalar. For Layer array input, the trainnet (Deep Learning Toolbox) and dlnetwork (Deep Learning Toolbox) functions automatically assign names to layers with the name "".

The ROIInputLayer object stores this property as a character vector.

Data Types: char | string

NumOutputs — Number of outputs

1 (default)

This property is read-only.

Number of outputs from the layer, returned as 1. This layer has a single output only.

Data Types: double

OutputNames — Output names

{'out'} (default)

This property is read-only.

Output names, returned as {'out'}. This layer has a single output only.

Data Types: cell

Examples

Connect ROI Input Layer to ROI Max Pooling Layer

Create a dlnetwork object.

net = dlnetwork;

Create an array of layers that includes an ROI input layer and an ROI max pooling layer with output size [4 4]. Add the layers to the network.

outputSize = [4 4];
layers = [
    roiInputLayer(Name="roi_input")
    roiMaxPooling2dLayer(outputSize,Name="roi_pool")]

layers = 
  2x1 Layer array with layers:

     1   'roi_input'   ROI Input         M-by-4 rectangular ROIs
     2   'roi_pool'    ROI Max Pooling   ROI Max Pooling with pooled output size [4 4]

net = addLayers(net,layers);

Connect the output of the ROI input layer with the "roi" input of the ROI max pooling layer. Remove the connection between the ROI input layer and the "in" input of the ROI max pooling layer.

net = connectLayers(net,"roi_input","roi_pool/roi");
net = disconnectLayers(net,"roi_input","roi_pool/in");
plot(net)

Version History

Introduced in R2018b

R2024b: Not Recommended

Starting in R2024b, R-CNN object detectors are no longer recommended. Instead, use a different type of object detector, such as a yoloxObjectDetector or yolov4ObjectDetector object. These object detectors are faster than R-CNN object detectors. For more information, see Choose an Object Detector.