Vehicle and Pedestrian Detector by Using OpenCV Importer

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This example shows how to build a Vehicle and Pedestrian Detector by using the OpenCV Importer app. The model places green and red outline on the vehicle and pedestrians when detected in a recorded video.

First import an OpenCV function into Simulink® by following the Install and Use Computer Vision Toolbox Interface for OpenCV in Simulink. The app creates a Simulink library that contains a subsystem and a C Caller block for the specified OpenCV function. The subsystem is then used in a preconfigured Simulink model to accept the recorded video for vehicle and pedestrian detection.

You learn how to:

Import an OpenCV function into a Simulink library.
Use blocks from a generated library in a Simulink model.

Set Up Your C++ Compiler

To build the OpenCV libraries, identify a compatible C++ compiler for your operating system, as described in Portable C Code Generation for Functions That Use OpenCV Library. Configure the identified compiler by using the mex -setup c++ command. For more information, see Choose a C++ Compiler.

Model Description

In this example, a vehicle and pedestrian detector is implemented by using the Simulink model VehiclePedestrianDetector.slx.

In this model, the subsystem_slwrap_drawDetect subsystem resides in the Vehicle_Pedestrian_Detector_Lib library. You create the subsystem_slwrap_drawDetect subsystem by using the OpenCV Importer app. The subsystem accepts a video from the From Multimedia File block.

Copy Example Folder to a Writable Location

To access the path to the example folder, at the MATLAB® command line, enter:

     OpenCVSimulinkExamples;

Each subfolder contains all the supporting files required to run the example.

Before proceeding with these steps, ensure that you copy the example folder to a writable folder location and change your current working folder to ...example\Vehicle_Pedestrian_Detector. All your output files are saved to this folder.

Step 1: Import OpenCV Function to Create a Simulink Library

1. To start the OpenCV Importer app, click Apps on the MATLAB Toolstrip. In the Welcome page, specify the Project name as Vehicle_Pedestrian_Detector. Make sure that the project name does not contain any spaces. Click Next.

2. In Specify OpenCV Library, specify these file locations, and then click Next.

Project root folder: Specify the path of your example folder. This path is the path to the writable project folder where you have saved your example files. All your output files are saved to this folder.
Source files: Specify the path of the .cpp file located inside your project folder as vehiclePedestrianDetector.cpp.
Include files: Specify the path of the .hpp header file located inside your project folder as vehiclePedestrianDetector.hpp.

3. Analyze your library to find the functions and types for import. Once the analysis is complete, click Next. Select the drawDetect function and click Next.

4. From What to import, select the I/O Type for img as Input, out as Output and then click Next.

5. In Create Simulink Library, configure the default values of OpenCV types. By default, Create a single C-caller block for the OpenCV function is selected to create a C Caller block along with the subsystem in the generated Simulink library.

6. Select Configure library to use Simulink.ImageType signals to configure the generated library subsystem to use Simulink.ImageType signals.

7. Set Default Color Format of Simlink.ImageType signal to RGB, which is the default color format of the image.

8. Set Default Array layout of Simulink.ImageType signal to Column-major, which is the default array layout of the image.

9. To create a Simulink library, click Next.

A Simulink library Vehicle_Pedestrian_Detector_Lib is created from your OpenCV code into the project root folder. You can use any of these blocks for model simulation. In this example, the subsystem subsystem_slwrap_drawDetect is used.

Step 2: Use Generated Subsystem in Simulink Model

To use the generated subsystem subsystem_slwrap_drawDetect with the Simulink model:

1. In your MATLAB current folder, right-click the VehiclePedestrianDetector.slx model and click Open from the context menu. Drag the generated subsystem from the library to the model. Insert the subsystem between From Multimedia File and Video Viewer block.

2. Double-click the subsystem and configure these parameter values:

Rows: 180
Columns: 320
Channels: 3
Underlying Type: uint8

3. Click Apply, and then click OK.

Step 3: Simulate the Vehicle and Pedestrian Detector

On the Simulink Toolstrip, in the Simulation tab, click on Run to simulate the model. After the simulation is complete, the Video Viewer block displays the video of vehicle and pedestrians detected in the video input.