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Author: lipingw2016

README.md

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-# Cone-Detection-Using-Deep-Learning-for-Formula-Student-Driverless
-This project presents a complete workflow for cone detection in Formula Student Driverless scenarios using deep learning. 
+# Cone Detection Using Deep Learning for Formula Student Driverless 
+<!-- This is the "Title of the contribution" that was approved during the Community Contribution Review Process --> 
+
+[![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=matlab-deep-learning/Cone-Detection-Using-Deep-Learning-for-Formula-Student-Driverless)
+<!-- Add the "File Exchange" icon to the README if this repo also appears on File Exchange via the "Connect to GitHub" feature --> 
+<!-- Add the "Open in MATLAB Online" icon to the README to open a particular file on MATLAB Online --> 
+
+This project presents a complete workflow for cone detection in Formula Student Driverless scenarios using deep learning. It demonstrates how to use MATLAB® and Simulink® for data preparation and labeling, YOLOX neural network design and training, and deployment to a GPU for real-time inference. We gratefully acknowledge the DIAN Racing Team at Tongji University, China, for providing the video datasets used in this demonstration. 
+
+![ss](snapshot.png)
+
+<!--- Please remember to delete all template related text that you are not using within your README.md ---> 
+
+## Installation 
+This project has been tested on MATLAB® release R2024b and R2025a. Before getting started, ensure that the below MathWorks Products and Support Packages are installed and configured correctly in MATLAB®: 
+### MathWorks Products
+* [Image Processing Toolbox™](https://www.mathworks.com/products/image-processing.html)
+* [Computer Vision Toolbox™](https://www.mathworks.com/products/computer-vision.html)
+* [Deep Learning Toolbox™](https://www.mathworks.com/products/deep-learning.html)
+* [Parallel Computing Toolbox™](https://www.mathworks.com/products/parallel-computing.html)
+* [MATLAB Coder™](https://www.mathworks.com/products/matlab-coder.html)
+* [GPU Coder™](https://www.mathworks.com/products/gpu-coder.html)
+### Support Packages
+* [The Computer Vision Toolbox™ Automated Visual Inspection Library](https://www.mathworks.com/matlabcentral/fileexchange/116555-automated-visual-inspection-library-for-computer-vision-toolbox) 
+* [MATLAB Coder Support Package for NVIDIA Jetson and NVIDIA DRIVE Platforms](https://www.mathworks.com/matlabcentral/fileexchange/68644-matlab-coder-support-package-for-nvidia-jetson-and-nvidia-drive-platforms) 
+
+Please see the [Setup and Configuration](https://www.mathworks.com/help/coder/setup-and-configuration.html) for detailed setup and configuration instructions of the [MATLAB Coder Support Package for NVIDIA Jetson and NVIDIA DRIVE Platforms](https://www.mathworks.com/matlabcentral/fileexchange/68644-matlab-coder-support-package-for-nvidia-jetson-and-nvidia-drive-platforms) . 
+<!--- Make sure you have a Installation.md document in the Documentation folder if you are to follow this formatting.  You can choose your own folder formatting if you prefer --->
+
+
+## Getting Started 
+Information about Getting Started
+<!--- List or link to any relevent Documentation to help the user Get Started --->
+* Open the `coneDetectionWithYOLOX.mlx` live script in MATLAB®, and run the code section-by-section to understand the workflow. **Please note:** In Step 7, do not forget to change the NVIDIA Jetson™ GPU settings to your own, and also change the video name *vidName* in the `coneDetection.m` to the file location of your own test video. 
+* Open the `coneDetectionWithObjectDetectorBlock.slx` in Simulink® and update the **File name** of the "From Multimedia File" block and the **File path** of the "Deep learning Object Detector" block to your own file name or path.
+
+## License
+<!--- Make sure you have a License.txt within your Repo --->
+
+The license is available in the `License.txt` file in this GitHub repository.
+
+## Community Support
+[MATLAB Central](https://www.mathworks.com/matlabcentral)
+
+Copyright 2025 The MathWorks, Inc.
+
+<!--- Do not forget to the add the SECURITY.md to this repo --->
+<!--- Add Topics #Topics to your Repo such as #MATLAB  --->
+
+<!--- This is my comment --->
+
+<!-- Include any Trademarks if this is the first time mentioning trademarked products (For Example:  MATLAB&reg; Simulink&reg; Trademark&trade; Simulink Test&#8482;) --> 
+

SECURITY.md

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+# Reporting Security Vulnerabilities 
+
+If you believe you have discovered a security vulnerability, please report it to 
+[[email protected]](mailto:[email protected]). Please see 
+[MathWorks Vulnerability Disclosure Policy for Security Researchers](https://www.mathworks.com/company/aboutus/policies_statements/vulnerability-disclosure-policy.html) 
+for additional information.  

coneDetection.m

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+function coneDetection() %#codegen
+    persistent model;
+    % Load model
+    if isempty(model)
+         model = coder.loadDeepLearningNetwork('yoloxConeDetector.mat');
+    end
+
+    % Create Jetson hardware object
+    hwobj = jetson();     
+    
+    % Please use your own video file with a frame size of 416x416
+    vidName = '/home/xavier/Videos/testConeDetector_416x416.mp4'; 
+
+    % Create video reader object,
+    vObj = VideoReader(hwobj,vidName,width= 416, height = 416);
+
+    % Create display object on the target
+    dispObj = imageDisplay(hwobj);
+
+    while vObj.hasFrame
+        % Grab a frame from the video pipeline
+        img = vObj.readFrame();
+    
+        % Cone detection in the frame
+        [bboxes, ~, labels] =  model.detect(img,'Threshold',0.5);
+        
+        % Annotate detections in the frame.
+        if ~isempty(bboxes)
+            outImg = insertObjectAnnotation(img,'Rectangle', ...
+                bboxes, cellstr(labels));
+        else
+             outImg = img;
+        end
+
+        % Adjust the direction of the frame for output 
+        displayImg = cat(3, outImg(:,:,1).', ...
+        outImg(:,:,2)',outImg(:,:,3)');
+
+        % Display the frame
+        image(dispObj,displayImg);
+    end
+end
+
+% Copyright 2025 The MathWorks, Inc.

coneDetectionWithObjectDetectorBlock.slx

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+Copyright (c) 2025, The MathWorks, Inc.
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are
+met:
+
+    * Redistributions of source code must retain the above copyright
+      notice, this list of conditions and the following disclaimer.
+    * Redistributions in binary form must reproduce the above copyright
+      notice, this list of conditions and the following disclaimer in
+      the documentation and/or other materials provided with the distribution
+    * Neither the name of the The MathWorks, Inc. nor the names
+      of its contributors may be used to endorse or promote products derived
+      from this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
+LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+POSSIBILITY OF SUCH DAMAGE.