Error executing command touch -c code generation

Any idea how can I fix this error?

 codegen('-config ',cfg,'-args',inputArgs,'alisamehtrial','-report');
------------------------------------------------------------------------
Error executing command "touch -c Timo/MATLAB_ws/R2023a/E/JetsonWork/georgee/codegen/exe/alisamehtrial/*.*;make  -f alisamehtrial_rtw.mk -j4 all MATLAB_WORKSPACE="timo/MATLAB_ws/R2023a" LINUX_TARGET_LIBS_MACRO="" -C Timo/MATLAB_ws/R2023a/E/JetsonWork/georgee/codegen/exe/alisamehtrial". Details:

STDERR: make: alisamehtrial_rtw.mk: No such file or directory
make: *** No rule to make target 'alisamehtrial_rtw.mk'.  Stop.

STDOUT: make: Entering directory '/home/ahmedtamer/Timo/MATLAB_ws/R2023a/E/JetsonWork/georgee/codegen/exe/alisamehtrial'
make: Leaving directory '/home/ahmedtamer/Timo/MATLAB_ws/R2023a/E/JetsonWork/georgee/codegen/exe/alisamehtrial'

------------------------------------------------------------------------
Build error: C++ compiler produced errors. See the Build Log for further details.
More information
Code generation failed: View Error Report

Error using codegen
 
>> 

I get this error when I try to deploy a code from matlab to jetson nano

This is my code:

function alisamehtrial(mdlName,calibFile,port,cameraName,resolution)
%#codegen
hwobj = jetson()
%%
% Create hwobj
hwobj = jetson();
camObj = camera(hwobj,cameraName,resolution);
dispObj = imageDisplay(hwobj);
obj = velodynelidar(hwobj,mdlName,calibFile,'Port',2368);

%%
R = [102.3  0 -178.5 ];
Translation = [-0.19 -0.32 0.08];
tform1 = rigidtform3d(R, Translation);
camToLidar = invert(tform1);
LidarToCam = tform1;
focalLength    = [2.030730245970483e+03 2.028918613870282e+03]; 
principalPoint = [1.372086996058644e+03 7.403715833893430e+02];
imageSize      = [720	1280];
intrinsics = cameraIntrinsics(focalLength,principalPoint,imageSize);
persistent yolov4Obj;

if isempty(yolov4Obj)
    yolov4Obj = coder.loadDeepLearningNetwork('tinyyolov4coco.mat');
end
%%
continousStreaming = true;
%%
start(obj)
if strcmp(mdlName,'VLP16')
    lenOut = 120;
    outStructLen = 28000;
else
    lenOut = 70;
    outStructLen = 48000;
end

%%
while continousStreaming
    % Capture the image from the Jetson camera hardware.
    I = snapshot(camObj);
    pc = read(obj);
    M=16;
    N=1808;
    reshapedLocation = reshape(pc.Location, [M, N, 3]);
    outStruct = pointCloud(reshapedLocation);


    % Call to detect method
    [bboxes, scores, labels] = detect(yolov4Obj, I, 'Threshold', 0.3);
    personIndices = find(labels == 'person');
    personBboxes = bboxes(personIndices, :);
    personScores = scores(personIndices, :);
    personLabels = labels(personIndices, :);
    % Convert categorical labels to cell array of character vectors
    labels = cellstr(labels);
    % Annotate detections in the camera image.
    img = insertObjectAnnotation(I, 'rectangle', bboxes, labels);
    % Remove ground plane
    groundPtsIndex = segmentGroundFromLidarData(outStruct, 'ElevationAngleDelta', 5, ...
        'InitialElevationAngle', 0);
    nonGroundPts = select(outStruct, ~groundPtsIndex);
        
    % Process lidar data if there are detections
    if bboxes ==  personBboxes
        [lidarBbox, ~, boxUsed] = bboxCameraToLidar(bboxes, nonGroundPts, intrinsics, ...
            camToLidar, 'ClusterThreshold', 0.3, 'MaxDetectionRange', [1, 50]);
        [distance, nearestRect, idx] = helperComputeDistance(bboxes, nonGroundPts, lidarBbox, ...
            intrinsics, LidarToCam);
        % Print distance information
            fprintf('Distance of a Person');        
    else 
        [lidarBbox, ~, boxUsed] = bboxCameraToLidar(bboxes, nonGroundPts, intrinsics, ...
            camToLidar, 'ClusterThreshold', 0.3, 'MaxDetectionRange', [1, 50]);
        [distance, nearestRect, idx] = helperComputeDistance(bboxes, nonGroundPts, lidarBbox, ...
            intrinsics, LidarToCam);
        % Print distance information
            %fprintf('Distance of an Object');        
        
        % Update image with bounding boxes
        % im = updateImage(display, im, nearestRect, distance);
        % updateLidarBbox(display, lidarBbox)
    end
end
end
%%
 function [distance, nearestRect, index] = helperComputeDistance(bboxes, outStruct, lidarBbox, intrinsic, lidarToCam)
    idx = zeros(0,1);
    numLidarDetections = size(lidarBbox, 1);
    nearestRect = zeros(0, 4);
    distance = zeros(1, numLidarDetections);
    index = zeros(0, 1);

    for i = 1:numLidarDetections
        bboxCuboid = lidarBbox(i, :);

        % Create cuboidModel
        model = cuboidModel(bboxCuboid);

        % Find points inside cuboid
        ind = findPointsInsideCuboid(model, outStruct);
        pts = select(outStruct, ind);

        % Project cuboid points to image
        imPts = projectLidarPointsOnImage(pts, intrinsic, lidarToCam);

        % Find 2-D rectangle corresponding to 3-D bounding box
        [nearestRect(i, :), idx] = findNearestRectangle(imPts, bboxes);

        % Limit the index to 10000
        idx = min(idx, 10000);
        index = [index; idx];

        % Calculate the median or mean distance from lidar points
        distances = sqrt(sum(pts.Location.^2, 2)); % Euclidean distance

        % Limit the detection distance to 10000
        distances = distances(distances <= 10000);

        if ~isempty(distances)
            distance(i) = mean(distances); % Use median or mean depending on your preference
        else
            distance(i) = NaN; % or any other value to indicate no valid distance within the range
        end
    end
end

function [nearestRect, idx] = findNearestRectangle(imPts, bboxes)
    numBbox = size(bboxes, 1);
    ratio = zeros(numBbox, 1);

    % Iterate over all the rectangles
    for i = 1:numBbox
        bbox = bboxes(i, :);
        corners = getCornersFromBbox(bbox);

        % Find overlapping ratio of the projected points and the rectangle
        idx = (imPts(:, 1) > corners(1, 1)) & (imPts(:, 1) < corners(2, 1)) & ...
            (imPts(:, 2) > corners(1, 2)) & (imPts(:, 2) < corners(3, 1));
        ratio(i) = sum(idx);
    end

    % Get nearest rectangle
    [~, idx] = max(ratio);
    nearestRect = bboxes(idx, :);
end

function cornersCamera = getCornersFromBbox(bbox)
    cornersCamera = zeros(4, 2);
    cornersCamera(1, 1:2) = bbox(1:2);
    cornersCamera(2, 1:2) = bbox(1:2) + [bbox(3), 0];
    cornersCamera(3, 1:2) = bbox(1:2) + bbox(3:4);
    cornersCamera(4, 1:2) = bbox(1:2) + [0,bbox(4)];
end

[Ramakrishna Mandalapu]

Hi Ahmed,

Make sure your codegen config is set up correctly for 'NVIDIA Jetson'. Add the following line to your codegen config:

cfg.Hardware = coder.hardware('NVIDIA Jetson');

cfg.Hardware.BuildDir = '~/timo';

From the error log, it seems the path might be inaccessible, as 'Timo/MATLAB_ws/R2023a/E/JetsonWork/....' may not exist on the target. Check the 'BuildDir' option in the hardware object above. As indicated in the code, the build directory will be created in the home directory. Ensure that the specified path is correct, either by providing the complete path like '/home/Timo/timo' or using aliases for home like '~/timo'. Configure 'BuildDir' in the hardware config accordingly and retry the build.

Ramakrishna