Size mismatch (size [1 x :?] ~= size [0 x 1]) - GPU Coder Deployment

Hello, I am trying to deploy a code from MATLAB to Jetson Nano,to summarize. This code is used to read live detections from a camera and Lidar VLP16, then It detects an object using the camera(eg.person), once the object is present on both camera and lidar, It computes the distance the object is from both LIDAR and Camera. Now, I am using helperComputeDistance function. I am going to provide step by step from my code.

Note that this code works perfectly when I run it on MATLAB, everything is fine. (Ofcourse I dont use obj, camObj, etc). I define LIDAR & camera normally.

function AliSamehTrial1(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('DistOfPerson: %.2f meters\n', distance);
        
    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('DistOfObj: %.2f meters\n', distance);
        
        % Update image with bounding boxes
        % im = updateImage(display, im, nearestRect, distance);
        % updateLidarBbox(display, lidarBbox)
    end
end

This is the main function, which has all the commands thats required.

As seen in this line of code:

[distance, nearestRect, idx] = helperComputeDistance(bboxes, nonGroundPts, lidarBbox, ...
            intrinsics, LidarToCam);

helperComputeDistance is used, I defined helperComputeDistance below here:

function [distance, nearestRect, index] = helperComputeDistance(bboxes, outStruct, lidarBbox, intrinsic, lidarToCam)
        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);
        index = [index, idx];
        

        % Calculate the median or mean distance from lidar points
        distances = sqrt(sum(pts.Location.^2, 2)); % Euclidean distance
        distance(i) = mean(distances); % Use median or mean depending on your preference
    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
end

However; I get this error

codegen('-config ',cfg,'-args',inputArgs,'AliSamehTrial1','-report');
Size mismatch (size [1 x :?] ~= size [0 x 1]).
The size to the left is the size of the left-hand side of the assignment.
More information
Error in ==> AliSamehTrial1 Line: 93 Column: 5

Line 93 is:

        index = [index, idx];

I tried doing the following:

        1- coder.extrinsic('helperComputeDistance');
        %This one didnt work.
        2- I tried coder.varsize('index')
        %This didnt work as well.
        %Or actually if someone can actually tell me how to properly use it

I do understand that this link here: https://www.mathworks.com/help/coder/ug/limitations-with-variable-size-support-for-code-generation.html

Most probably has solution to my issue, but I do not know how to implement it. So can somebody please help me?

[Ahmed Tamer]

Answer 1

[Bruno Luong]

Try to initialize

index = zeros(1, 0);

since you concatenate index horizontally in the for loop.

[Ahmed Tamer]

codegen('-config ',cfg,'-args',inputArgs,'AliSamehTrial1','-report');
Dimension 2 is fixed on the left-hand side but varies on the right ([1 x 1] ~= [1 x :?]).
More information
Error in ==> AliSamehTrial1 Line: 68 Column: 33
Code generation failed: View Error Report

Error using codegen

[Bruno Luong]

This seems to be different problem.

The previous error (line 93) in your original question seems to be fixed.

[Ahmed Tamer]

Any idea on what I should do?