Problem with Deploying YOLO 2 to Raspberry

Hi guys

I am doing deployment of yolo 2 to raspi however i am recieving the problem. i think it is with the camera (w) and herein the the following error :-

>> Untitled3
 Deploying code. This may take a few minutes. 
??? Variable 'w' is not fully defined on some execution paths.

Error in ==> detectobjectvideostreamliveviaraspi Line: 13 Column: 17
Code generation failed: View Error Report
Error using codegen


Error in Untitled3 (line 33)
codegen('-config ', cfg,'detectobjectvideostreamliveviaraspi', '-report');

Here in the function that i am calling:-

function detectobjectvideostreamliveviaraspi()
%#codegen

persistent yolov2Obj;
if isempty(yolov2Obj)
    yolov2Obj = coder.loadDeepLearningNetwork('detectorYolo2.mat');

hwobj = raspi;
w = webcam(hwobj);

end
for i = 1:1800
 img = snapshot(w);
img=imresize(img,[640,480]);
     fps = 0;
     avgfps = [];
     tic;


    [bboxes,scores] = detect(yolov2Obj,img,'Threshold',0.4);
     newt = toc;
     % fps
fps = .9*fps + .1*(1/newt);
avgfps = [avgfps, fps]; %#ok<AGROW>
  if ~isempty(bboxes)
    I = insertObjectAnnotation(img,'rectangle',bboxes,scores);
  else
        I = img;
  end
 I  = insertText(I , [1, 1],  sprintf('FPS %2.2f', fps), 'FontSize', 26);    
 displayImage(hwobj,I,'Title','detectedImg');

end

and herein the deployment code to raspi

%Create a C++ code generation configuration object.

cfg = coder.config('exe');
cfg.TargetLang = 'C++';

%Specify Use of the ARM Compute Library. The ARM Compute Library provides optimized functionality for the Raspberry Pi hardware. To generate code that uses the ARM Compute Library, create a coder.ARMNEONConfig object. Specify the version of the ARM Compute Library installed on your Raspberry Pi and the architecture of the Raspberry Pi. Attach the deep learning configuration cbject to the code generation configuration object
dlcfg = coder.DeepLearningConfig('arm-compute');
supportedVersions = dlcfg.getARMComputeSupportedVersions;
dlcfg.ArmArchitecture = 'armv7';
dlcfg.ArmComputeVersion = '19.02';
cfg.DeepLearningConfig = dlcfg;

%Create a Connection to the Raspberry Pi

hwobj = raspi;

%Configure Code Generation Hardware Parameters for Raspberry Pi

hw = coder.hardware('Raspberry Pi');
cfg.Hardware = hw;

%Specify a build folder on the Raspberry Pi:

buildDir = '~/remoteBuildDir';
cfg.Hardware.BuildDir = buildDir;

%Provide a C++ Main File
CustomInclude=fullfile('codgen','exe','detectobjectvideostreamliveviaraspi','example');
cfg.CustomSource =fullfile('codgen','exe', 'detectobjectvideostreamliveviaraspi','example','main cu');
    yolov2Obj = coder.loadDeepLearningNetwork('detectorYolo2.mat');

%Generate the Executable Program on the Raspberry Pi
codegen('-config ', cfg,'detectobjectvideostreamliveviaraspi', '-report');

kindly looking for support

Best,

Answer 1

[Puru Kathuria]

The error states that there is a possible execution path where w is not defined. The call to webcam function might lead to an instance where w remains undefined.

To resolve this, you can try defining w with default values before calling webcam.So that for all the execution paths, w has a defined value.