Problem with Deploying YOLO 2 to Raspberry

3 次查看（过去 30 天）
Abdussalam Elhanashi
回答： Puru Kathuria 2021-2-25
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,

请先登录，再回答此问题。

回答（1 个）

Puru Kathuria
Puru Kathuria 2021-2-25
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.

类别

在 Help Center 和 File Exchange 中查找有关 Run on Target Hardware 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by