CUDA Error - Semantic Segmentation

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Firat Erdem
Firat Erdem am 6 Okt. 2017
Beantwortet: Joss Knight am 16 Okt. 2017
Hello,
Using semantic segmentation, I want to separate the satellite image into two classes, water and land. I am having this problem: "An unexpected error occurred during CUDA execution. The CUDA error was: CUDA_ERROR_LAUNCH_FAILED"
How can I solve this problem ?
Here my codes :
clear;clc;close all
dataDir = fullfile('C:\Users\firat\Desktop\TEZ\Uygulama\Semantic Segmentation\data');
imDir = fullfile(dataDir,'image');
pxDir = fullfile(dataDir,'imagePixelLabels');
imds = imageDatastore(imDir);
I = readimage(imds,1);
figure
imshow(I)
% imageLabeler(imDir);
classNames = ["Water" "Land"];
pixelLabelID = [1 2];
pxds = pixelLabelDatastore(pxDir,classNames,pixelLabelID);
C = readimage(pxds,1);
B = labeloverlay(I,C);
figure
imshow(B)
buildingMask = C == 'Water';
figure
imshowpair(I, buildingMask,'montage')
% Create a Semantic Segmentation Network
numFilters = 64;
filterSize = 3;
numClasses = 2;
layers = [
imageInputLayer([1024 1024 3])
convolution2dLayer(filterSize,numFilters,'Padding',1)
reluLayer()
maxPooling2dLayer(2,'Stride',2)
convolution2dLayer(filterSize,numFilters,'Padding',1)
reluLayer()
transposedConv2dLayer(4,numFilters,'Stride',2,'Cropping',1);
convolution2dLayer(1,numClasses);
softmaxLayer()
pixelClassificationLayer()
]
opts = trainingOptions('sgdm', ...
'InitialLearnRate', 1e-3, ...
'MaxEpochs', 100, ...
'MiniBatchSize', 64);
trainingData = pixelLabelImageSource(imds,pxds);
net = trainNetwork(trainingData,layers,opts);
testImage = imread('C:\Users\firat\Desktop\TEZ\Uygulama\Semantic Segmentation\test\test3.tif');
C = semanticseg(testImage,net);
B = labeloverlay(testImage,C);
figure
imshow(B)
  2 Kommentare
Sean de Wolski
Sean de Wolski am 6 Okt. 2017
What's the output from?
>>gpuDevice
Firat Erdem
Firat Erdem am 6 Okt. 2017
ans =
CUDADevice with properties:
Name: 'GeForce 840M'
Index: 1.00
ComputeCapability: '5.0'
SupportsDouble: 1
DriverVersion: 9.00
ToolkitVersion: 8.00
MaxThreadsPerBlock: 1024.00
MaxShmemPerBlock: 49152.00
MaxThreadBlockSize: [1024.00 1024.00 64.00]
MaxGridSize: [2147483647.00 65535.00 65535.00]
SIMDWidth: 32.00
TotalMemory: 2147483648.00
MultiprocessorCount: 3.00
ClockRateKHz: 1124000.00
ComputeMode: 'Default'
GPUOverlapsTransfers: 1
KernelExecutionTimeout: 1
CanMapHostMemory: 1
DeviceSupported: 1
DeviceSelected: 1

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Antworten (1)

Joss Knight
Joss Knight am 16 Okt. 2017
This is almost guaranteed to be due to a kernel time-out - your GPU is also driving your graphics, and Windows imposes a time-out on long-running kernels to prevent the graphics freezing up. Try setting the TdrLevel registry key to 0 to turn off the time-outs, and see if the problem goes away.

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