Open Source Computer Vision Library https://opencv.org/
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
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// (including, but not limited to, procurement of substitute goods or services;
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//M*/
#include "test_precomp.hpp"
#ifdef HAVE_CUDA
using namespace std;
using namespace cv;
using namespace cv::cuda;
using namespace cvtest;
using namespace testing;
using namespace testing::internal;
//////////////////////////////////////////////////////////////////////
// Gpu devices
bool supportFeature(const DeviceInfo& info, FeatureSet feature)
{
return TargetArchs::builtWith(feature) && info.supports(feature);
}
DeviceManager& DeviceManager::instance()
{
static DeviceManager obj;
return obj;
}
void DeviceManager::load(int i)
{
devices_.clear();
devices_.reserve(1);
std::ostringstream msg;
if (i < 0 || i >= getCudaEnabledDeviceCount())
{
msg << "Incorrect device number - " << i;
CV_Error(cv::Error::StsBadArg, msg.str());
}
DeviceInfo info(i);
if (!info.isCompatible())
{
msg << "Device " << i << " [" << info.name() << "] is NOT compatible with current CUDA module build";
CV_Error(cv::Error::StsBadArg, msg.str());
}
devices_.push_back(info);
}
void DeviceManager::loadAll()
{
int deviceCount = getCudaEnabledDeviceCount();
devices_.clear();
devices_.reserve(deviceCount);
for (int i = 0; i < deviceCount; ++i)
{
DeviceInfo info(i);
if (info.isCompatible())
{
devices_.push_back(info);
}
}
}
#endif // HAVE_CUDA