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// ------------------------- OpenPose Resize Layer Testing -------------------------
// Third-party dependencies
#include <opencv2/opencv.hpp>
// Command-line user interface
#define OPENPOSE_FLAGS_DISABLE_POSE
#include <openpose/flags.hpp>
// OpenPose dependencies
#include <openpose/headers.hpp>
// Caffe dependencies
#ifdef USE_CAFFE
#include <caffe/blob.hpp>
#endif
// OpenCL dependencies
#ifdef USE_OPENCL
#include <openpose_private/gpu/opencl.hcl>
#include <openpose_private/gpu/cl2.hpp>
DEFINE_string(image_path, "examples/media/COCO_val2014_000000000192.jpg", "Process the desired image.");
// cv::Mat gpuResize(cv::Mat& img, const cv::Size& newSize)
// {
// #ifdef USE_CUDA
// // Upload to Source to GPU
// float* cpuPtr = &img.at<float>(0);
// float* gpuPtr;
// cudaMallocHost((void **)&gpuPtr, img.size().width * img.size().height * sizeof(float));
// cudaMemcpy(gpuPtr, cpuPtr, img.size().width * img.size().height * sizeof(float),
// cudaMemcpyHostToDevice);
// // Upload to Dest to GPU
// cv::Mat newImg = cv::Mat(newSize,CV_32FC1,cv::Scalar(0));
// float* newCpuPtr = &newImg.at<float>(0);
// float* newGpuPtr;
// cudaMallocHost((void **)&newGpuPtr, newSize.width * newSize.height * sizeof(float));
// cudaMemcpy(newGpuPtr, newCpuPtr, newSize.width * newSize.height * sizeof(float),
// cudaMemcpyHostToDevice);
// std::vector<const float*> sourcePtrs;
// sourcePtrs.emplace_back(gpuPtr);
// std::array<int, 4> targetSize = {1,1,newImg.size().height,newImg.size().width};
// std::array<int, 4> sourceSize = {1,1,img.size().height,img.size().width};
// std::vector<std::array<int, 4>> sourceSizes;
// sourceSizes.emplace_back(sourceSize);
// op::resizeAndMergeGpu(newGpuPtr, sourcePtrs, targetSize, sourceSizes);
// cudaMemcpy(newCpuPtr, newGpuPtr, newImg.size().width * newImg.size().height * sizeof(float),
// cudaMemcpyDeviceToHost);
// cudaFree(gpuPtr);
// cudaFree(newGpuPtr);
// return newImg;
// #else
// UNUSED(img);
// UNUSED(newSize);
// op::error("OpenPose must be compiled with the `USE_CAFFE` & `USE_CUDA` macro definitions in order to run"
// " this functionality.", __LINE__, __FUNCTION__, __FILE__);
// #endif
// }
// cv::Mat cpuResize(cv::Mat& img, cv::Size newSize)
// {
// // Upload to Source to GPU
// float* cpuPtr = &img.at<float>(0);
// // Upload to Dest to GPU
// cv::Mat newImg = cv::Mat(newSize,CV_32FC1,cv::Scalar(0));
// std::vector<const float*> sourcePtrs;
// sourcePtrs.emplace_back(cpuPtr);
// std::array<int, 4> targetSize = {1,1,newImg.size().height,newImg.size().width};
// std::array<int, 4> sourceSize = {1,1,img.size().height,img.size().width};
// std::vector<std::array<int, 4>> sourceSizes;
// sourceSizes.emplace_back(sourceSize);
// op::resizeAndMergeCpu(&newImg.at<float>(0), sourcePtrs, targetSize, sourceSizes);
// return newImg;
// }
typedef cl::KernelFunctor<cl::Buffer, int, int, float> ScaleFunctor;
const std::string scaleKernelString = MULTI_LINE_STRING(
__kernel void scaleKernel(__global float* targetPtr, const int targetWidth, const int targetHeight,
const float scale)
{
int x = get_global_id(0);
int y = get_global_id(1);
int c = get_global_id(2);
__global float* targetPtrC = &targetPtr[c*targetWidth*targetHeight];
targetPtrC[y*targetWidth+x] *= scale;
}
);
int clTest()
{
try
{
// logging_level
cv::Mat img = cv::imread(FLAGS_image_path);
if(img.empty())
op::error("Could not open or find the image: " + FLAGS_image_path, __LINE__, __FUNCTION__, __FILE__);
cv::Mat imgResize; cv::resize(img, imgResize, cv::Size(368,368));
cv::Mat imgFloat; imgResize.convertTo(imgFloat, CV_32FC3);
imgFloat /= 255.;
int imageVolume = imgFloat.size().width * imgFloat.size().height * imgFloat.channels();
std::cout << imgFloat.channels() << std::endl;
// Setup caffe
caffe::Caffe::set_mode(caffe::Caffe::GPU);
std::vector<int> devices;
const int maxNumberGpu = op::OpenCL::getTotalGPU();
for (auto i = 0; i < maxNumberGpu; i++){
devices.emplace_back(i);
std::cout << i << std::endl;
}
caffe::Caffe::SetDevices(devices);
// Load model
std::unique_ptr<caffe::Net<float>> upCaffeNet;
caffe::Caffe::set_mode(caffe::Caffe::GPU);
caffe::Caffe::SelectDevice(0, true);
upCaffeNet.reset(new caffe::Net<float>{
"models/pose/coco/pose_deploy_linevec.prototxt", caffe::TEST, caffe::Caffe::GetDefaultDevice()});
upCaffeNet->CopyTrainedLayersFrom("models/pose/coco/pose_iter_440000.caffemodel");
op::OpenCL::getInstance(0, CL_DEVICE_TYPE_GPU, true);
// Reshape net to image size
upCaffeNet->blobs()[0]->Reshape({1,imgFloat.channels(),imgResize.size().width,imgResize.size().height});
upCaffeNet->Reshape();
// Convert to caffe image
caffe::BlobProto blob_proto;
blob_proto.set_channels(3);
blob_proto.set_height(imgResize.size().width);
blob_proto.set_width(imgResize.size().height);
blob_proto.clear_data();
for (int c = 0; c < 3; ++c)
for (int h = 0; h < imgResize.size().height; ++h)
for (int w = 0; w < imgResize.size().width; ++w)
blob_proto.add_data(imgResize.at<cv::Vec3f>(h, w)[c]);
blob_proto.set_num(1);
caffe::Blob<float>* input_layer = upCaffeNet->input_blobs()[0];
input_layer->FromProto(blob_proto);
upCaffeNet->Forward(0);
boost::shared_ptr<caffe::Blob<float>> output_blob = upCaffeNet->blob_by_name("net_output");
// Test
cl::Device& device = op::OpenCL::getInstance(0)->getDevice();
cl_uint mem_align;
clGetDeviceInfo(device.get(), CL_DEVICE_MEM_BASE_ADDR_ALIGN, sizeof(mem_align), &mem_align, nullptr);
std::cout << "Alignment in bits of the base address : " << mem_align << std::endl;
// GPU Test
cv::Mat finalImage = imgFloat;
try{
// Get
float* gpuPtr = output_blob->mutable_gpu_data();
cl::Buffer outputBuffer((cl_mem)gpuPtr, true);
// Read it
// Read back image to GPU
float* heatmaps = new float[output_blob->shape()[1] * output_blob->shape()[2] * output_blob->shape()[3]];
op::OpenCL::getInstance(0)->getQueue().enqueueReadBuffer(
outputBuffer, CL_TRUE, 0,
output_blob->shape()[1] * output_blob->shape()[2] * output_blob->shape()[3] * sizeof(float), heatmaps);
int heatmapChannels = output_blob->shape()[1];
int shape = output_blob->shape()[2] * output_blob->shape()[3];
for(int i=0; i<heatmapChannels; i++){
cv::Mat hm(cv::Size(output_blob->shape()[2], output_blob->shape()[3]), CV_32FC1);
// Read subbuffer
cl_buffer_region sourceRegion;
op::OpenCL::getBufferRegion<float>(sourceRegion, i * shape, shape);
cl::Buffer regionBuffer = outputBuffer.createSubBuffer(CL_MEM_READ_WRITE,
CL_BUFFER_CREATE_TYPE_REGION,
&sourceRegion);
}
}
#if defined(USE_OPENCL) && defined(CL_HPP_ENABLE_EXCEPTIONS)
catch (const cl::Error& e)
{
op::error(std::string(e.what()) + " : " + op::OpenCL::clErrorToString(e.err()) + " ID: " +
std::to_string(0), __LINE__, __FUNCTION__, __FILE__);
}
#endif
catch (const std::exception& e)
{
op::error(e.what(), __LINE__, __FUNCTION__, __FILE__);
}
cv::imshow("win", finalImage);
cv::waitKey(0);
// Load model
// img.convertTo(img, CV_32FC1);
// img = cpuResize(img, cv::Size(img.size().width/4,img.size().height/4));
// img*=0.005;
// cv::Mat gpuImg = gpuResize(img, cv::Size(img.size().width*8,img.size().height*8));
// cv::Mat cpuImg = cpuResize(img, cv::Size(img.size().width*8,img.size().height*8));
// cv::imshow("gpuImg", gpuImg);
// cv::imshow("cpuImg", cpuImg);
// op::opLog("Done");
// cv::waitKey(0);
return 0;
}
catch (const std::exception& e)
{
op::error(e.what(), __LINE__, __FUNCTION__, __FILE__);
return -1;
}
}
#endif
int main()
{
#ifdef USE_OPENCL
// Parsing command line flags
gflags::ParseCommandLineFlags(&argc, &argv, true);
// Running handFromJsonTest
std::thread t(&clTest);
t.join();
return 0;
#else
op::error("OpenPose must be compiled with the `USE_CAFFE` & `USE_OPENCL` macro definitions in order to run"
" this functionality.", __LINE__, __FUNCTION__, __FILE__);
return -1;
#endif
}
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