haotian/duan8
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

retina fpn

Browse Source
This commit is contained in:
wang-xinyu 2020-04-07 13:11:10 +00:00
parent 18599b7f3a
commit d1c10789ba
2 changed files with 16 additions and 21 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

3
retinaface/README.md Normal file
View File

@ -0,0 +1,3 @@
# RetinaFace
still working in progress

34
retinaface/retina_r50.cpp
View File

@ -13,12 +13,12 @@
#include <opencv2/opencv.hpp>
//#define USE_FP16 // comment out this if want to use FP32
#define DEVICE 1 // GPU id
#define DEVICE 0 // GPU id
// stuff we know about the network and the input/output blobs
static const int INPUT_H = 384; //
static const int INPUT_W = 640;
static const int OUTPUT_SIZE = 256 * 24 * 40;
static const int OUTPUT_SIZE = 256 * 48 * 80;
const char* INPUT_BLOB_NAME = "data";
const char* OUTPUT_BLOB_NAME = "prob";
@ -324,28 +324,20 @@ ICudaEngine* createEngine(unsigned int maxBatchSize, IBuilder* builder, DataType
up3->setNbGroups(256);
weightMap["up3"] = deconvwts;
IElementWiseLayer* ew1 = network->addElementWise(*output2->getOutput(0), *up3->getOutput(0), ElementWiseOperation::kSUM);
assert(ew1);
output2 = network->addElementWise(*output2->getOutput(0), *up3->getOutput(0), ElementWiseOperation::kSUM);
output2 = conv_bn_relu(network, weightMap, *output2->getOutput(0), 256, 3, 1, 1, true, "fpn.merge2");
Dims dims = ew1->getOutput(0)->getDimensions();
std::cout << ew1->getOutput(0)->getName() << " dims";
for (int i = 0; i < dims.nbDims; i++) {
std::cout << dims.d[i] << "-" << (int)dims.type[i] << " ";
}
std::cout << std::endl;
IDeconvolutionLayer* up2 = network->addDeconvolution(*output2->getOutput(0), 256, DimsHW{2, 2}, deconvwts, emptywts);
assert(up2);
up2->setStride(DimsHW{2, 2});
up2->setNbGroups(256);
output1 = network->addElementWise(*output1->getOutput(0), *up2->getOutput(0), ElementWiseOperation::kSUM);
output1 = conv_bn_relu(network, weightMap, *output1->getOutput(0), 256, 3, 1, 1, true, "fpn.merge1");
//output2 = conv_bn_relu(network, weightMap, *ew1->getOutput(0), 256, 3, 1, 1, true, "fpn.merge2");
//IDeconvolutionLayer* up2 = network->addDeconvolution(*output2->getOutput(0), 256, DimsHW{2, 2}, deconvwts, emptywts);
//assert(up2);
//up2->setStride(DimsHW{2, 2});
//up2->setNbGroups(256);
//output1 = network->addElementWise(*output1->getOutput(0), *up2->getOutput(0), ElementWiseOperation::kSUM);
//output1 = conv_bn_relu(network, weightMap, *output1->getOutput(0), 256, 3, 1, 1, true, "fpn.merge1");
ew1->getOutput(0)->setName(OUTPUT_BLOB_NAME);
// ------------- SSH ---------------
output1->getOutput(0)->setName(OUTPUT_BLOB_NAME);
std::cout << "set name out" << std::endl;
network->markOutput(*ew1->getOutput(0));
network->markOutput(*output1->getOutput(0));
// Build engine
builder->setMaxBatchSize(maxBatchSize);