2433 lines
156 KiB
C++
2433 lines
156 KiB
C++
#include <iostream>
|
|
#include <chrono>
|
|
#include <cmath>
|
|
#include "cuda_utils.h"
|
|
#include "logging.h"
|
|
#include "common.hpp"
|
|
#include "utils.h"
|
|
#include "calibrator.h"
|
|
#include "preprocess.h"
|
|
|
|
#define USE_FP16 // set USE_INT8 or USE_FP16 or USE_FP32
|
|
#define DEVICE 0 // GPU id
|
|
#define NMS_THRESH 0.45
|
|
#define CONF_THRESH 0.25
|
|
#define BATCH_SIZE 1
|
|
#define MAX_IMAGE_INPUT_SIZE_THRESH 3000 * 3000 // max input image buffer size
|
|
|
|
// stuff we know about the network and the input/output blobs
|
|
static const int INPUT_H = Yolo::INPUT_H;
|
|
static const int INPUT_W = Yolo::INPUT_W;
|
|
static const int CLASS_NUM = Yolo::CLASS_NUM;
|
|
static const int OUTPUT_SIZE = Yolo::MAX_OUTPUT_BBOX_COUNT * sizeof(Yolo::Detection) / sizeof(float) + 1; // we assume the yololayer outputs no more than MAX_OUTPUT_BBOX_COUNT boxes that conf >= 0.1
|
|
const char* INPUT_BLOB_NAME = "data";
|
|
const char* OUTPUT_BLOB_NAME = "prob";
|
|
static Logger gLogger;
|
|
|
|
|
|
static int get_width(int x, float gw, int divisor = 8) {
|
|
return int(ceil((x * gw) / divisor)) * divisor;
|
|
}
|
|
|
|
static int get_depth(int x, float gd) {
|
|
if (x == 1) return 1;
|
|
int r = round(x * gd);
|
|
if (x * gd - int(x * gd) == 0.5 && (int(x * gd) % 2) == 0) {
|
|
--r;
|
|
}
|
|
return std::max<int>(r, 1);
|
|
}
|
|
|
|
ICudaEngine* build_engine_yolov7e6e(unsigned int maxBatchSize, IBuilder* builder, IBuilderConfig* config, DataType dt, const std::string& wts_path) {
|
|
std::map<std::string, Weights> weightMap = loadWeights(wts_path);
|
|
|
|
INetworkDefinition* network = builder->createNetworkV2(0U);
|
|
ITensor* data = network->addInput(INPUT_BLOB_NAME, dt, Dims3{ 3, INPUT_H, INPUT_W });
|
|
assert(data);
|
|
|
|
auto* conv0 = ReOrg(network, weightMap, *data, 3);
|
|
|
|
|
|
IElementWiseLayer* conv1 = convBnSilu(network, weightMap, *conv0->getOutput(0), 80, 3, 1, 1, "model.1");
|
|
auto conv2 = DownC(network, weightMap, *conv1->getOutput(0), 80, 160, "model.2");
|
|
|
|
IElementWiseLayer* conv3 = convBnSilu(network, weightMap, *conv2->getOutput(0), 64, 1, 1, 0, "model.3");
|
|
IElementWiseLayer* conv4 = convBnSilu(network, weightMap, *conv2->getOutput(0), 64, 1, 1, 0, "model.4");
|
|
|
|
IElementWiseLayer* conv5 = convBnSilu(network, weightMap, *conv4->getOutput(0), 64, 3, 1, 1, "model.5");
|
|
IElementWiseLayer* conv6 = convBnSilu(network, weightMap, *conv5->getOutput(0), 64, 3, 1, 1, "model.6");
|
|
IElementWiseLayer* conv7 = convBnSilu(network, weightMap, *conv6->getOutput(0), 64, 3, 1, 1, "model.7");
|
|
IElementWiseLayer* conv8 = convBnSilu(network, weightMap, *conv7->getOutput(0), 64, 3, 1, 1, "model.8");
|
|
IElementWiseLayer* conv9 = convBnSilu(network, weightMap, *conv8->getOutput(0), 64, 3, 1, 1, "model.9");
|
|
IElementWiseLayer* conv10 = convBnSilu(network, weightMap, *conv9->getOutput(0), 64, 3, 1, 1, "model.10");
|
|
|
|
ITensor* input_tensor_11[] = { conv10->getOutput(0), conv8->getOutput(0),conv6->getOutput(0), conv4->getOutput(0),
|
|
conv3->getOutput(0) };
|
|
IConcatenationLayer* concat11 = network->addConcatenation(input_tensor_11, 5);
|
|
|
|
IElementWiseLayer* conv12 = convBnSilu(network, weightMap, *concat11->getOutput(0), 160, 1, 1, 0, "model.12");
|
|
|
|
|
|
IElementWiseLayer* conv13 = convBnSilu(network, weightMap, *conv2->getOutput(0), 64, 1, 1, 0, "model.13");
|
|
IElementWiseLayer* conv14 = convBnSilu(network, weightMap, *conv2->getOutput(0), 64, 1, 1, 0, "model.14");
|
|
|
|
IElementWiseLayer* conv15 = convBnSilu(network, weightMap, *conv14->getOutput(0), 64, 3, 1, 1, "model.15");
|
|
IElementWiseLayer* conv16 = convBnSilu(network, weightMap, *conv15->getOutput(0), 64, 3, 1, 1, "model.16");
|
|
IElementWiseLayer* conv17 = convBnSilu(network, weightMap, *conv16->getOutput(0), 64, 3, 1, 1, "model.17");
|
|
IElementWiseLayer* conv18 = convBnSilu(network, weightMap, *conv17->getOutput(0), 64, 3, 1, 1, "model.18");
|
|
IElementWiseLayer* conv19 = convBnSilu(network, weightMap, *conv18->getOutput(0), 64, 3, 1, 1, "model.19");
|
|
IElementWiseLayer* conv20 = convBnSilu(network, weightMap, *conv19->getOutput(0), 64, 3, 1, 1, "model.20");
|
|
ITensor* input_tensor_21[] = { conv20->getOutput(0), conv18->getOutput(0),conv16->getOutput(0), conv14->getOutput(0),
|
|
conv13->getOutput(0) };
|
|
IConcatenationLayer* concat21 = network->addConcatenation(input_tensor_21, 5);
|
|
|
|
IElementWiseLayer* conv22 = convBnSilu(network, weightMap, *concat21->getOutput(0), 160, 1, 1, 0, "model.22");
|
|
auto conv23 = network->addElementWise(*conv22->getOutput(0), *conv12->getOutput(0), ElementWiseOperation::kSUM);
|
|
|
|
auto conv24 = DownC(network, weightMap, *conv23->getOutput(0), 160, 320, "model.24");
|
|
IElementWiseLayer* conv25 = convBnSilu(network, weightMap, *conv24->getOutput(0), 128, 1, 1, 0, "model.25");
|
|
IElementWiseLayer* conv26 = convBnSilu(network, weightMap, *conv24->getOutput(0), 128, 1, 1, 0, "model.26");
|
|
|
|
IElementWiseLayer* conv27 = convBnSilu(network, weightMap, *conv26->getOutput(0), 128, 3, 1, 1, "model.27");
|
|
IElementWiseLayer* conv28 = convBnSilu(network, weightMap, *conv27->getOutput(0), 128, 3, 1, 1, "model.28");
|
|
IElementWiseLayer* conv29 = convBnSilu(network, weightMap, *conv28->getOutput(0), 128, 3, 1, 1, "model.29");
|
|
IElementWiseLayer* conv30 = convBnSilu(network, weightMap, *conv29->getOutput(0), 128, 3, 1, 1, "model.30");
|
|
IElementWiseLayer* conv31 = convBnSilu(network, weightMap, *conv30->getOutput(0), 128, 3, 1, 1, "model.31");
|
|
IElementWiseLayer* conv32 = convBnSilu(network, weightMap, *conv31->getOutput(0), 128, 3, 1, 1, "model.32");
|
|
|
|
ITensor* input_tensor_33[] = { conv32->getOutput(0), conv30->getOutput(0),conv28->getOutput(0), conv26->getOutput(0),
|
|
conv25->getOutput(0)};
|
|
IConcatenationLayer* concat33 = network->addConcatenation(input_tensor_33, 5);
|
|
|
|
IElementWiseLayer* conv34 = convBnSilu(network, weightMap, *concat33->getOutput(0), 320, 1, 1, 0, "model.34");
|
|
|
|
IElementWiseLayer* conv35 = convBnSilu(network, weightMap, *conv24->getOutput(0), 128, 1, 1, 0, "model.35");
|
|
IElementWiseLayer* conv36 = convBnSilu(network, weightMap, *conv24->getOutput(0), 128, 1, 1, 0, "model.36");
|
|
|
|
IElementWiseLayer* conv37 = convBnSilu(network, weightMap, *conv36->getOutput(0), 128, 3, 1, 1, "model.37");
|
|
IElementWiseLayer* conv38 = convBnSilu(network, weightMap, *conv37->getOutput(0), 128, 3, 1, 1, "model.38");
|
|
IElementWiseLayer* conv39 = convBnSilu(network, weightMap, *conv38->getOutput(0), 128, 3, 1, 1, "model.39");
|
|
IElementWiseLayer* conv40 = convBnSilu(network, weightMap, *conv39->getOutput(0), 128, 3, 1, 1, "model.40");
|
|
IElementWiseLayer* conv41 = convBnSilu(network, weightMap, *conv40->getOutput(0), 128, 3, 1, 1, "model.41");
|
|
IElementWiseLayer* conv42 = convBnSilu(network, weightMap, *conv41->getOutput(0), 128, 3, 1, 1, "model.42");
|
|
|
|
ITensor* input_tensor_43[] = { conv42->getOutput(0), conv40->getOutput(0),conv38->getOutput(0), conv36->getOutput(0),
|
|
conv35->getOutput(0)};
|
|
IConcatenationLayer* concat43 = network->addConcatenation(input_tensor_43, 5);
|
|
IElementWiseLayer* conv44 = convBnSilu(network, weightMap, *concat43->getOutput(0), 320, 1, 1, 0, "model.44");
|
|
|
|
auto conv45 = network->addElementWise(*conv44->getOutput(0), *conv34->getOutput(0), ElementWiseOperation::kSUM);
|
|
|
|
auto conv46 = DownC(network, weightMap, *conv45->getOutput(0), 320, 640, "model.46");//=====
|
|
|
|
|
|
IElementWiseLayer* conv47 = convBnSilu(network, weightMap, *conv46->getOutput(0), 256, 1, 1, 0, "model.47");
|
|
IElementWiseLayer* conv48 = convBnSilu(network, weightMap, *conv46->getOutput(0), 256, 1, 1, 0, "model.48");
|
|
|
|
IElementWiseLayer* conv49 = convBnSilu(network, weightMap, *conv48->getOutput(0), 256, 3, 1, 1, "model.49");
|
|
IElementWiseLayer* conv50 = convBnSilu(network, weightMap, *conv49->getOutput(0), 256, 3, 1, 1, "model.50");
|
|
IElementWiseLayer* conv51 = convBnSilu(network, weightMap, *conv50->getOutput(0), 256, 3, 1, 1, "model.51");
|
|
IElementWiseLayer* conv52 = convBnSilu(network, weightMap, *conv51->getOutput(0), 256, 3, 1, 1, "model.52");
|
|
IElementWiseLayer* conv53 = convBnSilu(network, weightMap, *conv52->getOutput(0), 256, 3, 1, 1, "model.53");
|
|
IElementWiseLayer* conv54 = convBnSilu(network, weightMap, *conv53->getOutput(0), 256, 3, 1, 1, "model.54");
|
|
|
|
ITensor* input_tensor_55[] = { conv54->getOutput(0), conv52->getOutput(0),conv50->getOutput(0), conv48->getOutput(0),
|
|
conv47->getOutput(0) };
|
|
IConcatenationLayer* concat55 = network->addConcatenation(input_tensor_55, 5);
|
|
IElementWiseLayer* conv56 = convBnSilu(network, weightMap, *concat55->getOutput(0), 640, 1, 1, 0, "model.56");
|
|
|
|
IElementWiseLayer* conv57 = convBnSilu(network, weightMap, *conv46->getOutput(0), 256, 1, 1, 0, "model.57");
|
|
IElementWiseLayer* conv58 = convBnSilu(network, weightMap, *conv46->getOutput(0), 256, 1, 1, 0, "model.58");
|
|
|
|
IElementWiseLayer* conv59 = convBnSilu(network, weightMap, *conv58->getOutput(0), 256, 3, 1, 1, "model.59");
|
|
IElementWiseLayer* conv60 = convBnSilu(network, weightMap, *conv59->getOutput(0), 256, 3, 1, 1, "model.60");
|
|
IElementWiseLayer* conv61 = convBnSilu(network, weightMap, *conv60->getOutput(0), 256, 3, 1, 1, "model.61");
|
|
IElementWiseLayer* conv62 = convBnSilu(network, weightMap, *conv61->getOutput(0), 256, 3, 1, 1, "model.62");
|
|
IElementWiseLayer* conv63 = convBnSilu(network, weightMap, *conv62->getOutput(0), 256, 3, 1, 1, "model.63");
|
|
IElementWiseLayer* conv64 = convBnSilu(network, weightMap, *conv63->getOutput(0), 256, 3, 1, 1, "model.64");
|
|
ITensor* input_tensor_65[] = { conv64->getOutput(0), conv62->getOutput(0),conv60->getOutput(0), conv58->getOutput(0),
|
|
conv57->getOutput(0) };
|
|
IConcatenationLayer* concat65 = network->addConcatenation(input_tensor_65, 5);
|
|
IElementWiseLayer* conv66 = convBnSilu(network, weightMap, *concat65->getOutput(0), 640, 1, 1, 0, "model.66");
|
|
auto conv67 = network->addElementWise(*conv66->getOutput(0), *conv56->getOutput(0), ElementWiseOperation::kSUM);
|
|
|
|
auto conv68 = DownC(network, weightMap, *conv67->getOutput(0), 640, 960, "model.68");//=====
|
|
|
|
IElementWiseLayer* conv69 = convBnSilu(network, weightMap, *conv68->getOutput(0), 384, 1, 1, 0, "model.69");
|
|
IElementWiseLayer* conv70 = convBnSilu(network, weightMap, *conv68->getOutput(0), 384, 1, 1, 0, "model.70");
|
|
|
|
IElementWiseLayer* conv71 = convBnSilu(network, weightMap, *conv70->getOutput(0), 384, 3, 1, 1, "model.71");
|
|
IElementWiseLayer* conv72 = convBnSilu(network, weightMap, *conv71->getOutput(0), 384, 3, 1, 1, "model.72");
|
|
IElementWiseLayer* conv73 = convBnSilu(network, weightMap, *conv72->getOutput(0), 384, 3, 1, 1, "model.73");
|
|
IElementWiseLayer* conv74 = convBnSilu(network, weightMap, *conv73->getOutput(0), 384, 3, 1, 1, "model.74");
|
|
IElementWiseLayer* conv75 = convBnSilu(network, weightMap, *conv74->getOutput(0), 384, 3, 1, 1, "model.75");
|
|
IElementWiseLayer* conv76 = convBnSilu(network, weightMap, *conv75->getOutput(0), 384, 3, 1, 1, "model.76");
|
|
ITensor* input_tensor_77[] = { conv76->getOutput(0), conv74->getOutput(0),conv72->getOutput(0), conv70->getOutput(0),
|
|
conv69->getOutput(0) };
|
|
IConcatenationLayer* concat77 = network->addConcatenation(input_tensor_77, 5);
|
|
IElementWiseLayer* conv78 = convBnSilu(network, weightMap, *concat77->getOutput(0), 960, 1, 1, 0, "model.78");
|
|
|
|
IElementWiseLayer* conv79 = convBnSilu(network, weightMap, *conv68->getOutput(0), 384, 1, 1, 0, "model.79");
|
|
IElementWiseLayer* conv80 = convBnSilu(network, weightMap, *conv68->getOutput(0), 384, 1, 1, 0, "model.80");
|
|
|
|
IElementWiseLayer* conv81 = convBnSilu(network, weightMap, *conv80->getOutput(0), 384, 3, 1, 1, "model.81");
|
|
IElementWiseLayer* conv82 = convBnSilu(network, weightMap, *conv81->getOutput(0), 384, 3, 1, 1, "model.82");
|
|
IElementWiseLayer* conv83 = convBnSilu(network, weightMap, *conv82->getOutput(0), 384, 3, 1, 1, "model.83");
|
|
IElementWiseLayer* conv84 = convBnSilu(network, weightMap, *conv83->getOutput(0), 384, 3, 1, 1, "model.84");
|
|
IElementWiseLayer* conv85 = convBnSilu(network, weightMap, *conv84->getOutput(0), 384, 3, 1, 1, "model.85");
|
|
IElementWiseLayer* conv86 = convBnSilu(network, weightMap, *conv85->getOutput(0), 384, 3, 1, 1, "model.86");
|
|
ITensor* input_tensor_87[] = { conv86->getOutput(0), conv84->getOutput(0),conv82->getOutput(0), conv80->getOutput(0),
|
|
conv79->getOutput(0) };
|
|
IConcatenationLayer* concat87 = network->addConcatenation(input_tensor_87, 5);
|
|
IElementWiseLayer* conv88 = convBnSilu(network, weightMap, *concat87->getOutput(0), 960, 1, 1, 0, "model.88");
|
|
auto conv89 = network->addElementWise(*conv88->getOutput(0), *conv78->getOutput(0), ElementWiseOperation::kSUM);
|
|
|
|
|
|
auto conv90 = DownC(network, weightMap, *conv89->getOutput(0), 960, 1280, "model.90");
|
|
|
|
IElementWiseLayer* conv91 = convBnSilu(network, weightMap, *conv90->getOutput(0), 512, 1, 1, 0, "model.91");
|
|
IElementWiseLayer* conv92 = convBnSilu(network, weightMap, *conv90->getOutput(0), 512, 1, 1, 0, "model.92");
|
|
|
|
IElementWiseLayer* conv93 = convBnSilu(network, weightMap, *conv92->getOutput(0), 512, 3, 1, 1, "model.93");
|
|
IElementWiseLayer* conv94 = convBnSilu(network, weightMap, *conv93->getOutput(0), 512, 3, 1, 1, "model.94");
|
|
IElementWiseLayer* conv95 = convBnSilu(network, weightMap, *conv94->getOutput(0), 512, 3, 1, 1, "model.95");
|
|
IElementWiseLayer* conv96 = convBnSilu(network, weightMap, *conv95->getOutput(0), 512, 3, 1, 1, "model.96");
|
|
IElementWiseLayer* conv97 = convBnSilu(network, weightMap, *conv96->getOutput(0), 512, 3, 1, 1, "model.97");
|
|
IElementWiseLayer* conv98 = convBnSilu(network, weightMap, *conv97->getOutput(0), 512, 3, 1, 1, "model.98");
|
|
ITensor* input_tensor_99[] = { conv98->getOutput(0), conv96->getOutput(0),conv94->getOutput(0), conv92->getOutput(0),
|
|
conv91->getOutput(0) };
|
|
IConcatenationLayer* concat99 = network->addConcatenation(input_tensor_99, 5);
|
|
IElementWiseLayer* conv100 = convBnSilu(network, weightMap, *concat99->getOutput(0), 1280, 1, 1, 0, "model.100");
|
|
|
|
IElementWiseLayer* conv101 = convBnSilu(network, weightMap, *conv90->getOutput(0), 512, 1, 1, 0, "model.101");
|
|
IElementWiseLayer* conv102 = convBnSilu(network, weightMap, *conv90->getOutput(0), 512, 1, 1, 0, "model.102");
|
|
|
|
IElementWiseLayer* conv103 = convBnSilu(network, weightMap, *conv102->getOutput(0), 512, 3, 1, 1, "model.103");
|
|
IElementWiseLayer* conv104 = convBnSilu(network, weightMap, *conv103->getOutput(0), 512, 3, 1, 1, "model.104");
|
|
IElementWiseLayer* conv105 = convBnSilu(network, weightMap, *conv104->getOutput(0), 512, 3, 1, 1, "model.105");
|
|
IElementWiseLayer* conv106 = convBnSilu(network, weightMap, *conv105->getOutput(0), 512, 3, 1, 1, "model.106");
|
|
IElementWiseLayer* conv107 = convBnSilu(network, weightMap, *conv106->getOutput(0), 512, 3, 1, 1, "model.107");
|
|
IElementWiseLayer* conv108 = convBnSilu(network, weightMap, *conv107->getOutput(0), 512, 3, 1, 1, "model.108");
|
|
ITensor* input_tensor_109[] = { conv108->getOutput(0), conv106->getOutput(0),conv104->getOutput(0), conv102->getOutput(0),
|
|
conv101->getOutput(0) };
|
|
IConcatenationLayer* concat109 = network->addConcatenation(input_tensor_109, 5);
|
|
IElementWiseLayer* conv110 = convBnSilu(network, weightMap, *concat109->getOutput(0), 1280, 1, 1, 0, "model.110");
|
|
auto conv111 = network->addElementWise(*conv110->getOutput(0), *conv100->getOutput(0), ElementWiseOperation::kSUM);
|
|
//---------------------------yolov7e6e head---------------------------------
|
|
auto conv112 = SPPCSPC(network, weightMap, *conv111->getOutput(0), 640, "model.112");
|
|
IElementWiseLayer* conv113 = convBnSilu(network, weightMap, *conv112->getOutput(0), 480, 1, 1, 0, "model.113");
|
|
|
|
|
|
float scale[] = { 1.0, 2.0, 2.0 };
|
|
IResizeLayer* re114 = network->addResize(*conv113->getOutput(0));
|
|
re114->setResizeMode(ResizeMode::kNEAREST);
|
|
re114->setScales(scale, 3);
|
|
|
|
IElementWiseLayer* conv115 = convBnSilu(network, weightMap, *conv89->getOutput(0), 480, 1, 1, 0, "model.115");
|
|
ITensor* input_tensor_116[] = { conv115->getOutput(0), re114->getOutput(0) };
|
|
IConcatenationLayer* concat116 = network->addConcatenation(input_tensor_116, 2);
|
|
|
|
|
|
IElementWiseLayer* conv117 = convBnSilu(network, weightMap, *concat116->getOutput(0), 384, 1, 1, 0, "model.117");
|
|
IElementWiseLayer* conv118 = convBnSilu(network, weightMap, *concat116->getOutput(0), 384, 1, 1, 0, "model.118");
|
|
|
|
IElementWiseLayer* conv119 = convBnSilu(network, weightMap, *conv118->getOutput(0), 192, 3, 1, 1, "model.119");
|
|
IElementWiseLayer* conv120 = convBnSilu(network, weightMap, *conv119->getOutput(0), 192, 3, 1, 1, "model.120");
|
|
IElementWiseLayer* conv121 = convBnSilu(network, weightMap, *conv120->getOutput(0), 192, 3, 1, 1, "model.121");
|
|
IElementWiseLayer* conv122 = convBnSilu(network, weightMap, *conv121->getOutput(0), 192, 3, 1, 1, "model.122");
|
|
IElementWiseLayer* conv123 = convBnSilu(network, weightMap, *conv122->getOutput(0), 192, 3, 1, 1, "model.123");
|
|
IElementWiseLayer* conv124 = convBnSilu(network, weightMap, *conv123->getOutput(0), 192, 3, 1, 1, "model.124");
|
|
ITensor* input_tensor_125[] = { conv124->getOutput(0), conv123->getOutput(0),conv122->getOutput(0), conv121->getOutput(0),
|
|
conv120->getOutput(0), conv119->getOutput(0), conv118->getOutput(0), conv117->getOutput(0) };
|
|
IConcatenationLayer* concat125 = network->addConcatenation(input_tensor_125, 8);
|
|
IElementWiseLayer* conv126 = convBnSilu(network, weightMap, *concat125->getOutput(0), 480, 1, 1, 0, "model.126");
|
|
|
|
IElementWiseLayer* conv127 = convBnSilu(network, weightMap, *concat116->getOutput(0), 384, 1, 1, 0, "model.127");
|
|
IElementWiseLayer* conv128 = convBnSilu(network, weightMap, *concat116->getOutput(0), 384, 1, 1, 0, "model.128");
|
|
|
|
IElementWiseLayer* conv129 = convBnSilu(network, weightMap, *conv128->getOutput(0), 192, 3, 1, 1, "model.129");
|
|
IElementWiseLayer* conv130 = convBnSilu(network, weightMap, *conv129->getOutput(0), 192, 3, 1, 1, "model.130");
|
|
IElementWiseLayer* conv131 = convBnSilu(network, weightMap, *conv130->getOutput(0), 192, 3, 1, 1, "model.131");
|
|
IElementWiseLayer* conv132 = convBnSilu(network, weightMap, *conv131->getOutput(0), 192, 3, 1, 1, "model.132");
|
|
IElementWiseLayer* conv133 = convBnSilu(network, weightMap, *conv132->getOutput(0), 192, 3, 1, 1, "model.133");
|
|
IElementWiseLayer* conv134 = convBnSilu(network, weightMap, *conv133->getOutput(0), 192, 3, 1, 1, "model.134");
|
|
ITensor* input_tensor_135[] = { conv134->getOutput(0), conv133->getOutput(0),conv132->getOutput(0), conv131->getOutput(0),
|
|
conv130->getOutput(0), conv129->getOutput(0), conv128->getOutput(0), conv127->getOutput(0) };
|
|
IConcatenationLayer* concat135 = network->addConcatenation(input_tensor_135, 8);
|
|
IElementWiseLayer* conv136 = convBnSilu(network, weightMap, *concat135->getOutput(0), 480, 1, 1, 0, "model.136");
|
|
auto conv137 = network->addElementWise(*conv136->getOutput(0), *conv126->getOutput(0), ElementWiseOperation::kSUM);
|
|
|
|
IElementWiseLayer* conv138 = convBnSilu(network, weightMap, *conv137->getOutput(0), 320, 1, 1, 0, "model.138");
|
|
IResizeLayer* re139 = network->addResize(*conv138->getOutput(0));
|
|
re139->setResizeMode(ResizeMode::kNEAREST);
|
|
re139->setScales(scale, 3);
|
|
IElementWiseLayer* conv140 = convBnSilu(network, weightMap, *conv67->getOutput(0), 320, 1, 1, 0, "model.140");
|
|
ITensor* input_tensor_141[] = { conv140->getOutput(0), re139->getOutput(0) };
|
|
IConcatenationLayer* concat141 = network->addConcatenation(input_tensor_141, 2);
|
|
|
|
IElementWiseLayer* conv142 = convBnSilu(network, weightMap, *concat141->getOutput(0), 256, 1, 1, 0, "model.142");
|
|
IElementWiseLayer* conv143 = convBnSilu(network, weightMap, *concat141->getOutput(0), 256, 1, 1, 0, "model.143");
|
|
|
|
IElementWiseLayer* conv144 = convBnSilu(network, weightMap, *conv143->getOutput(0), 128, 3, 1, 1, "model.144");
|
|
IElementWiseLayer* conv145 = convBnSilu(network, weightMap, *conv144->getOutput(0), 128, 3, 1, 1, "model.145");
|
|
IElementWiseLayer* conv146 = convBnSilu(network, weightMap, *conv145->getOutput(0), 128, 3, 1, 1, "model.146");
|
|
IElementWiseLayer* conv147 = convBnSilu(network, weightMap, *conv146->getOutput(0), 128, 3, 1, 1, "model.147");
|
|
IElementWiseLayer* conv148 = convBnSilu(network, weightMap, *conv147->getOutput(0), 128, 3, 1, 1, "model.148");
|
|
IElementWiseLayer* conv149 = convBnSilu(network, weightMap, *conv148->getOutput(0), 128, 3, 1, 1, "model.149");
|
|
|
|
ITensor* input_tensor_150[] = { conv149->getOutput(0), conv148->getOutput(0),conv147->getOutput(0), conv146->getOutput(0),
|
|
conv145->getOutput(0), conv144->getOutput(0), conv143->getOutput(0), conv142->getOutput(0) };
|
|
IConcatenationLayer* concat150 = network->addConcatenation(input_tensor_150, 8);
|
|
|
|
IElementWiseLayer* conv151 = convBnSilu(network, weightMap, *concat150->getOutput(0), 320, 1, 1, 0, "model.151");
|
|
|
|
IElementWiseLayer* conv152 = convBnSilu(network, weightMap, *concat141->getOutput(0), 256, 1, 1, 0, "model.152");
|
|
IElementWiseLayer* conv153 = convBnSilu(network, weightMap, *concat141->getOutput(0), 256, 1, 1, 0, "model.153");
|
|
|
|
IElementWiseLayer* conv154 = convBnSilu(network, weightMap, *conv153->getOutput(0), 128, 3, 1, 1, "model.154");
|
|
IElementWiseLayer* conv155 = convBnSilu(network, weightMap, *conv154->getOutput(0), 128, 3, 1, 1, "model.155");
|
|
IElementWiseLayer* conv156 = convBnSilu(network, weightMap, *conv155->getOutput(0), 128, 3, 1, 1, "model.156");
|
|
IElementWiseLayer* conv157 = convBnSilu(network, weightMap, *conv156->getOutput(0), 128, 3, 1, 1, "model.157");
|
|
IElementWiseLayer* conv158 = convBnSilu(network, weightMap, *conv157->getOutput(0), 128, 3, 1, 1, "model.158");
|
|
IElementWiseLayer* conv159 = convBnSilu(network, weightMap, *conv158->getOutput(0), 128, 3, 1, 1, "model.159");
|
|
ITensor* input_tensor_160[] = { conv159->getOutput(0), conv158->getOutput(0),conv157->getOutput(0), conv156->getOutput(0),
|
|
conv155->getOutput(0), conv154->getOutput(0), conv153->getOutput(0), conv152->getOutput(0) };
|
|
IConcatenationLayer* concat160 = network->addConcatenation(input_tensor_160, 8);
|
|
IElementWiseLayer* conv161 = convBnSilu(network, weightMap, *concat160->getOutput(0), 320, 1, 1, 0, "model.161");
|
|
auto conv162 = network->addElementWise(*conv161->getOutput(0), *conv151->getOutput(0), ElementWiseOperation::kSUM);
|
|
|
|
IElementWiseLayer* conv163 = convBnSilu(network, weightMap, *conv162->getOutput(0), 160, 1, 1, 0, "model.163");
|
|
|
|
IResizeLayer* re164 = network->addResize(*conv163->getOutput(0));
|
|
re164->setResizeMode(ResizeMode::kNEAREST);
|
|
re164->setScales(scale, 3);
|
|
|
|
IElementWiseLayer* conv165 = convBnSilu(network, weightMap, *conv45->getOutput(0), 160, 1, 1, 0, "model.165");
|
|
ITensor* input_tensor_166[] = { conv165->getOutput(0), re164->getOutput(0) };
|
|
IConcatenationLayer* concat166 = network->addConcatenation(input_tensor_166, 2);
|
|
|
|
IElementWiseLayer* conv167 = convBnSilu(network, weightMap, *concat166->getOutput(0), 128, 1, 1, 0, "model.167");
|
|
IElementWiseLayer* conv168 = convBnSilu(network, weightMap, *concat166->getOutput(0), 128, 1, 1, 0, "model.168");
|
|
IElementWiseLayer* conv169 = convBnSilu(network, weightMap, *conv168->getOutput(0), 64, 3, 1, 1, "model.169");
|
|
IElementWiseLayer* conv170 = convBnSilu(network, weightMap, *conv169->getOutput(0), 64, 3, 1, 1, "model.170");
|
|
IElementWiseLayer* conv171 = convBnSilu(network, weightMap, *conv170->getOutput(0), 64, 3, 1, 1, "model.171");
|
|
IElementWiseLayer* conv172 = convBnSilu(network, weightMap, *conv171->getOutput(0), 64, 3, 1, 1, "model.172");
|
|
IElementWiseLayer* conv173 = convBnSilu(network, weightMap, *conv172->getOutput(0), 64, 3, 1, 1, "model.173");
|
|
IElementWiseLayer* conv174 = convBnSilu(network, weightMap, *conv173->getOutput(0), 64, 3, 1, 1, "model.174");
|
|
|
|
|
|
ITensor* input_tensor_175[] = { conv174->getOutput(0), conv173->getOutput(0),conv172->getOutput(0), conv171->getOutput(0),
|
|
conv170->getOutput(0), conv169->getOutput(0), conv168->getOutput(0), conv167->getOutput(0) };
|
|
IConcatenationLayer* concat175 = network->addConcatenation(input_tensor_175, 8);
|
|
IElementWiseLayer* conv176 = convBnSilu(network, weightMap, *concat175->getOutput(0), 160, 1, 1, 0, "model.176");
|
|
IElementWiseLayer* conv177 = convBnSilu(network, weightMap, *concat166->getOutput(0), 128, 1, 1, 0, "model.177");
|
|
IElementWiseLayer* conv178 = convBnSilu(network, weightMap, *concat166->getOutput(0), 128, 1, 1, 0, "model.178");
|
|
|
|
IElementWiseLayer* conv179 = convBnSilu(network, weightMap, *conv178->getOutput(0), 64, 3, 1, 1, "model.179");
|
|
IElementWiseLayer* conv180 = convBnSilu(network, weightMap, *conv179->getOutput(0), 64, 3, 1, 1, "model.180");
|
|
IElementWiseLayer* conv181 = convBnSilu(network, weightMap, *conv180->getOutput(0), 64, 3, 1, 1, "model.181");
|
|
IElementWiseLayer* conv182 = convBnSilu(network, weightMap, *conv181->getOutput(0), 64, 3, 1, 1, "model.182");
|
|
IElementWiseLayer* conv183 = convBnSilu(network, weightMap, *conv182->getOutput(0), 64, 3, 1, 1, "model.183");
|
|
IElementWiseLayer* conv184 = convBnSilu(network, weightMap, *conv183->getOutput(0), 64, 3, 1, 1, "model.184");
|
|
ITensor* input_tensor_185[] = { conv184->getOutput(0), conv183->getOutput(0),conv182->getOutput(0), conv181->getOutput(0),
|
|
conv180->getOutput(0), conv179->getOutput(0), conv178->getOutput(0), conv177->getOutput(0) };
|
|
IConcatenationLayer* concat185 = network->addConcatenation(input_tensor_185, 8);
|
|
IElementWiseLayer* conv186 = convBnSilu(network, weightMap, *concat185->getOutput(0), 160, 1, 1, 0, "model.186");
|
|
auto conv187 = network->addElementWise(*conv186->getOutput(0), *conv176->getOutput(0), ElementWiseOperation::kSUM);
|
|
|
|
auto conv188 = DownC(network, weightMap, *conv187->getOutput(0), 160, 320, "model.188");
|
|
|
|
|
|
ITensor* input_tensor_189[] = { conv188->getOutput(0), conv162->getOutput(0) };
|
|
IConcatenationLayer* concat189 = network->addConcatenation(input_tensor_189, 2);
|
|
|
|
IElementWiseLayer* conv190 = convBnSilu(network, weightMap, *concat189->getOutput(0), 256, 1, 1, 0, "model.190");
|
|
IElementWiseLayer* conv191 = convBnSilu(network, weightMap, *concat189->getOutput(0), 256, 1, 1, 0, "model.191");
|
|
|
|
IElementWiseLayer* conv192 = convBnSilu(network, weightMap, *conv191->getOutput(0), 128, 3, 1, 1, "model.192");
|
|
IElementWiseLayer* conv193 = convBnSilu(network, weightMap, *conv192->getOutput(0), 128, 3, 1, 1, "model.193");
|
|
IElementWiseLayer* conv194 = convBnSilu(network, weightMap, *conv193->getOutput(0), 128, 3, 1, 1, "model.194");
|
|
IElementWiseLayer* conv195 = convBnSilu(network, weightMap, *conv194->getOutput(0), 128, 3, 1, 1, "model.195");
|
|
IElementWiseLayer* conv196 = convBnSilu(network, weightMap, *conv195->getOutput(0), 128, 3, 1, 1, "model.196");
|
|
IElementWiseLayer* conv197 = convBnSilu(network, weightMap, *conv196->getOutput(0), 128, 3, 1, 1, "model.197");
|
|
|
|
|
|
ITensor* input_tensor_198[] = { conv197->getOutput(0), conv196->getOutput(0),conv195->getOutput(0), conv194->getOutput(0),
|
|
conv193->getOutput(0), conv192->getOutput(0), conv191->getOutput(0), conv190->getOutput(0) };
|
|
IConcatenationLayer* concat198 = network->addConcatenation(input_tensor_198, 8);
|
|
IElementWiseLayer* conv199 = convBnSilu(network, weightMap, *concat198->getOutput(0), 320, 1, 1, 0, "model.199");
|
|
|
|
IElementWiseLayer* conv200 = convBnSilu(network, weightMap, *concat189->getOutput(0), 256, 1, 1, 0, "model.200");
|
|
IElementWiseLayer* conv201 = convBnSilu(network, weightMap, *concat189->getOutput(0), 256, 1, 1, 0, "model.201");
|
|
|
|
IElementWiseLayer* conv202 = convBnSilu(network, weightMap, *conv201->getOutput(0), 128, 3, 1, 1, "model.202");
|
|
IElementWiseLayer* conv203 = convBnSilu(network, weightMap, *conv202->getOutput(0), 128, 3, 1, 1, "model.203");
|
|
IElementWiseLayer* conv204 = convBnSilu(network, weightMap, *conv203->getOutput(0), 128, 3, 1, 1, "model.204");
|
|
IElementWiseLayer* conv205 = convBnSilu(network, weightMap, *conv204->getOutput(0), 128, 3, 1, 1, "model.205");
|
|
IElementWiseLayer* conv206 = convBnSilu(network, weightMap, *conv205->getOutput(0), 128, 3, 1, 1, "model.206");
|
|
IElementWiseLayer* conv207 = convBnSilu(network, weightMap, *conv206->getOutput(0), 128, 3, 1, 1, "model.207");
|
|
ITensor* input_tensor_208[] = { conv207->getOutput(0), conv206->getOutput(0),conv205->getOutput(0), conv204->getOutput(0),
|
|
conv203->getOutput(0), conv202->getOutput(0), conv201->getOutput(0), conv200->getOutput(0) };
|
|
IConcatenationLayer* concat208 = network->addConcatenation(input_tensor_208, 8);
|
|
IElementWiseLayer* conv209 = convBnSilu(network, weightMap, *concat208->getOutput(0), 320, 1, 1, 0, "model.209");
|
|
auto conv210 = network->addElementWise(*conv209->getOutput(0), *conv199->getOutput(0), ElementWiseOperation::kSUM);
|
|
|
|
|
|
auto conv211 = DownC(network, weightMap, *conv210->getOutput(0), 320, 480, "model.211");
|
|
ITensor* input_tensor_212[] = { conv211->getOutput(0), conv137->getOutput(0) };
|
|
IConcatenationLayer* concat212 = network->addConcatenation(input_tensor_212, 2);
|
|
|
|
IElementWiseLayer* conv213 = convBnSilu(network, weightMap, *concat212->getOutput(0), 384, 1, 1, 0, "model.213");
|
|
IElementWiseLayer* conv214 = convBnSilu(network, weightMap, *concat212->getOutput(0), 384, 1, 1, 0, "model.214");
|
|
|
|
IElementWiseLayer* conv215 = convBnSilu(network, weightMap, *conv214->getOutput(0), 192, 3, 1, 1, "model.215");
|
|
IElementWiseLayer* conv216 = convBnSilu(network, weightMap, *conv215->getOutput(0), 192, 3, 1, 1, "model.216");
|
|
IElementWiseLayer* conv217 = convBnSilu(network, weightMap, *conv216->getOutput(0), 192, 3, 1, 1, "model.217");
|
|
IElementWiseLayer* conv218 = convBnSilu(network, weightMap, *conv217->getOutput(0), 192, 3, 1, 1, "model.218");
|
|
IElementWiseLayer* conv219 = convBnSilu(network, weightMap, *conv218->getOutput(0), 192, 3, 1, 1, "model.219");
|
|
IElementWiseLayer* conv220 = convBnSilu(network, weightMap, *conv219->getOutput(0), 192, 3, 1, 1, "model.220");
|
|
|
|
ITensor* input_tensor_221[] = { conv220->getOutput(0), conv219->getOutput(0),conv218->getOutput(0), conv217->getOutput(0),
|
|
conv216->getOutput(0), conv215->getOutput(0), conv214->getOutput(0), conv213->getOutput(0) };
|
|
IConcatenationLayer* concat221 = network->addConcatenation(input_tensor_221, 8);
|
|
IElementWiseLayer* conv222 = convBnSilu(network, weightMap, *concat221->getOutput(0), 480, 1, 1, 0, "model.222");
|
|
|
|
IElementWiseLayer* conv223 = convBnSilu(network, weightMap, *concat212->getOutput(0), 384, 1, 1, 0, "model.223");
|
|
IElementWiseLayer* conv224 = convBnSilu(network, weightMap, *concat212->getOutput(0), 384, 1, 1, 0, "model.224");
|
|
|
|
IElementWiseLayer* conv225 = convBnSilu(network, weightMap, *conv224->getOutput(0), 192, 3, 1, 1, "model.225");
|
|
IElementWiseLayer* conv226 = convBnSilu(network, weightMap, *conv225->getOutput(0), 192, 3, 1, 1, "model.226");
|
|
IElementWiseLayer* conv227 = convBnSilu(network, weightMap, *conv226->getOutput(0), 192, 3, 1, 1, "model.227");
|
|
IElementWiseLayer* conv228 = convBnSilu(network, weightMap, *conv227->getOutput(0), 192, 3, 1, 1, "model.228");
|
|
IElementWiseLayer* conv229 = convBnSilu(network, weightMap, *conv228->getOutput(0), 192, 3, 1, 1, "model.229");
|
|
IElementWiseLayer* conv230 = convBnSilu(network, weightMap, *conv229->getOutput(0), 192, 3, 1, 1, "model.230");
|
|
ITensor* input_tensor_231[] = { conv230->getOutput(0), conv229->getOutput(0),conv228->getOutput(0), conv227->getOutput(0),
|
|
conv226->getOutput(0), conv225->getOutput(0), conv224->getOutput(0), conv223->getOutput(0) };
|
|
IConcatenationLayer* concat231 = network->addConcatenation(input_tensor_231, 8);
|
|
IElementWiseLayer* conv232 = convBnSilu(network, weightMap, *concat231->getOutput(0), 480, 1, 1, 0, "model.232");
|
|
|
|
auto conv233 = network->addElementWise(*conv232->getOutput(0), *conv222->getOutput(0), ElementWiseOperation::kSUM);
|
|
|
|
|
|
auto conv234 = DownC(network, weightMap, *conv233->getOutput(0), 480, 640, "model.234");
|
|
ITensor* input_tensor_235[] = { conv234->getOutput(0), conv112->getOutput(0) };
|
|
IConcatenationLayer* concat235 = network->addConcatenation(input_tensor_235, 2);
|
|
|
|
|
|
IElementWiseLayer* conv236 = convBnSilu(network, weightMap, *concat235->getOutput(0), 512, 1, 1, 0, "model.236");
|
|
IElementWiseLayer* conv237 = convBnSilu(network, weightMap, *concat235->getOutput(0), 512, 1, 1, 0, "model.237");
|
|
|
|
IElementWiseLayer* conv238 = convBnSilu(network, weightMap, *conv237->getOutput(0), 256, 3, 1, 1, "model.238");
|
|
IElementWiseLayer* conv239 = convBnSilu(network, weightMap, *conv238->getOutput(0), 256, 3, 1, 1, "model.239");
|
|
IElementWiseLayer* conv240 = convBnSilu(network, weightMap, *conv239->getOutput(0), 256, 3, 1, 1, "model.240");
|
|
IElementWiseLayer* conv241 = convBnSilu(network, weightMap, *conv240->getOutput(0), 256, 3, 1, 1, "model.241");
|
|
IElementWiseLayer* conv242 = convBnSilu(network, weightMap, *conv241->getOutput(0), 256, 3, 1, 1, "model.242");
|
|
IElementWiseLayer* conv243 = convBnSilu(network, weightMap, *conv242->getOutput(0), 256, 3, 1, 1, "model.243");
|
|
|
|
ITensor* input_tensor_244[] = { conv243->getOutput(0), conv242->getOutput(0),conv241->getOutput(0), conv240->getOutput(0),
|
|
conv239->getOutput(0), conv238->getOutput(0), conv237->getOutput(0), conv236->getOutput(0) };
|
|
IConcatenationLayer* concat244 = network->addConcatenation(input_tensor_244, 8);
|
|
IElementWiseLayer* conv245 = convBnSilu(network, weightMap, *concat244->getOutput(0), 640, 1, 1, 0, "model.245");
|
|
|
|
IElementWiseLayer* conv246 = convBnSilu(network, weightMap, *concat235->getOutput(0), 512, 1, 1, 0, "model.246");
|
|
IElementWiseLayer* conv247 = convBnSilu(network, weightMap, *concat235->getOutput(0), 512, 1, 1, 0, "model.247");
|
|
|
|
IElementWiseLayer* conv248 = convBnSilu(network, weightMap, *conv247->getOutput(0), 256, 3, 1, 1, "model.248");
|
|
IElementWiseLayer* conv249 = convBnSilu(network, weightMap, *conv248->getOutput(0), 256, 3, 1, 1, "model.249");
|
|
IElementWiseLayer* conv250 = convBnSilu(network, weightMap, *conv249->getOutput(0), 256, 3, 1, 1, "model.250");
|
|
IElementWiseLayer* conv251 = convBnSilu(network, weightMap, *conv250->getOutput(0), 256, 3, 1, 1, "model.251");
|
|
IElementWiseLayer* conv252 = convBnSilu(network, weightMap, *conv251->getOutput(0), 256, 3, 1, 1, "model.252");
|
|
IElementWiseLayer* conv253 = convBnSilu(network, weightMap, *conv252->getOutput(0), 256, 3, 1, 1, "model.253");
|
|
|
|
ITensor* input_tensor_254[] = { conv253->getOutput(0), conv252->getOutput(0),conv251->getOutput(0), conv250->getOutput(0),
|
|
conv249->getOutput(0), conv248->getOutput(0), conv247->getOutput(0), conv246->getOutput(0) };
|
|
IConcatenationLayer* concat254 = network->addConcatenation(input_tensor_254, 8);
|
|
|
|
IElementWiseLayer* conv255= convBnSilu(network, weightMap, *concat254->getOutput(0), 640, 1, 1, 0, "model.255");
|
|
auto conv256 = network->addElementWise(*conv255->getOutput(0), *conv245->getOutput(0), ElementWiseOperation::kSUM);
|
|
|
|
IElementWiseLayer* conv257 = convBnSilu(network, weightMap, *conv187->getOutput(0), 320, 3, 1, 1, "model.257");
|
|
IElementWiseLayer* conv258 = convBnSilu(network, weightMap, *conv210->getOutput(0), 640, 3, 1, 1, "model.258");
|
|
IElementWiseLayer* conv259 = convBnSilu(network, weightMap, *conv233->getOutput(0), 960, 3, 1, 1, "model.259");
|
|
IElementWiseLayer* conv260 = convBnSilu(network, weightMap, *conv256->getOutput(0), 1280, 3, 1, 1, "model.260");
|
|
|
|
|
|
|
|
// out
|
|
IConvolutionLayer* cv105_0 = network->addConvolutionNd(*conv257->getOutput(0), 3 * (Yolo::CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.261.m.0.weight"], weightMap["model.261.m.0.bias"]);
|
|
assert(cv105_0);
|
|
cv105_0->setName("cv105.0");
|
|
IConvolutionLayer* cv105_1 = network->addConvolutionNd(*conv258->getOutput(0), 3 * (Yolo::CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.261.m.1.weight"], weightMap["model.261.m.1.bias"]);
|
|
assert(cv105_1);
|
|
cv105_1->setName("cv105.1");
|
|
IConvolutionLayer* cv105_2 = network->addConvolutionNd(*conv259->getOutput(0), 3 * (Yolo::CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.261.m.2.weight"], weightMap["model.261.m.2.bias"]);
|
|
assert(cv105_2);
|
|
cv105_2->setName("cv105.2");
|
|
IConvolutionLayer* cv105_3 = network->addConvolutionNd(*conv260->getOutput(0), 3 * (Yolo::CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.261.m.3.weight"], weightMap["model.261.m.3.bias"]);
|
|
assert(cv105_3);
|
|
cv105_3->setName("cv105.3");
|
|
|
|
|
|
|
|
/*------------detect-----------*/
|
|
auto yolo = addYoLoLayer(network, weightMap, "model.261", std::vector<IConvolutionLayer*>{cv105_0, cv105_1, cv105_2, cv105_3});
|
|
yolo->getOutput(0)->setName(OUTPUT_BLOB_NAME);
|
|
network->markOutput(*yolo->getOutput(0));
|
|
// Build engine
|
|
builder->setMaxBatchSize(maxBatchSize);
|
|
config->setMaxWorkspaceSize(16 * (1 << 20)); // 16MB
|
|
#if defined(USE_FP16)
|
|
config->setFlag(BuilderFlag::kFP16);
|
|
#endif
|
|
|
|
std::cout << "Building engine, please wait for a while..." << std::endl;
|
|
ICudaEngine* engine = builder->buildEngineWithConfig(*network, *config);
|
|
std::cout << "Build engine successfully!" << std::endl;
|
|
|
|
network->destroy();
|
|
|
|
// Release host memory
|
|
for (auto& mem : weightMap) {
|
|
free((void*)(mem.second.values));
|
|
}
|
|
|
|
return engine;
|
|
}
|
|
|
|
ICudaEngine* build_engine_yolov7d6(unsigned int maxBatchSize, IBuilder* builder, IBuilderConfig* config, DataType dt, const std::string& wts_path) {
|
|
std::map<std::string, Weights> weightMap = loadWeights(wts_path);
|
|
|
|
INetworkDefinition* network = builder->createNetworkV2(0U);
|
|
ITensor* data = network->addInput(INPUT_BLOB_NAME, dt, Dims3{ 3, INPUT_H, INPUT_W });
|
|
assert(data);
|
|
|
|
/*----------------------------------yolov7d6 backbone-----------------------------------------*/
|
|
auto* conv0 = ReOrg(network, weightMap, *data, 3);
|
|
|
|
|
|
IElementWiseLayer* conv1 = convBnSilu(network, weightMap, *conv0->getOutput(0), 96, 3, 1, 1, "model.1");
|
|
auto conv2 = DownC(network, weightMap, *conv1->getOutput(0), 96, 192, "model.2");
|
|
|
|
IElementWiseLayer* conv3 = convBnSilu(network, weightMap, *conv2->getOutput(0), 64, 1, 1, 0, "model.3");
|
|
IElementWiseLayer* conv4 = convBnSilu(network, weightMap, *conv2->getOutput(0), 64, 1, 1, 0, "model.4");
|
|
|
|
IElementWiseLayer* conv5 = convBnSilu(network, weightMap, *conv4->getOutput(0), 64, 3, 1, 1, "model.5");
|
|
IElementWiseLayer* conv6 = convBnSilu(network, weightMap, *conv5->getOutput(0), 64, 3, 1, 1, "model.6");
|
|
IElementWiseLayer* conv7 = convBnSilu(network, weightMap, *conv6->getOutput(0), 64, 3, 1, 1, "model.7");
|
|
IElementWiseLayer* conv8 = convBnSilu(network, weightMap, *conv7->getOutput(0), 64, 3, 1, 1, "model.8");
|
|
IElementWiseLayer* conv9 = convBnSilu(network, weightMap, *conv8->getOutput(0), 64, 3, 1, 1, "model.9");
|
|
IElementWiseLayer* conv10 = convBnSilu(network, weightMap, *conv9->getOutput(0), 64, 3, 1, 1, "model.10");
|
|
IElementWiseLayer* conv11 = convBnSilu(network, weightMap, *conv10->getOutput(0), 64, 3, 1, 1, "model.11");
|
|
IElementWiseLayer* conv12 = convBnSilu(network, weightMap, *conv11->getOutput(0), 64, 3, 1, 1, "model.12");
|
|
|
|
ITensor* input_tensor_13[] = { conv12->getOutput(0), conv10->getOutput(0),conv8->getOutput(0), conv6->getOutput(0),
|
|
conv4->getOutput(0),conv3->getOutput(0) };
|
|
IConcatenationLayer* concat13 = network->addConcatenation(input_tensor_13, 6);
|
|
|
|
IElementWiseLayer* conv14 = convBnSilu(network, weightMap, *concat13->getOutput(0), 192, 1, 1, 0, "model.14");
|
|
|
|
|
|
auto conv15 = DownC(network, weightMap, *conv14->getOutput(0), 192, 384, "model.15");
|
|
IElementWiseLayer* conv16 = convBnSilu(network, weightMap, *conv15->getOutput(0), 128, 1, 1, 0, "model.16");
|
|
IElementWiseLayer* conv17 = convBnSilu(network, weightMap, *conv15->getOutput(0), 128, 1, 1, 0, "model.17");
|
|
|
|
IElementWiseLayer* conv18 = convBnSilu(network, weightMap, *conv17->getOutput(0), 128, 3, 1, 1, "model.18");
|
|
IElementWiseLayer* conv19 = convBnSilu(network, weightMap, *conv18->getOutput(0), 128, 3, 1, 1, "model.19");
|
|
IElementWiseLayer* conv20 = convBnSilu(network, weightMap, *conv19->getOutput(0), 128, 3, 1, 1, "model.20");
|
|
IElementWiseLayer* conv21 = convBnSilu(network, weightMap, *conv20->getOutput(0), 128, 3, 1, 1, "model.21");
|
|
IElementWiseLayer* conv22 = convBnSilu(network, weightMap, *conv21->getOutput(0), 128, 3, 1, 1, "model.22");
|
|
IElementWiseLayer* conv23 = convBnSilu(network, weightMap, *conv22->getOutput(0), 128, 3, 1, 1, "model.23");
|
|
IElementWiseLayer* conv24 = convBnSilu(network, weightMap, *conv23->getOutput(0), 128, 3, 1, 1, "model.24");
|
|
IElementWiseLayer* conv25 = convBnSilu(network, weightMap, *conv24->getOutput(0), 128, 3, 1, 1, "model.25");
|
|
ITensor* input_tensor_26[] = { conv25->getOutput(0), conv23->getOutput(0),conv21->getOutput(0), conv19->getOutput(0),
|
|
conv17->getOutput(0),conv16->getOutput(0) };
|
|
IConcatenationLayer* concat26 = network->addConcatenation(input_tensor_26, 6);
|
|
|
|
IElementWiseLayer* conv27 = convBnSilu(network, weightMap, *concat26->getOutput(0), 384, 1, 1, 0, "model.27");
|
|
|
|
|
|
auto conv28 = DownC(network, weightMap, *conv27->getOutput(0), 384, 768, "model.28");
|
|
IElementWiseLayer* conv29 = convBnSilu(network, weightMap, *conv28->getOutput(0), 256, 1, 1, 0, "model.29");
|
|
IElementWiseLayer* conv30 = convBnSilu(network, weightMap, *conv28->getOutput(0), 256, 1, 1, 0, "model.30");
|
|
|
|
IElementWiseLayer* conv31 = convBnSilu(network, weightMap, *conv30->getOutput(0), 256, 3, 1, 1, "model.31");
|
|
IElementWiseLayer* conv32 = convBnSilu(network, weightMap, *conv31->getOutput(0), 256, 3, 1, 1, "model.32");
|
|
IElementWiseLayer* conv33 = convBnSilu(network, weightMap, *conv32->getOutput(0), 256, 3, 1, 1, "model.33");
|
|
IElementWiseLayer* conv34 = convBnSilu(network, weightMap, *conv33->getOutput(0), 256, 3, 1, 1, "model.34");
|
|
IElementWiseLayer* conv35 = convBnSilu(network, weightMap, *conv34->getOutput(0), 256, 3, 1, 1, "model.35");
|
|
IElementWiseLayer* conv36 = convBnSilu(network, weightMap, *conv35->getOutput(0), 256, 3, 1, 1, "model.36");
|
|
IElementWiseLayer* conv37 = convBnSilu(network, weightMap, *conv36->getOutput(0), 256, 3, 1, 1, "model.37");
|
|
IElementWiseLayer* conv38 = convBnSilu(network, weightMap, *conv37->getOutput(0), 256, 3, 1, 1, "model.38");
|
|
ITensor* input_tensor_39[] = { conv38->getOutput(0), conv36->getOutput(0),conv34->getOutput(0), conv32->getOutput(0),
|
|
conv30->getOutput(0), conv29 ->getOutput(0)};
|
|
IConcatenationLayer* concat39 = network->addConcatenation(input_tensor_39, 6);
|
|
|
|
IElementWiseLayer* conv40 = convBnSilu(network, weightMap, *concat39->getOutput(0), 768, 1, 1, 0, "model.40");
|
|
auto conv41 = DownC(network, weightMap, *conv40->getOutput(0), 768, 1152, "model.41");
|
|
IElementWiseLayer* conv42 = convBnSilu(network, weightMap, *conv41->getOutput(0), 384, 1, 1, 0, "model.42");
|
|
IElementWiseLayer* conv43 = convBnSilu(network, weightMap, *conv41->getOutput(0), 384, 1, 1, 0, "model.43");
|
|
|
|
IElementWiseLayer* conv44 = convBnSilu(network, weightMap, *conv43->getOutput(0), 384, 3, 1, 1, "model.44");
|
|
IElementWiseLayer* conv45 = convBnSilu(network, weightMap, *conv44->getOutput(0), 384, 3, 1, 1, "model.45");
|
|
IElementWiseLayer* conv46 = convBnSilu(network, weightMap, *conv45->getOutput(0), 384, 3, 1, 1, "model.46");
|
|
IElementWiseLayer* conv47 = convBnSilu(network, weightMap, *conv46->getOutput(0), 384, 3, 1, 1, "model.47");
|
|
IElementWiseLayer* conv48 = convBnSilu(network, weightMap, *conv47->getOutput(0), 384, 3, 1, 1, "model.48");
|
|
IElementWiseLayer* conv49 = convBnSilu(network, weightMap, *conv48->getOutput(0), 384, 3, 1, 1, "model.49");
|
|
IElementWiseLayer* conv50 = convBnSilu(network, weightMap, *conv49->getOutput(0), 384, 3, 1, 1, "model.50");
|
|
IElementWiseLayer* conv51 = convBnSilu(network, weightMap, *conv50->getOutput(0), 384, 3, 1, 1, "model.51");
|
|
|
|
ITensor* input_tensor_52[] = { conv51->getOutput(0), conv49->getOutput(0),conv47->getOutput(0), conv45->getOutput(0),
|
|
conv43->getOutput(0),conv42->getOutput(0) };
|
|
IConcatenationLayer* concat52 = network->addConcatenation(input_tensor_52, 6);
|
|
IElementWiseLayer* conv53 = convBnSilu(network, weightMap, *concat52->getOutput(0), 1152, 1, 1, 0, "model.53");
|
|
|
|
auto conv54 = DownC(network, weightMap, *conv53->getOutput(0), 1152, 1536, "model.54");//=====
|
|
IElementWiseLayer* conv55 = convBnSilu(network, weightMap, *conv54->getOutput(0), 512, 1, 1, 0, "model.55");
|
|
IElementWiseLayer* conv56 = convBnSilu(network, weightMap, *conv54->getOutput(0), 512, 1, 1, 0, "model.56");
|
|
|
|
IElementWiseLayer* conv57 = convBnSilu(network, weightMap, *conv56->getOutput(0), 512, 3, 1, 1, "model.57");
|
|
IElementWiseLayer* conv58 = convBnSilu(network, weightMap, *conv57->getOutput(0), 512, 3, 1, 1, "model.58");
|
|
IElementWiseLayer* conv59 = convBnSilu(network, weightMap, *conv58->getOutput(0), 512, 3, 1, 1, "model.59");
|
|
IElementWiseLayer* conv60 = convBnSilu(network, weightMap, *conv59->getOutput(0), 512, 3, 1, 1, "model.60");
|
|
IElementWiseLayer* conv61 = convBnSilu(network, weightMap, *conv60->getOutput(0), 512, 3, 1, 1, "model.61");
|
|
IElementWiseLayer* conv62 = convBnSilu(network, weightMap, *conv61->getOutput(0), 512, 3, 1, 1, "model.62");
|
|
IElementWiseLayer* conv63 = convBnSilu(network, weightMap, *conv62->getOutput(0), 512, 3, 1, 1, "model.63");
|
|
IElementWiseLayer* conv64 = convBnSilu(network, weightMap, *conv63->getOutput(0), 512, 3, 1, 1, "model.64");
|
|
ITensor* input_tensor_65[] = { conv64->getOutput(0), conv62->getOutput(0),conv60->getOutput(0), conv58->getOutput(0),
|
|
conv56->getOutput(0),conv55->getOutput(0) };
|
|
IConcatenationLayer* concat65 = network->addConcatenation(input_tensor_65, 6);
|
|
IElementWiseLayer* conv66 = convBnSilu(network, weightMap, *concat65->getOutput(0), 1536, 1, 1, 0, "model.66");
|
|
|
|
//------------------------yolov7e6 head-------------------------------
|
|
auto conv67 = SPPCSPC(network, weightMap, *conv66->getOutput(0), 768, "model.67");
|
|
IElementWiseLayer* conv68 = convBnSilu(network, weightMap, *conv67->getOutput(0), 576, 1, 1, 0, "model.68");
|
|
|
|
|
|
float scale[] = { 1.0, 2.0, 2.0 };
|
|
IResizeLayer* re69 = network->addResize(*conv68->getOutput(0));
|
|
re69->setResizeMode(ResizeMode::kNEAREST);
|
|
re69->setScales(scale, 3);
|
|
|
|
IElementWiseLayer* conv70 = convBnSilu(network, weightMap, *conv53->getOutput(0), 576, 1, 1, 0, "model.70");
|
|
ITensor* input_tensor_71[] = { conv70->getOutput(0), re69->getOutput(0) };
|
|
IConcatenationLayer* concat71 = network->addConcatenation(input_tensor_71, 2);
|
|
IElementWiseLayer* conv72 = convBnSilu(network, weightMap, *concat71->getOutput(0), 384, 1, 1, 0, "model.72");
|
|
IElementWiseLayer* conv73 = convBnSilu(network, weightMap, *concat71->getOutput(0), 384, 1, 1, 0, "model.73");
|
|
|
|
IElementWiseLayer* conv74 = convBnSilu(network, weightMap, *conv73->getOutput(0), 192, 3, 1, 1, "model.74");
|
|
IElementWiseLayer* conv75 = convBnSilu(network, weightMap, *conv74->getOutput(0), 192, 3, 1, 1, "model.75");
|
|
IElementWiseLayer* conv76 = convBnSilu(network, weightMap, *conv75->getOutput(0), 192, 3, 1, 1, "model.76");
|
|
IElementWiseLayer* conv77 = convBnSilu(network, weightMap, *conv76->getOutput(0), 192, 3, 1, 1, "model.77");
|
|
IElementWiseLayer* conv78 = convBnSilu(network, weightMap, *conv77->getOutput(0), 192, 3, 1, 1, "model.78");
|
|
IElementWiseLayer* conv79 = convBnSilu(network, weightMap, *conv78->getOutput(0), 192, 3, 1, 1, "model.79");
|
|
IElementWiseLayer* conv80 = convBnSilu(network, weightMap, *conv79->getOutput(0), 192, 3, 1, 1, "model.80");
|
|
IElementWiseLayer* conv81 = convBnSilu(network, weightMap, *conv80->getOutput(0), 192, 3, 1, 1, "model.81");
|
|
|
|
ITensor* input_tensor_82[] = { conv81->getOutput(0), conv80->getOutput(0),conv79->getOutput(0), conv78->getOutput(0),
|
|
conv77->getOutput(0), conv76->getOutput(0), conv75->getOutput(0), conv74->getOutput(0), conv73->getOutput(0),
|
|
conv72->getOutput(0) };
|
|
IConcatenationLayer* concat82 = network->addConcatenation(input_tensor_82, 10);
|
|
IElementWiseLayer* conv83 = convBnSilu(network, weightMap, *concat82->getOutput(0), 576, 1, 1, 0, "model.83");
|
|
|
|
IElementWiseLayer* conv84 = convBnSilu(network, weightMap, *conv83->getOutput(0), 384, 1, 1, 0, "model.84");
|
|
IResizeLayer* re85 = network->addResize(*conv84->getOutput(0));
|
|
re85->setResizeMode(ResizeMode::kNEAREST);
|
|
re85->setScales(scale, 3);
|
|
IElementWiseLayer* conv86 = convBnSilu(network, weightMap, *conv40->getOutput(0), 384, 1, 1, 0, "model.86");
|
|
ITensor* input_tensor_87[] = { conv86->getOutput(0), re85->getOutput(0) };
|
|
IConcatenationLayer* concat87 = network->addConcatenation(input_tensor_87, 2);
|
|
|
|
IElementWiseLayer* conv88 = convBnSilu(network, weightMap, *concat87->getOutput(0), 256, 1, 1, 0, "model.88");
|
|
IElementWiseLayer* conv89 = convBnSilu(network, weightMap, *concat87->getOutput(0), 256, 1, 1, 0, "model.89");
|
|
|
|
IElementWiseLayer* conv90 = convBnSilu(network, weightMap, *conv89->getOutput(0), 128, 3, 1, 1, "model.90");
|
|
IElementWiseLayer* conv91 = convBnSilu(network, weightMap, *conv90->getOutput(0), 128, 3, 1, 1, "model.91");
|
|
IElementWiseLayer* conv92 = convBnSilu(network, weightMap, *conv91->getOutput(0), 128, 3, 1, 1, "model.92");
|
|
IElementWiseLayer* conv93 = convBnSilu(network, weightMap, *conv92->getOutput(0), 128, 3, 1, 1, "model.93");
|
|
IElementWiseLayer* conv94 = convBnSilu(network, weightMap, *conv93->getOutput(0), 128, 3, 1, 1, "model.94");
|
|
IElementWiseLayer* conv95 = convBnSilu(network, weightMap, *conv94->getOutput(0), 128, 3, 1, 1, "model.95");
|
|
IElementWiseLayer* conv96 = convBnSilu(network, weightMap, *conv95->getOutput(0), 128, 3, 1, 1, "model.96");
|
|
IElementWiseLayer* conv97 = convBnSilu(network, weightMap, *conv96->getOutput(0), 128, 3, 1, 1, "model.97");
|
|
|
|
ITensor* input_tensor_98[] = { conv97->getOutput(0), conv96->getOutput(0),conv95->getOutput(0), conv94->getOutput(0),
|
|
conv93->getOutput(0), conv92->getOutput(0), conv91->getOutput(0), conv90->getOutput(0),conv89->getOutput(0),
|
|
conv88->getOutput(0) };
|
|
IConcatenationLayer* concat98 = network->addConcatenation(input_tensor_98, 10);
|
|
|
|
IElementWiseLayer* conv99 = convBnSilu(network, weightMap, *concat98->getOutput(0), 384, 1, 1, 0, "model.99");
|
|
|
|
IElementWiseLayer* conv100 = convBnSilu(network, weightMap, *conv99->getOutput(0), 192, 1, 1, 0, "model.100");
|
|
IResizeLayer* re101 = network->addResize(*conv100->getOutput(0));
|
|
re101->setResizeMode(ResizeMode::kNEAREST);
|
|
re101->setScales(scale, 3);
|
|
IElementWiseLayer* conv102 = convBnSilu(network, weightMap, *conv27->getOutput(0), 192, 1, 1, 0, "model.102");
|
|
ITensor* input_tensor_103[] = { conv102->getOutput(0), re101->getOutput(0) };
|
|
IConcatenationLayer* concat103 = network->addConcatenation(input_tensor_103, 2);
|
|
|
|
IElementWiseLayer* conv104 = convBnSilu(network, weightMap, *concat103->getOutput(0), 128, 1, 1, 0, "model.104");
|
|
IElementWiseLayer* conv105 = convBnSilu(network, weightMap, *concat103->getOutput(0), 128, 1, 1, 0, "model.105");
|
|
IElementWiseLayer* conv106 = convBnSilu(network, weightMap, *conv105->getOutput(0), 64, 3, 1, 1, "model.106");
|
|
IElementWiseLayer* conv107 = convBnSilu(network, weightMap, *conv106->getOutput(0), 64, 3, 1, 1, "model.107");
|
|
IElementWiseLayer* conv108 = convBnSilu(network, weightMap, *conv107->getOutput(0), 64, 3, 1, 1, "model.108");
|
|
IElementWiseLayer* conv109 = convBnSilu(network, weightMap, *conv108->getOutput(0), 64, 3, 1, 1, "model.109");
|
|
IElementWiseLayer* conv110 = convBnSilu(network, weightMap, *conv109->getOutput(0), 64, 3, 1, 1, "model.110");
|
|
IElementWiseLayer* conv111 = convBnSilu(network, weightMap, *conv110->getOutput(0), 64, 3, 1, 1, "model.111");
|
|
IElementWiseLayer* conv112 = convBnSilu(network, weightMap, *conv111->getOutput(0), 64, 3, 1, 1, "model.112");
|
|
IElementWiseLayer* conv113 = convBnSilu(network, weightMap, *conv112->getOutput(0), 64, 3, 1, 1, "model.113");
|
|
|
|
ITensor* input_tensor_114[] = { conv113->getOutput(0), conv112->getOutput(0),conv111->getOutput(0), conv110->getOutput(0),
|
|
conv109->getOutput(0), conv108->getOutput(0), conv107->getOutput(0), conv106->getOutput(0), conv105->getOutput(0),
|
|
conv104->getOutput(0) };
|
|
IConcatenationLayer* concat114 = network->addConcatenation(input_tensor_114, 10);
|
|
|
|
IElementWiseLayer* conv115 = convBnSilu(network, weightMap, *concat114->getOutput(0), 192, 1, 1, 0, "model.115");
|
|
|
|
auto conv116 = DownC(network, weightMap, *conv115->getOutput(0), 192, 384, "model.116");
|
|
ITensor* input_tensor_117[] = { conv116->getOutput(0), conv99->getOutput(0) };
|
|
IConcatenationLayer* concat117 = network->addConcatenation(input_tensor_117, 2);
|
|
|
|
IElementWiseLayer* conv118 = convBnSilu(network, weightMap, *concat117->getOutput(0), 256, 1, 1, 0, "model.118");
|
|
IElementWiseLayer* conv119 = convBnSilu(network, weightMap, *concat117->getOutput(0), 256, 1, 1, 0, "model.119");
|
|
|
|
IElementWiseLayer* conv120 = convBnSilu(network, weightMap, *conv119->getOutput(0), 128, 3, 1, 1, "model.120");
|
|
IElementWiseLayer* conv121 = convBnSilu(network, weightMap, *conv120->getOutput(0), 128, 3, 1, 1, "model.121");
|
|
IElementWiseLayer* conv122 = convBnSilu(network, weightMap, *conv121->getOutput(0), 128, 3, 1, 1, "model.122");
|
|
IElementWiseLayer* conv123 = convBnSilu(network, weightMap, *conv122->getOutput(0), 128, 3, 1, 1, "model.123");
|
|
IElementWiseLayer* conv124 = convBnSilu(network, weightMap, *conv123->getOutput(0), 128, 3, 1, 1, "model.124");
|
|
IElementWiseLayer* conv125 = convBnSilu(network, weightMap, *conv124->getOutput(0), 128, 3, 1, 1, "model.125");
|
|
IElementWiseLayer* conv126 = convBnSilu(network, weightMap, *conv125->getOutput(0), 128, 3, 1, 1, "model.126");
|
|
IElementWiseLayer* conv127 = convBnSilu(network, weightMap, *conv126->getOutput(0), 128, 3, 1, 1, "model.127");
|
|
|
|
ITensor* input_tensor_128[] = { conv127->getOutput(0), conv126->getOutput(0),conv125->getOutput(0), conv124->getOutput(0),
|
|
conv123->getOutput(0), conv122->getOutput(0), conv121->getOutput(0), conv120->getOutput(0), conv119->getOutput(0),
|
|
conv118->getOutput(0) };
|
|
IConcatenationLayer* concat128 = network->addConcatenation(input_tensor_128, 10);
|
|
IElementWiseLayer* conv129 = convBnSilu(network, weightMap, *concat128->getOutput(0), 384, 1, 1, 0, "model.129");
|
|
|
|
auto conv130 = DownC(network, weightMap, *conv129->getOutput(0), 384, 576, "model.130");
|
|
ITensor* input_tensor_131[] = { conv130->getOutput(0), conv83->getOutput(0) };
|
|
IConcatenationLayer* concat131 = network->addConcatenation(input_tensor_131, 2);
|
|
|
|
IElementWiseLayer* conv132 = convBnSilu(network, weightMap, *concat131->getOutput(0), 384, 1, 1, 0, "model.132");
|
|
IElementWiseLayer* conv133 = convBnSilu(network, weightMap, *concat131->getOutput(0), 384, 1, 1, 0, "model.133");
|
|
|
|
IElementWiseLayer* conv134 = convBnSilu(network, weightMap, *conv133->getOutput(0), 192, 3, 1, 1, "model.134");
|
|
IElementWiseLayer* conv135 = convBnSilu(network, weightMap, *conv134->getOutput(0), 192, 3, 1, 1, "model.135");
|
|
IElementWiseLayer* conv136 = convBnSilu(network, weightMap, *conv135->getOutput(0), 192, 3, 1, 1, "model.136");
|
|
IElementWiseLayer* conv137 = convBnSilu(network, weightMap, *conv136->getOutput(0), 192, 3, 1, 1, "model.137");
|
|
IElementWiseLayer* conv138 = convBnSilu(network, weightMap, *conv137->getOutput(0), 192, 3, 1, 1, "model.138");
|
|
IElementWiseLayer* conv139 = convBnSilu(network, weightMap, *conv138->getOutput(0), 192, 3, 1, 1, "model.139");
|
|
IElementWiseLayer* conv140 = convBnSilu(network, weightMap, *conv139->getOutput(0), 192, 3, 1, 1, "model.140");
|
|
IElementWiseLayer* conv141 = convBnSilu(network, weightMap, *conv140->getOutput(0), 192, 3, 1, 1, "model.141");
|
|
ITensor* input_tensor_142[] = { conv141->getOutput(0), conv140->getOutput(0),conv139->getOutput(0), conv138->getOutput(0),
|
|
conv137->getOutput(0), conv136->getOutput(0), conv135->getOutput(0), conv134->getOutput(0), conv133->getOutput(0),
|
|
conv132->getOutput(0) };
|
|
IConcatenationLayer* concat142 = network->addConcatenation(input_tensor_142, 10);
|
|
IElementWiseLayer* conv143 = convBnSilu(network, weightMap, *concat142->getOutput(0), 576, 1, 1, 0, "model.143");
|
|
|
|
auto conv144 = DownC(network, weightMap, *conv143->getOutput(0), 576, 768, "model.144");
|
|
ITensor* input_tensor_145[] = { conv144->getOutput(0), conv67->getOutput(0) };
|
|
IConcatenationLayer* concat145 = network->addConcatenation(input_tensor_145, 2);
|
|
|
|
IElementWiseLayer* conv146 = convBnSilu(network, weightMap, *concat145->getOutput(0), 512, 1, 1, 0, "model.146");
|
|
IElementWiseLayer* conv147 = convBnSilu(network, weightMap, *concat145->getOutput(0), 512, 1, 1, 0, "model.147");
|
|
|
|
IElementWiseLayer* conv148 = convBnSilu(network, weightMap, *conv147->getOutput(0), 256, 3, 1, 1, "model.148");
|
|
IElementWiseLayer* conv149 = convBnSilu(network, weightMap, *conv148->getOutput(0), 256, 3, 1, 1, "model.149");
|
|
IElementWiseLayer* conv150 = convBnSilu(network, weightMap, *conv149->getOutput(0), 256, 3, 1, 1, "model.150");
|
|
IElementWiseLayer* conv151 = convBnSilu(network, weightMap, *conv150->getOutput(0), 256, 3, 1, 1, "model.151");
|
|
IElementWiseLayer* conv152 = convBnSilu(network, weightMap, *conv151->getOutput(0), 256, 3, 1, 1, "model.152");
|
|
IElementWiseLayer* conv153 = convBnSilu(network, weightMap, *conv152->getOutput(0), 256, 3, 1, 1, "model.153");
|
|
IElementWiseLayer* conv154 = convBnSilu(network, weightMap, *conv153->getOutput(0), 256, 3, 1, 1, "model.154");
|
|
IElementWiseLayer* conv155 = convBnSilu(network, weightMap, *conv154->getOutput(0), 256, 3, 1, 1, "model.155");
|
|
ITensor* input_tensor_156[] = { conv155->getOutput(0), conv154->getOutput(0),conv153->getOutput(0), conv152->getOutput(0),
|
|
conv151->getOutput(0), conv150->getOutput(0), conv149->getOutput(0), conv148->getOutput(0),conv147->getOutput(0),
|
|
conv146->getOutput(0) };
|
|
IConcatenationLayer* concat156 = network->addConcatenation(input_tensor_156, 10);
|
|
IElementWiseLayer* conv157 = convBnSilu(network, weightMap, *concat156->getOutput(0), 768, 1, 1, 0, "model.157");
|
|
|
|
IElementWiseLayer* conv158= convBnSilu(network, weightMap, *conv115->getOutput(0), 384, 3, 1, 1, "model.158");
|
|
IElementWiseLayer* conv159 = convBnSilu(network, weightMap, *conv129->getOutput(0), 768, 3, 1, 1, "model.159");
|
|
IElementWiseLayer* conv160 = convBnSilu(network, weightMap, *conv143->getOutput(0), 1152, 3, 1, 1, "model.160");
|
|
IElementWiseLayer* conv161 = convBnSilu(network, weightMap, *conv157->getOutput(0), 1536, 3, 1, 1, "model.161");
|
|
|
|
|
|
|
|
// out
|
|
IConvolutionLayer* cv105_0 = network->addConvolutionNd(*conv158->getOutput(0), 3 * (Yolo::CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.162.m.0.weight"], weightMap["model.162.m.0.bias"]);
|
|
assert(cv105_0);
|
|
cv105_0->setName("cv105.0");
|
|
IConvolutionLayer* cv105_1 = network->addConvolutionNd(*conv159->getOutput(0), 3 * (Yolo::CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.162.m.1.weight"], weightMap["model.162.m.1.bias"]);
|
|
assert(cv105_1);
|
|
cv105_1->setName("cv105.1");
|
|
IConvolutionLayer* cv105_2 = network->addConvolutionNd(*conv160->getOutput(0), 3 * (Yolo::CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.162.m.2.weight"], weightMap["model.162.m.2.bias"]);
|
|
assert(cv105_2);
|
|
cv105_2->setName("cv105.2");
|
|
IConvolutionLayer* cv105_3 = network->addConvolutionNd(*conv161->getOutput(0), 3 * (Yolo::CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.162.m.3.weight"], weightMap["model.162.m.3.bias"]);
|
|
assert(cv105_3);
|
|
cv105_3->setName("cv105.3");
|
|
|
|
|
|
|
|
|
|
/*------------detect-----------*/
|
|
auto yolo = addYoLoLayer(network, weightMap, "model.162", std::vector<IConvolutionLayer*>{cv105_0, cv105_1, cv105_2, cv105_3});
|
|
yolo->getOutput(0)->setName(OUTPUT_BLOB_NAME);
|
|
network->markOutput(*yolo->getOutput(0));
|
|
// Build engine
|
|
builder->setMaxBatchSize(maxBatchSize);
|
|
config->setMaxWorkspaceSize(16 * (1 << 20)); // 16MB
|
|
#if defined(USE_FP16)
|
|
config->setFlag(BuilderFlag::kFP16);
|
|
#endif
|
|
|
|
std::cout << "Building engine, please wait for a while..." << std::endl;
|
|
ICudaEngine* engine = builder->buildEngineWithConfig(*network, *config);
|
|
std::cout << "Build engine successfully!" << std::endl;
|
|
|
|
|
|
network->destroy();
|
|
|
|
// Release host memory
|
|
for (auto& mem : weightMap) {
|
|
free((void*)(mem.second.values));
|
|
}
|
|
|
|
return engine;
|
|
}
|
|
|
|
ICudaEngine* build_engine_yolov7e6(unsigned int maxBatchSize, IBuilder* builder, IBuilderConfig* config, DataType dt, const std::string& wts_path) {
|
|
std::map<std::string, Weights> weightMap = loadWeights(wts_path);
|
|
|
|
INetworkDefinition* network = builder->createNetworkV2(0U);
|
|
ITensor* data = network->addInput(INPUT_BLOB_NAME, dt, Dims3{ 3, INPUT_H, INPUT_W });
|
|
assert(data);
|
|
|
|
/*----------------------------------yolov7e6 backbone-----------------------------------------*/
|
|
auto* conv0 = ReOrg(network, weightMap, *data, 3);
|
|
|
|
|
|
IElementWiseLayer* conv1 = convBnSilu(network, weightMap, *conv0->getOutput(0), 80, 3, 1, 1, "model.1");
|
|
auto conv2 = DownC(network, weightMap, *conv1->getOutput(0), 80, 160, "model.2");
|
|
|
|
IElementWiseLayer* conv3 = convBnSilu(network, weightMap, *conv2->getOutput(0), 64, 1, 1, 0, "model.3");
|
|
IElementWiseLayer* conv4 = convBnSilu(network, weightMap, *conv2->getOutput(0), 64, 1, 1, 0, "model.4");
|
|
|
|
IElementWiseLayer* conv5 = convBnSilu(network, weightMap, *conv4->getOutput(0), 64, 3, 1, 1, "model.5");
|
|
IElementWiseLayer* conv6 = convBnSilu(network, weightMap, *conv5->getOutput(0), 64, 3, 1, 1, "model.6");
|
|
IElementWiseLayer* conv7 = convBnSilu(network, weightMap, *conv6->getOutput(0), 64, 3, 1, 1, "model.7");
|
|
IElementWiseLayer* conv8 = convBnSilu(network, weightMap, *conv7->getOutput(0), 64, 3, 1, 1, "model.8");
|
|
IElementWiseLayer* conv9 = convBnSilu(network, weightMap, *conv8->getOutput(0), 64, 3, 1, 1, "model.9");
|
|
IElementWiseLayer* conv10 = convBnSilu(network, weightMap, *conv9->getOutput(0), 64, 3, 1, 1, "model.10");
|
|
|
|
ITensor* input_tensor_11[] = { conv10->getOutput(0), conv8->getOutput(0),conv6->getOutput(0), conv4->getOutput(0),conv3->getOutput(0) };
|
|
IConcatenationLayer* concat11 = network->addConcatenation(input_tensor_11, 5);
|
|
|
|
IElementWiseLayer* conv12 = convBnSilu(network, weightMap, *concat11->getOutput(0), 160, 1, 1, 0, "model.12");
|
|
|
|
|
|
auto conv13 = DownC(network, weightMap, *conv12->getOutput(0), 160, 320, "model.13");
|
|
IElementWiseLayer* conv14 = convBnSilu(network, weightMap, *conv13->getOutput(0), 128, 1, 1, 0, "model.14");
|
|
IElementWiseLayer* conv15 = convBnSilu(network, weightMap, *conv13->getOutput(0), 128, 1, 1, 0, "model.15");
|
|
|
|
IElementWiseLayer* conv16 = convBnSilu(network, weightMap, *conv15->getOutput(0), 128, 3, 1, 1, "model.16");
|
|
IElementWiseLayer* conv17 = convBnSilu(network, weightMap, *conv16->getOutput(0), 128, 3, 1, 1, "model.17");
|
|
IElementWiseLayer* conv18 = convBnSilu(network, weightMap, *conv17->getOutput(0), 128, 3, 1, 1, "model.18");
|
|
IElementWiseLayer* conv19 = convBnSilu(network, weightMap, *conv18->getOutput(0), 128, 3, 1, 1, "model.19");
|
|
IElementWiseLayer* conv20 = convBnSilu(network, weightMap, *conv19->getOutput(0), 128, 3, 1, 1, "model.20");
|
|
IElementWiseLayer* conv21 = convBnSilu(network, weightMap, *conv20->getOutput(0), 128, 3, 1, 1, "model.21");
|
|
ITensor* input_tensor_22[] = { conv21->getOutput(0), conv19->getOutput(0),conv17->getOutput(0), conv15->getOutput(0),conv14->getOutput(0) };
|
|
IConcatenationLayer* concat22 = network->addConcatenation(input_tensor_22, 5);
|
|
|
|
IElementWiseLayer* conv23 = convBnSilu(network, weightMap, *concat22->getOutput(0), 320, 1, 1, 0, "model.23");
|
|
|
|
|
|
auto conv24 = DownC(network, weightMap, *conv23->getOutput(0), 320, 640, "model.24");
|
|
IElementWiseLayer* conv25 = convBnSilu(network, weightMap, *conv24->getOutput(0), 256, 1, 1, 0, "model.25");
|
|
IElementWiseLayer* conv26 = convBnSilu(network, weightMap, *conv24->getOutput(0), 256, 1, 1, 0, "model.26");
|
|
|
|
IElementWiseLayer* conv27 = convBnSilu(network, weightMap, *conv26->getOutput(0), 256, 3, 1, 1, "model.27");
|
|
IElementWiseLayer* conv28 = convBnSilu(network, weightMap, *conv27->getOutput(0), 256, 3, 1, 1, "model.28");
|
|
IElementWiseLayer* conv29 = convBnSilu(network, weightMap, *conv28->getOutput(0), 256, 3, 1, 1, "model.29");
|
|
IElementWiseLayer* conv30 = convBnSilu(network, weightMap, *conv29->getOutput(0), 256, 3, 1, 1, "model.30");
|
|
IElementWiseLayer* conv31 = convBnSilu(network, weightMap, *conv30->getOutput(0), 256, 3, 1, 1, "model.31");
|
|
IElementWiseLayer* conv32 = convBnSilu(network, weightMap, *conv31->getOutput(0), 256, 3, 1, 1, "model.32");
|
|
ITensor* input_tensor_33[] = { conv32->getOutput(0), conv30->getOutput(0),conv28->getOutput(0), conv26->getOutput(0),conv25->getOutput(0) };
|
|
IConcatenationLayer* concat33 = network->addConcatenation(input_tensor_33, 5);
|
|
|
|
IElementWiseLayer* conv34 = convBnSilu(network, weightMap, *concat33->getOutput(0), 640, 1, 1, 0, "model.34");
|
|
auto conv35 = DownC(network, weightMap, *conv34->getOutput(0), 640, 960, "model.35");
|
|
IElementWiseLayer* conv36 = convBnSilu(network, weightMap, *conv35->getOutput(0), 384, 1, 1, 0, "model.36");
|
|
IElementWiseLayer* conv37 = convBnSilu(network, weightMap, *conv35->getOutput(0), 384, 1, 1, 0, "model.37");
|
|
|
|
IElementWiseLayer* conv38 = convBnSilu(network, weightMap, *conv37->getOutput(0), 384, 3, 1, 1, "model.38");
|
|
IElementWiseLayer* conv39 = convBnSilu(network, weightMap, *conv38->getOutput(0), 384, 3, 1, 1, "model.39");
|
|
IElementWiseLayer* conv40 = convBnSilu(network, weightMap, *conv39->getOutput(0), 384, 3, 1, 1, "model.40");
|
|
IElementWiseLayer* conv41 = convBnSilu(network, weightMap, *conv40->getOutput(0), 384, 3, 1, 1, "model.41");
|
|
IElementWiseLayer* conv42 = convBnSilu(network, weightMap, *conv41->getOutput(0), 384, 3, 1, 1, "model.42");
|
|
IElementWiseLayer* conv43 = convBnSilu(network, weightMap, *conv42->getOutput(0), 384, 3, 1, 1, "model.43");
|
|
|
|
ITensor* input_tensor_44[] = { conv43->getOutput(0), conv41->getOutput(0),conv39->getOutput(0), conv37->getOutput(0),conv36->getOutput(0) };
|
|
IConcatenationLayer* concat44 = network->addConcatenation(input_tensor_44, 5);
|
|
IElementWiseLayer* conv45 = convBnSilu(network, weightMap, *concat44->getOutput(0), 960, 1, 1, 0, "model.45");
|
|
|
|
auto conv46 = DownC(network, weightMap, *conv45->getOutput(0), 960, 1280, "model.46");
|
|
IElementWiseLayer* conv47 = convBnSilu(network, weightMap, *conv46->getOutput(0), 512, 1, 1, 0, "model.47");
|
|
IElementWiseLayer* conv48 = convBnSilu(network, weightMap, *conv46->getOutput(0), 512, 1, 1, 0, "model.48");
|
|
|
|
IElementWiseLayer* conv49 = convBnSilu(network, weightMap, *conv48->getOutput(0), 512, 3, 1, 1, "model.49");
|
|
IElementWiseLayer* conv50 = convBnSilu(network, weightMap, *conv49->getOutput(0), 512, 3, 1, 1, "model.50");
|
|
IElementWiseLayer* conv51 = convBnSilu(network, weightMap, *conv50->getOutput(0), 512, 3, 1, 1, "model.51");
|
|
IElementWiseLayer* conv52 = convBnSilu(network, weightMap, *conv51->getOutput(0), 512, 3, 1, 1, "model.52");
|
|
IElementWiseLayer* conv53 = convBnSilu(network, weightMap, *conv52->getOutput(0), 512, 3, 1, 1, "model.53");
|
|
IElementWiseLayer* conv54 = convBnSilu(network, weightMap, *conv53->getOutput(0), 512, 3, 1, 1, "model.54");
|
|
ITensor* input_tensor_55[] = { conv54->getOutput(0), conv52->getOutput(0),conv50->getOutput(0), conv48->getOutput(0),conv47->getOutput(0) };
|
|
IConcatenationLayer* concat55 = network->addConcatenation(input_tensor_55, 5);
|
|
IElementWiseLayer* conv56 = convBnSilu(network, weightMap, *concat55->getOutput(0), 1280, 1, 1, 0, "model.56");
|
|
|
|
//------------------------yolov7e6 head-------------------------------
|
|
auto conv57 = SPPCSPC(network, weightMap, *conv56->getOutput(0), 640, "model.57");
|
|
IElementWiseLayer* conv58 = convBnSilu(network, weightMap, *conv57->getOutput(0), 480, 1, 1, 0, "model.58");
|
|
|
|
|
|
float scale[] = { 1.0, 2.0, 2.0 };
|
|
IResizeLayer* re59 = network->addResize(*conv58->getOutput(0));
|
|
re59->setResizeMode(ResizeMode::kNEAREST);
|
|
re59->setScales(scale, 3);
|
|
|
|
IElementWiseLayer* conv60 = convBnSilu(network, weightMap, *conv45->getOutput(0), 480, 1, 1, 0, "model.60");
|
|
ITensor* input_tensor_61[] = { conv60->getOutput(0), re59->getOutput(0) };
|
|
IConcatenationLayer* concat61 = network->addConcatenation(input_tensor_61, 2);
|
|
IElementWiseLayer* conv62 = convBnSilu(network, weightMap, *concat61->getOutput(0), 384, 1, 1, 0, "model.62");
|
|
IElementWiseLayer* conv63 = convBnSilu(network, weightMap, *concat61->getOutput(0), 384, 1, 1, 0, "model.63");
|
|
|
|
IElementWiseLayer* conv64 = convBnSilu(network, weightMap, *conv63->getOutput(0), 192, 3, 1, 1, "model.64");
|
|
IElementWiseLayer* conv65 = convBnSilu(network, weightMap, *conv64->getOutput(0), 192, 3, 1, 1, "model.65");
|
|
IElementWiseLayer* conv66 = convBnSilu(network, weightMap, *conv65->getOutput(0), 192, 3, 1, 1, "model.66");
|
|
IElementWiseLayer* conv67 = convBnSilu(network, weightMap, *conv66->getOutput(0), 192, 3, 1, 1, "model.67");
|
|
IElementWiseLayer* conv68 = convBnSilu(network, weightMap, *conv67->getOutput(0), 192, 3, 1, 1, "model.68");
|
|
IElementWiseLayer* conv69 = convBnSilu(network, weightMap, *conv68->getOutput(0), 192, 3, 1, 1, "model.69");
|
|
|
|
ITensor* input_tensor_70[] = { conv69->getOutput(0), conv68->getOutput(0),conv67->getOutput(0), conv66->getOutput(0),
|
|
conv65->getOutput(0), conv64->getOutput(0), conv63->getOutput(0), conv62->getOutput(0) };
|
|
IConcatenationLayer* concat70 = network->addConcatenation(input_tensor_70, 8);
|
|
IElementWiseLayer* conv71 = convBnSilu(network, weightMap, *concat70->getOutput(0), 480, 1, 1, 0, "model.71");
|
|
|
|
IElementWiseLayer* conv72 = convBnSilu(network, weightMap, *conv71->getOutput(0), 320, 1, 1, 0, "model.72");
|
|
IResizeLayer* re73 = network->addResize(*conv72->getOutput(0));
|
|
re73->setResizeMode(ResizeMode::kNEAREST);
|
|
re73->setScales(scale, 3);
|
|
IElementWiseLayer* conv74 = convBnSilu(network, weightMap, *conv34->getOutput(0), 320, 1, 1, 0, "model.74");
|
|
ITensor* input_tensor_75[] = { conv74->getOutput(0), re73->getOutput(0) };
|
|
IConcatenationLayer* concat75 = network->addConcatenation(input_tensor_75, 2);
|
|
|
|
IElementWiseLayer* conv76 = convBnSilu(network, weightMap, *concat75->getOutput(0), 256, 1, 1, 0, "model.76");
|
|
IElementWiseLayer* conv77 = convBnSilu(network, weightMap, *concat75->getOutput(0), 256, 1, 1, 0, "model.77");
|
|
|
|
IElementWiseLayer* conv78 = convBnSilu(network, weightMap, *conv77->getOutput(0), 128, 3, 1, 1, "model.78");
|
|
IElementWiseLayer* conv79 = convBnSilu(network, weightMap, *conv78->getOutput(0), 128, 3, 1, 1, "model.79");
|
|
IElementWiseLayer* conv80 = convBnSilu(network, weightMap, *conv79->getOutput(0), 128, 3, 1, 1, "model.80");
|
|
IElementWiseLayer* conv81 = convBnSilu(network, weightMap, *conv80->getOutput(0), 128, 3, 1, 1, "model.81");
|
|
IElementWiseLayer* conv82 = convBnSilu(network, weightMap, *conv81->getOutput(0), 128, 3, 1, 1, "model.82");
|
|
IElementWiseLayer* conv83 = convBnSilu(network, weightMap, *conv82->getOutput(0), 128, 3, 1, 1, "model.83");
|
|
|
|
ITensor* input_tensor_84[] = { conv83->getOutput(0), conv82->getOutput(0),conv81->getOutput(0), conv80->getOutput(0),
|
|
conv79->getOutput(0), conv78->getOutput(0), conv77->getOutput(0), conv76->getOutput(0) };
|
|
IConcatenationLayer* concat84 = network->addConcatenation(input_tensor_84, 8);
|
|
|
|
IElementWiseLayer* conv85 = convBnSilu(network, weightMap, *concat84->getOutput(0), 320, 1, 1, 0, "model.85");
|
|
|
|
IElementWiseLayer* conv86 = convBnSilu(network, weightMap, *conv85->getOutput(0), 160, 1, 1, 0, "model.86");
|
|
IResizeLayer* re87 = network->addResize(*conv86->getOutput(0));
|
|
re87->setResizeMode(ResizeMode::kNEAREST);
|
|
re87->setScales(scale, 3);
|
|
IElementWiseLayer* conv88 = convBnSilu(network, weightMap, *conv23->getOutput(0), 160, 1, 1, 0, "model.88");
|
|
ITensor* input_tensor_89[] = { conv88->getOutput(0), re87->getOutput(0) };
|
|
IConcatenationLayer* concat89 = network->addConcatenation(input_tensor_89, 2);
|
|
|
|
IElementWiseLayer* conv90 = convBnSilu(network, weightMap, *concat89->getOutput(0), 128, 1, 1, 0, "model.90");
|
|
IElementWiseLayer* conv91 = convBnSilu(network, weightMap, *concat89->getOutput(0), 128, 1, 1, 0, "model.91");
|
|
IElementWiseLayer* conv92 = convBnSilu(network, weightMap, *conv91->getOutput(0), 64, 3, 1, 1, "model.92");
|
|
IElementWiseLayer* conv93 = convBnSilu(network, weightMap, *conv92->getOutput(0), 64, 3, 1, 1, "model.93");
|
|
IElementWiseLayer* conv94 = convBnSilu(network, weightMap, *conv93->getOutput(0), 64, 3, 1, 1, "model.94");
|
|
IElementWiseLayer* conv95 = convBnSilu(network, weightMap, *conv94->getOutput(0), 64, 3, 1, 1, "model.95");
|
|
IElementWiseLayer* conv96 = convBnSilu(network, weightMap, *conv95->getOutput(0), 64, 3, 1, 1, "model.96");
|
|
IElementWiseLayer* conv97 = convBnSilu(network, weightMap, *conv96->getOutput(0), 64, 3, 1, 1, "model.97");
|
|
|
|
ITensor* input_tensor_98[] = { conv97->getOutput(0), conv96->getOutput(0),conv95->getOutput(0), conv94->getOutput(0),
|
|
conv93->getOutput(0), conv92->getOutput(0), conv91->getOutput(0), conv90->getOutput(0) };
|
|
IConcatenationLayer* concat98 = network->addConcatenation(input_tensor_98, 8);
|
|
|
|
IElementWiseLayer* conv99 = convBnSilu(network, weightMap, *concat98->getOutput(0), 160, 1, 1, 0, "model.99");
|
|
|
|
auto conv100 = DownC(network, weightMap, *conv99->getOutput(0), 160, 320, "model.100");
|
|
ITensor* input_tensor_101[] = { conv100->getOutput(0), conv85->getOutput(0) };
|
|
IConcatenationLayer* concat101 = network->addConcatenation(input_tensor_101, 2);
|
|
|
|
IElementWiseLayer* conv102 = convBnSilu(network, weightMap, *concat101->getOutput(0), 256, 1, 1, 0, "model.102");
|
|
IElementWiseLayer* conv103 = convBnSilu(network, weightMap, *concat101->getOutput(0), 256, 1, 1, 0, "model.103");
|
|
|
|
IElementWiseLayer* conv104 = convBnSilu(network, weightMap, *conv103->getOutput(0), 128, 3, 1, 1, "model.104");
|
|
IElementWiseLayer* conv105 = convBnSilu(network, weightMap, *conv104->getOutput(0), 128, 3, 1, 1, "model.105");
|
|
IElementWiseLayer* conv106 = convBnSilu(network, weightMap, *conv105->getOutput(0), 128, 3, 1, 1, "model.106");
|
|
IElementWiseLayer* conv107 = convBnSilu(network, weightMap, *conv106->getOutput(0), 128, 3, 1, 1, "model.107");
|
|
IElementWiseLayer* conv108 = convBnSilu(network, weightMap, *conv107->getOutput(0), 128, 3, 1, 1, "model.108");
|
|
IElementWiseLayer* conv109 = convBnSilu(network, weightMap, *conv108->getOutput(0), 128, 3, 1, 1, "model.109");
|
|
|
|
ITensor* input_tensor_110[] = { conv109->getOutput(0), conv108->getOutput(0),conv107->getOutput(0), conv106->getOutput(0),
|
|
conv105->getOutput(0), conv104->getOutput(0), conv103->getOutput(0), conv102->getOutput(0) };
|
|
IConcatenationLayer* concat110 = network->addConcatenation(input_tensor_110, 8);
|
|
IElementWiseLayer* conv111 = convBnSilu(network, weightMap, *concat110->getOutput(0), 320, 1, 1, 0, "model.111");
|
|
|
|
auto conv112 = DownC(network, weightMap, *conv111->getOutput(0), 320, 480, "model.112");
|
|
ITensor* input_tensor_113[] = { conv112->getOutput(0), conv71->getOutput(0) };
|
|
IConcatenationLayer* concat113 = network->addConcatenation(input_tensor_113, 2);
|
|
|
|
IElementWiseLayer* conv114 = convBnSilu(network, weightMap, *concat113->getOutput(0), 384, 1, 1, 0, "model.114");
|
|
IElementWiseLayer* conv115 = convBnSilu(network, weightMap, *concat113->getOutput(0), 384, 1, 1, 0, "model.115");
|
|
|
|
IElementWiseLayer* conv116 = convBnSilu(network, weightMap, *conv115->getOutput(0), 192, 3, 1, 1, "model.116");
|
|
IElementWiseLayer* conv117 = convBnSilu(network, weightMap, *conv116->getOutput(0), 192, 3, 1, 1, "model.117");
|
|
IElementWiseLayer* conv118 = convBnSilu(network, weightMap, *conv117->getOutput(0), 192, 3, 1, 1, "model.118");
|
|
IElementWiseLayer* conv119 = convBnSilu(network, weightMap, *conv118->getOutput(0), 192, 3, 1, 1, "model.119");
|
|
IElementWiseLayer* conv120 = convBnSilu(network, weightMap, *conv119->getOutput(0), 192, 3, 1, 1, "model.120");
|
|
IElementWiseLayer* conv121 = convBnSilu(network, weightMap, *conv120->getOutput(0), 192, 3, 1, 1, "model.121");
|
|
ITensor* input_tensor_122[] = { conv121->getOutput(0), conv120->getOutput(0),conv119->getOutput(0), conv118->getOutput(0),
|
|
conv117->getOutput(0), conv116->getOutput(0), conv115->getOutput(0), conv114->getOutput(0) };
|
|
IConcatenationLayer* concat122 = network->addConcatenation(input_tensor_122, 8);
|
|
IElementWiseLayer* conv123 = convBnSilu(network, weightMap, *concat122->getOutput(0), 480, 1, 1, 0, "model.123");
|
|
|
|
auto conv124 = DownC(network, weightMap, *conv123->getOutput(0), 480, 640, "model.124");
|
|
ITensor* input_tensor_125[] = { conv124->getOutput(0), conv57->getOutput(0) };
|
|
IConcatenationLayer* concat125 = network->addConcatenation(input_tensor_125, 2);
|
|
|
|
IElementWiseLayer* conv126 = convBnSilu(network, weightMap, *concat125->getOutput(0), 512, 1, 1, 0, "model.126");
|
|
IElementWiseLayer* conv127 = convBnSilu(network, weightMap, *concat125->getOutput(0), 512, 1, 1, 0, "model.127");
|
|
|
|
IElementWiseLayer* conv128 = convBnSilu(network, weightMap, *conv127->getOutput(0), 256, 3, 1, 1, "model.128");
|
|
IElementWiseLayer* conv129 = convBnSilu(network, weightMap, *conv128->getOutput(0), 256, 3, 1, 1, "model.129");
|
|
IElementWiseLayer* conv130 = convBnSilu(network, weightMap, *conv129->getOutput(0), 256, 3, 1, 1, "model.130");
|
|
IElementWiseLayer* conv131 = convBnSilu(network, weightMap, *conv130->getOutput(0), 256, 3, 1, 1, "model.131");
|
|
IElementWiseLayer* conv132 = convBnSilu(network, weightMap, *conv131->getOutput(0), 256, 3, 1, 1, "model.132");
|
|
IElementWiseLayer* conv133 = convBnSilu(network, weightMap, *conv132->getOutput(0), 256, 3, 1, 1, "model.133");
|
|
ITensor* input_tensor_134[] = { conv133->getOutput(0), conv132->getOutput(0),conv131->getOutput(0), conv130->getOutput(0),
|
|
conv129->getOutput(0), conv128->getOutput(0), conv127->getOutput(0), conv126->getOutput(0) };
|
|
IConcatenationLayer* concat134 = network->addConcatenation(input_tensor_134, 8);
|
|
IElementWiseLayer* conv135 = convBnSilu(network, weightMap, *concat134->getOutput(0), 640, 1, 1, 0, "model.135");
|
|
|
|
IElementWiseLayer* conv136 = convBnSilu(network, weightMap, *conv99->getOutput(0), 320, 3, 1, 1, "model.136");
|
|
IElementWiseLayer* conv137 = convBnSilu(network, weightMap, *conv111->getOutput(0), 640, 3, 1, 1, "model.137");
|
|
IElementWiseLayer* conv138 = convBnSilu(network, weightMap, *conv123->getOutput(0), 960, 3, 1, 1, "model.138");
|
|
IElementWiseLayer* conv139 = convBnSilu(network, weightMap, *conv135->getOutput(0), 1280, 3, 1, 1, "model.139");
|
|
|
|
|
|
|
|
// out
|
|
IConvolutionLayer* cv105_0 = network->addConvolutionNd(*conv136->getOutput(0), 3 * (Yolo::CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.140.m.0.weight"], weightMap["model.140.m.0.bias"]);
|
|
assert(cv105_0);
|
|
cv105_0->setName("cv105.0");
|
|
IConvolutionLayer* cv105_1 = network->addConvolutionNd(*conv137->getOutput(0), 3 * (Yolo::CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.140.m.1.weight"], weightMap["model.140.m.1.bias"]);
|
|
assert(cv105_1);
|
|
cv105_1->setName("cv105.1");
|
|
IConvolutionLayer* cv105_2 = network->addConvolutionNd(*conv138->getOutput(0), 3 * (Yolo::CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.140.m.2.weight"], weightMap["model.140.m.2.bias"]);
|
|
assert(cv105_2);
|
|
cv105_2->setName("cv105.2");
|
|
IConvolutionLayer* cv105_3 = network->addConvolutionNd(*conv139->getOutput(0), 3 * (Yolo::CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.140.m.3.weight"], weightMap["model.140.m.3.bias"]);
|
|
assert(cv105_3);
|
|
cv105_3->setName("cv105.3");
|
|
|
|
|
|
|
|
|
|
/*------------detect-----------*/
|
|
auto yolo = addYoLoLayer(network, weightMap, "model.140", std::vector<IConvolutionLayer*>{cv105_0, cv105_1, cv105_2, cv105_3});
|
|
yolo->getOutput(0)->setName(OUTPUT_BLOB_NAME);
|
|
network->markOutput(*yolo->getOutput(0));
|
|
// Build engine
|
|
builder->setMaxBatchSize(maxBatchSize);
|
|
config->setMaxWorkspaceSize(16 * (1 << 20)); // 16MB
|
|
#if defined(USE_FP16)
|
|
config->setFlag(BuilderFlag::kFP16);
|
|
#endif
|
|
|
|
std::cout << "Building engine, please wait for a while..." << std::endl;
|
|
ICudaEngine* engine = builder->buildEngineWithConfig(*network, *config);
|
|
std::cout << "Build engine successfully!" << std::endl;
|
|
|
|
|
|
network->destroy();
|
|
|
|
// Release host memory
|
|
for (auto& mem : weightMap)
|
|
{
|
|
free((void*)(mem.second.values));
|
|
}
|
|
|
|
return engine;
|
|
}
|
|
|
|
ICudaEngine* build_engine_yolov7w6(unsigned int maxBatchSize, IBuilder* builder, IBuilderConfig* config, DataType dt, const std::string& wts_path) {
|
|
std::map<std::string, Weights> weightMap = loadWeights(wts_path);
|
|
|
|
INetworkDefinition* network = builder->createNetworkV2(0U);
|
|
ITensor* data = network->addInput(INPUT_BLOB_NAME, dt, Dims3{ 3, INPUT_H, INPUT_W });
|
|
assert(data);
|
|
|
|
/*----------------------------------yolov7w6 backbone-----------------------------------------*/
|
|
auto* conv0 = ReOrg(network, weightMap, *data, 3);
|
|
|
|
|
|
IElementWiseLayer* conv1 = convBnSilu(network, weightMap, *conv0->getOutput(0), 64, 3, 1, 1, "model.1");
|
|
|
|
IElementWiseLayer* conv2 = convBnSilu(network, weightMap, *conv1->getOutput(0), 128, 3, 2, 1, "model.2");
|
|
|
|
IElementWiseLayer* conv3 = convBnSilu(network, weightMap, *conv2->getOutput(0), 64, 1, 1, 0, "model.3");
|
|
IElementWiseLayer* conv4 = convBnSilu(network, weightMap, *conv2->getOutput(0), 64, 1, 1, 0, "model.4");
|
|
|
|
IElementWiseLayer* conv5 = convBnSilu(network, weightMap, *conv4->getOutput(0), 64, 3, 1, 1, "model.5");
|
|
IElementWiseLayer* conv6 = convBnSilu(network, weightMap, *conv5->getOutput(0), 64, 3, 1, 1, "model.6");
|
|
IElementWiseLayer* conv7 = convBnSilu(network, weightMap, *conv6->getOutput(0), 64, 3, 1, 1, "model.7");
|
|
IElementWiseLayer* conv8 = convBnSilu(network, weightMap, *conv7->getOutput(0), 64, 3, 1, 1, "model.8");
|
|
|
|
|
|
|
|
ITensor* input_tensor_9[] = { conv8->getOutput(0), conv6->getOutput(0), conv4->getOutput(0), conv3->getOutput(0) };
|
|
IConcatenationLayer* concat9 = network->addConcatenation(input_tensor_9, 4);
|
|
concat9->setAxis(0);
|
|
IElementWiseLayer* conv10 = convBnSilu(network, weightMap, *concat9->getOutput(0), 128, 1, 1, 0, "model.10");
|
|
|
|
IElementWiseLayer* conv11 = convBnSilu(network, weightMap, *conv10->getOutput(0), 256, 3, 2, 1, "model.11");
|
|
|
|
IElementWiseLayer* conv12 = convBnSilu(network, weightMap, *conv11->getOutput(0), 128, 1, 1, 0, "model.12");
|
|
IElementWiseLayer* conv13 = convBnSilu(network, weightMap, *conv11->getOutput(0), 128, 1, 1, 0, "model.13");
|
|
IElementWiseLayer* conv14 = convBnSilu(network, weightMap, *conv13->getOutput(0), 128, 3, 1, 1, "model.14");
|
|
IElementWiseLayer* conv15 = convBnSilu(network, weightMap, *conv14->getOutput(0), 128, 3, 1, 1, "model.15");
|
|
IElementWiseLayer* conv16 = convBnSilu(network, weightMap, *conv15->getOutput(0), 128, 3, 1, 1, "model.16");
|
|
IElementWiseLayer* conv17 = convBnSilu(network, weightMap, *conv16->getOutput(0), 128, 3, 1, 1, "model.17");
|
|
ITensor* input_tensor_18[] = { conv17->getOutput(0), conv15->getOutput(0), conv13->getOutput(0), conv12->getOutput(0) };
|
|
IConcatenationLayer* concat18 = network->addConcatenation(input_tensor_18, 4);
|
|
concat18->setAxis(0);
|
|
IElementWiseLayer* conv19 = convBnSilu(network, weightMap, *concat18->getOutput(0), 256, 1, 1, 0, "model.19");
|
|
|
|
IElementWiseLayer* conv20 = convBnSilu(network, weightMap, *conv19->getOutput(0), 512, 3, 2, 1, "model.20");
|
|
|
|
IElementWiseLayer* conv21 = convBnSilu(network, weightMap, *conv20->getOutput(0), 256, 1, 1, 0, "model.21");
|
|
IElementWiseLayer* conv22 = convBnSilu(network, weightMap, *conv20->getOutput(0), 256, 1, 1, 0, "model.22");
|
|
IElementWiseLayer* conv23 = convBnSilu(network, weightMap, *conv22->getOutput(0), 256, 3, 1, 1, "model.23");
|
|
IElementWiseLayer* conv24 = convBnSilu(network, weightMap, *conv23->getOutput(0), 256, 3, 1, 1, "model.24");
|
|
IElementWiseLayer* conv25 = convBnSilu(network, weightMap, *conv24->getOutput(0), 256, 3, 1, 1, "model.25");
|
|
IElementWiseLayer* conv26 = convBnSilu(network, weightMap, *conv25->getOutput(0), 256, 3, 1, 1, "model.26");
|
|
ITensor* input_tensor_27[] = { conv26->getOutput(0), conv24->getOutput(0), conv22->getOutput(0), conv21->getOutput(0) };
|
|
IConcatenationLayer* concat27 = network->addConcatenation(input_tensor_27, 4);
|
|
concat27->setAxis(0);
|
|
|
|
|
|
|
|
IElementWiseLayer* conv28 = convBnSilu(network, weightMap, *concat27->getOutput(0), 512, 1, 1, 0, "model.28");
|
|
|
|
IElementWiseLayer* conv29 = convBnSilu(network, weightMap, *conv28->getOutput(0), 768, 3, 2, 1, "model.29");
|
|
|
|
IElementWiseLayer* conv30 = convBnSilu(network, weightMap, *conv29->getOutput(0), 384, 1, 1, 0, "model.30");
|
|
IElementWiseLayer* conv31 = convBnSilu(network, weightMap, *conv29->getOutput(0), 384, 1, 1, 0, "model.31");
|
|
IElementWiseLayer* conv32 = convBnSilu(network, weightMap, *conv31->getOutput(0), 384, 3, 1, 1, "model.32");
|
|
IElementWiseLayer* conv33 = convBnSilu(network, weightMap, *conv32->getOutput(0), 384, 3, 1, 1, "model.33");
|
|
IElementWiseLayer* conv34 = convBnSilu(network, weightMap, *conv33->getOutput(0), 384, 3, 1, 1, "model.34");
|
|
IElementWiseLayer* conv35 = convBnSilu(network, weightMap, *conv34->getOutput(0), 384, 3, 1, 1, "model.35");
|
|
ITensor* input_tensor_36[] = { conv35->getOutput(0), conv33->getOutput(0), conv31->getOutput(0), conv30->getOutput(0) };
|
|
IConcatenationLayer* concat36 = network->addConcatenation(input_tensor_36, 4);
|
|
IElementWiseLayer* conv37 = convBnSilu(network, weightMap, *concat36->getOutput(0), 768, 1, 1, 0, "model.37");
|
|
|
|
IElementWiseLayer* conv38 = convBnSilu(network, weightMap, *conv37->getOutput(0), 1024, 3, 2, 1, "model.38");
|
|
|
|
IElementWiseLayer* conv39 = convBnSilu(network, weightMap, *conv38->getOutput(0), 512, 1, 1, 0, "model.39");
|
|
IElementWiseLayer* conv40 = convBnSilu(network, weightMap, *conv38->getOutput(0), 512, 1, 1, 0, "model.40");
|
|
IElementWiseLayer* conv41 = convBnSilu(network, weightMap, *conv40->getOutput(0), 512, 3, 1, 1, "model.41");
|
|
IElementWiseLayer* conv42 = convBnSilu(network, weightMap, *conv41->getOutput(0), 512, 3, 1, 1, "model.42");
|
|
IElementWiseLayer* conv43 = convBnSilu(network, weightMap, *conv42->getOutput(0), 512, 3, 1, 1, "model.43");
|
|
IElementWiseLayer* conv44 = convBnSilu(network, weightMap, *conv43->getOutput(0), 512, 3, 1, 1, "model.44");
|
|
ITensor* input_tensor_45[] = { conv44->getOutput(0), conv42->getOutput(0), conv40->getOutput(0), conv39->getOutput(0) };
|
|
IConcatenationLayer* concat45 = network->addConcatenation(input_tensor_45, 4);
|
|
IElementWiseLayer* conv46 = convBnSilu(network, weightMap, *concat45->getOutput(0), 1024, 1, 1, 0, "model.46");
|
|
|
|
//----------------head============================
|
|
auto conv47 = SPPCSPC(network, weightMap, *conv46->getOutput(0), 512, "model.47");
|
|
IElementWiseLayer* conv48 = convBnSilu(network, weightMap, *conv47->getOutput(0), 384, 1, 1, 0, "model.48");
|
|
|
|
|
|
float scale[] = { 1.0, 2.0, 2.0 };
|
|
IResizeLayer* re49 = network->addResize(*conv48->getOutput(0));
|
|
re49->setResizeMode(ResizeMode::kNEAREST);
|
|
re49->setScales(scale, 3);
|
|
|
|
IElementWiseLayer* conv50 = convBnSilu(network, weightMap, *conv37->getOutput(0), 384, 1, 1, 0, "model.50");
|
|
ITensor* input_tensor_51[] = { conv50->getOutput(0), re49->getOutput(0) };
|
|
IConcatenationLayer* concat51 = network->addConcatenation(input_tensor_51, 2);
|
|
|
|
IElementWiseLayer* conv52 = convBnSilu(network, weightMap, *concat51->getOutput(0), 384, 1, 1, 0, "model.52");
|
|
IElementWiseLayer* conv53 = convBnSilu(network, weightMap, *concat51->getOutput(0), 384, 1, 1, 0, "model.53");
|
|
IElementWiseLayer* conv54 = convBnSilu(network, weightMap, *conv53->getOutput(0), 192, 3, 1, 1, "model.54");
|
|
IElementWiseLayer* conv55 = convBnSilu(network, weightMap, *conv54->getOutput(0), 192, 3, 1, 1, "model.55");
|
|
IElementWiseLayer* conv56 = convBnSilu(network, weightMap, *conv55->getOutput(0), 192, 3, 1, 1, "model.56");
|
|
IElementWiseLayer* conv57 = convBnSilu(network, weightMap, *conv56->getOutput(0), 192, 3, 1, 1, "model.57");
|
|
|
|
|
|
ITensor* input_tensor_58[] = { conv57->getOutput(0), conv56->getOutput(0), conv55->getOutput(0), conv54->getOutput(0), conv53->getOutput(0), conv52->getOutput(0) };
|
|
IConcatenationLayer* concat58 = network->addConcatenation(input_tensor_58, 6);
|
|
|
|
IElementWiseLayer* conv59 = convBnSilu(network, weightMap, *concat58->getOutput(0), 384, 1, 1, 0, "model.59");
|
|
|
|
IElementWiseLayer* conv60 = convBnSilu(network, weightMap, *conv59->getOutput(0), 256, 1, 1, 0, "model.60");
|
|
IResizeLayer* re61 = network->addResize(*conv60->getOutput(0));
|
|
re61->setResizeMode(ResizeMode::kNEAREST);
|
|
re61->setScales(scale, 3);
|
|
IElementWiseLayer* conv62 = convBnSilu(network, weightMap, *conv28->getOutput(0), 256, 1, 1, 0, "model.62");
|
|
ITensor* input_tensor_63[] = { conv62->getOutput(0), re61->getOutput(0) };
|
|
IConcatenationLayer* concat63 = network->addConcatenation(input_tensor_63, 2);
|
|
|
|
|
|
IElementWiseLayer* conv64 = convBnSilu(network, weightMap, *concat63->getOutput(0), 256, 1, 1, 0, "model.64");
|
|
IElementWiseLayer* conv65 = convBnSilu(network, weightMap, *concat63->getOutput(0), 256, 1, 1, 0, "model.65");
|
|
IElementWiseLayer* conv66 = convBnSilu(network, weightMap, *conv65->getOutput(0), 128, 3, 1, 1, "model.66");
|
|
IElementWiseLayer* conv67 = convBnSilu(network, weightMap, *conv66->getOutput(0), 128, 3, 1, 1, "model.67");
|
|
IElementWiseLayer* conv68 = convBnSilu(network, weightMap, *conv67->getOutput(0), 128, 3, 1, 1, "model.68");
|
|
IElementWiseLayer* conv69 = convBnSilu(network, weightMap, *conv68->getOutput(0), 128, 3, 1, 1, "model.69");
|
|
|
|
ITensor* input_tensor_70[] = { conv69->getOutput(0), conv68->getOutput(0), conv67->getOutput(0), conv66->getOutput(0), conv65->getOutput(0), conv64->getOutput(0) };
|
|
IConcatenationLayer* concat70 = network->addConcatenation(input_tensor_70, 6);
|
|
|
|
IElementWiseLayer* conv71 = convBnSilu(network, weightMap, *concat70->getOutput(0), 256, 1, 1, 0, "model.71");
|
|
IElementWiseLayer* conv72 = convBnSilu(network, weightMap, *conv71->getOutput(0), 128, 1, 1, 0, "model.72");
|
|
IResizeLayer* re73 = network->addResize(*conv72->getOutput(0));
|
|
re73->setResizeMode(ResizeMode::kNEAREST);
|
|
re73->setScales(scale, 3);
|
|
|
|
IElementWiseLayer* conv74 = convBnSilu(network, weightMap, *conv19->getOutput(0), 128, 1, 1, 0, "model.74");
|
|
ITensor* input_tensor_75[] = { conv74->getOutput(0), re73->getOutput(0) };
|
|
IConcatenationLayer* concat75 = network->addConcatenation(input_tensor_75, 2);
|
|
IElementWiseLayer* conv76 = convBnSilu(network, weightMap, *concat75->getOutput(0), 128, 1, 1, 0, "model.76");
|
|
IElementWiseLayer* conv77 = convBnSilu(network, weightMap, *concat75->getOutput(0), 128, 1, 1, 0, "model.77");
|
|
|
|
IElementWiseLayer* conv78 = convBnSilu(network, weightMap, *conv77->getOutput(0), 64, 3, 1, 1, "model.78");
|
|
IElementWiseLayer* conv79 = convBnSilu(network, weightMap, *conv78->getOutput(0), 64, 3, 1, 1, "model.79");
|
|
IElementWiseLayer* conv80 = convBnSilu(network, weightMap, *conv79->getOutput(0), 64, 3, 1, 1, "model.80");
|
|
IElementWiseLayer* conv81 = convBnSilu(network, weightMap, *conv80->getOutput(0), 64, 3, 1, 1, "model.81");
|
|
ITensor* input_tensor_82[] = { conv81->getOutput(0), conv80->getOutput(0), conv79->getOutput(0), conv78->getOutput(0), conv77->getOutput(0), conv76->getOutput(0) };
|
|
IConcatenationLayer* concat82 = network->addConcatenation(input_tensor_82, 6);
|
|
|
|
IElementWiseLayer* conv83 = convBnSilu(network, weightMap, *concat82->getOutput(0), 128, 1, 1, 0, "model.83");
|
|
|
|
IElementWiseLayer* conv84 = convBnSilu(network, weightMap, *conv83->getOutput(0), 256, 3, 2, 1, "model.84");
|
|
ITensor* input_tensor_85[] = { conv84->getOutput(0), conv71->getOutput(0) };
|
|
IConcatenationLayer* concat85 = network->addConcatenation(input_tensor_85, 2);
|
|
|
|
IElementWiseLayer* conv86 = convBnSilu(network, weightMap, *concat85->getOutput(0), 256, 1, 1, 0, "model.86");
|
|
IElementWiseLayer* conv87 = convBnSilu(network, weightMap, *concat85->getOutput(0), 256, 1, 1, 0, "model.87");
|
|
IElementWiseLayer* conv88 = convBnSilu(network, weightMap, *conv87->getOutput(0), 128, 3, 1, 1, "model.88");
|
|
IElementWiseLayer* conv89 = convBnSilu(network, weightMap, *conv88->getOutput(0), 128, 3, 1, 1, "model.89");
|
|
IElementWiseLayer* conv90 = convBnSilu(network, weightMap, *conv89->getOutput(0), 128, 3, 1, 1, "model.90");
|
|
IElementWiseLayer* conv91 = convBnSilu(network, weightMap, *conv90->getOutput(0), 128, 3, 1, 1, "model.91");
|
|
|
|
ITensor* input_tensor_92[] = { conv91->getOutput(0), conv90->getOutput(0), conv89->getOutput(0), conv88->getOutput(0), conv87->getOutput(0), conv86->getOutput(0) };
|
|
IConcatenationLayer* concat92 = network->addConcatenation(input_tensor_92, 6);
|
|
|
|
IElementWiseLayer* conv93 = convBnSilu(network, weightMap, *concat92->getOutput(0), 256, 1, 1, 0, "model.93");
|
|
|
|
IElementWiseLayer* conv94 = convBnSilu(network, weightMap, *conv93->getOutput(0), 384, 3, 2, 1, "model.94");
|
|
ITensor* input_tensor_95[] = { conv94->getOutput(0), conv59->getOutput(0) };
|
|
IConcatenationLayer* concat95 = network->addConcatenation(input_tensor_95, 2);
|
|
|
|
IElementWiseLayer* conv96 = convBnSilu(network, weightMap, *concat95->getOutput(0), 384, 1, 1, 0, "model.96");
|
|
IElementWiseLayer* conv97 = convBnSilu(network, weightMap, *concat95->getOutput(0), 384, 1, 1, 0, "model.97");
|
|
|
|
IElementWiseLayer* conv98 = convBnSilu(network, weightMap, *conv97->getOutput(0), 192, 3, 1, 1, "model.98");
|
|
IElementWiseLayer* conv99 = convBnSilu(network, weightMap, *conv98->getOutput(0), 192, 3, 1, 1, "model.99");
|
|
IElementWiseLayer* conv100 = convBnSilu(network, weightMap, *conv99->getOutput(0), 192, 3, 1, 1, "model.100");
|
|
IElementWiseLayer* conv101 = convBnSilu(network, weightMap, *conv100->getOutput(0), 192, 3, 1, 1, "model.101");
|
|
ITensor* input_tensor_102[] = { conv101->getOutput(0), conv100->getOutput(0), conv99->getOutput(0), conv98->getOutput(0), conv97->getOutput(0), conv96->getOutput(0) };
|
|
IConcatenationLayer* concat102 = network->addConcatenation(input_tensor_102, 6);
|
|
IElementWiseLayer* conv103 = convBnSilu(network, weightMap, *concat102->getOutput(0), 384, 1, 1, 0, "model.103");
|
|
|
|
IElementWiseLayer* conv104 = convBnSilu(network, weightMap, *conv103->getOutput(0), 512, 3, 2, 1, "model.104");
|
|
|
|
|
|
ITensor* input_tensor_105[] = { conv104->getOutput(0), conv47->getOutput(0) };
|
|
IConcatenationLayer* concat105 = network->addConcatenation(input_tensor_105, 2);
|
|
|
|
IElementWiseLayer* conv106 = convBnSilu(network, weightMap, *concat105->getOutput(0), 512, 1, 1, 0, "model.106");
|
|
IElementWiseLayer* conv107 = convBnSilu(network, weightMap, *concat105->getOutput(0), 512, 1, 1, 0, "model.107");
|
|
|
|
IElementWiseLayer* conv108 = convBnSilu(network, weightMap, *conv107->getOutput(0), 256, 3, 1, 1, "model.108");
|
|
IElementWiseLayer* conv109 = convBnSilu(network, weightMap, *conv108->getOutput(0), 256, 3, 1, 1, "model.109");
|
|
IElementWiseLayer* conv110 = convBnSilu(network, weightMap, *conv109->getOutput(0), 256, 3, 1, 1, "model.110");
|
|
IElementWiseLayer* conv111 = convBnSilu(network, weightMap, *conv110->getOutput(0), 256, 3, 1, 1, "model.111");
|
|
ITensor* input_tensor_112[] = { conv111->getOutput(0), conv110->getOutput(0), conv109->getOutput(0), conv108->getOutput(0), conv107->getOutput(0), conv106->getOutput(0) };
|
|
IConcatenationLayer* concat112 = network->addConcatenation(input_tensor_112, 6);
|
|
|
|
IElementWiseLayer* conv113 = convBnSilu(network, weightMap, *concat112->getOutput(0), 512, 1, 1, 0, "model.113");
|
|
|
|
IElementWiseLayer* conv114 = convBnSilu(network, weightMap, *conv83->getOutput(0), 256, 3, 1, 1, "model.114");
|
|
IElementWiseLayer* conv115 = convBnSilu(network, weightMap, *conv93->getOutput(0), 512, 3, 1, 1, "model.115");
|
|
IElementWiseLayer* conv116 = convBnSilu(network, weightMap, *conv103->getOutput(0), 768, 3, 1, 1, "model.116");
|
|
IElementWiseLayer* conv117 = convBnSilu(network, weightMap, *conv113->getOutput(0), 1024, 3, 1, 1, "model.117");
|
|
|
|
|
|
|
|
// out
|
|
IConvolutionLayer* cv105_0 = network->addConvolutionNd(*conv114->getOutput(0), 3 * (Yolo::CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.118.m.0.weight"], weightMap["model.118.m.0.bias"]);
|
|
assert(cv105_0);
|
|
cv105_0->setName("cv105.0");
|
|
IConvolutionLayer* cv105_1 = network->addConvolutionNd(*conv115->getOutput(0), 3 * (Yolo::CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.118.m.1.weight"], weightMap["model.118.m.1.bias"]);
|
|
assert(cv105_1);
|
|
cv105_1->setName("cv105.1");
|
|
IConvolutionLayer* cv105_2 = network->addConvolutionNd(*conv116->getOutput(0), 3 * (Yolo::CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.118.m.2.weight"], weightMap["model.118.m.2.bias"]);
|
|
assert(cv105_2);
|
|
cv105_2->setName("cv105.2");
|
|
IConvolutionLayer* cv105_3 = network->addConvolutionNd(*conv117->getOutput(0), 3 * (Yolo::CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.118.m.3.weight"], weightMap["model.118.m.3.bias"]);
|
|
assert(cv105_3);
|
|
cv105_3->setName("cv105.3");
|
|
|
|
|
|
|
|
/*------------detect-----------*/
|
|
auto yolo = addYoLoLayer(network, weightMap, "model.118", std::vector<IConvolutionLayer*>{cv105_0, cv105_1, cv105_2, cv105_3});
|
|
yolo->getOutput(0)->setName(OUTPUT_BLOB_NAME);
|
|
network->markOutput(*yolo->getOutput(0));
|
|
// Build engine
|
|
builder->setMaxBatchSize(maxBatchSize);
|
|
config->setMaxWorkspaceSize(16 * (1 << 20)); // 16MB
|
|
#if defined(USE_FP16)
|
|
config->setFlag(BuilderFlag::kFP16);
|
|
#endif
|
|
|
|
std::cout << "Building engine, please wait for a while..." << std::endl;
|
|
ICudaEngine* engine = builder->buildEngineWithConfig(*network, *config);
|
|
std::cout << "Build engine successfully!" << std::endl;
|
|
|
|
|
|
network->destroy();
|
|
|
|
// Release host memory
|
|
for (auto& mem : weightMap) {
|
|
free((void*)(mem.second.values));
|
|
}
|
|
|
|
return engine;
|
|
}
|
|
|
|
//----------------------------------yolov7x---------------------------------------------------
|
|
ICudaEngine* build_engine_yolov7x(unsigned int maxBatchSize,IBuilder* builder, IBuilderConfig* config, DataType dt, const std::string& wts_path) {
|
|
std::map<std::string, Weights> weightMap = loadWeights(wts_path);
|
|
|
|
INetworkDefinition* network = builder->createNetworkV2(0U);
|
|
ITensor* data = network->addInput(INPUT_BLOB_NAME, dt, Dims3{ 3, INPUT_H, INPUT_W });
|
|
assert(data);
|
|
|
|
/*----------------------------------yolov7x backbone-----------------------------------------*/
|
|
IElementWiseLayer* conv0 = convBnSilu(network, weightMap, *data, 40, 3, 1, 1, "model.0");
|
|
|
|
IElementWiseLayer* conv1 = convBnSilu(network, weightMap, *conv0->getOutput(0), 80, 3, 2, 1, "model.1");
|
|
IElementWiseLayer* conv2 = convBnSilu(network, weightMap, *conv1->getOutput(0), 80, 3, 1, 1, "model.2");
|
|
IElementWiseLayer* conv3 = convBnSilu(network, weightMap, *conv2->getOutput(0), 160, 3, 2, 1, "model.3");
|
|
|
|
|
|
IElementWiseLayer* conv4 = convBnSilu(network, weightMap, *conv3->getOutput(0), 64, 1, 1, 0, "model.4");
|
|
|
|
IElementWiseLayer* conv5 = convBnSilu(network, weightMap, *conv3->getOutput(0), 64, 1, 1, 0, "model.5");
|
|
IElementWiseLayer* conv6 = convBnSilu(network, weightMap, *conv5->getOutput(0), 64, 3, 1, 1, "model.6");
|
|
IElementWiseLayer* conv7 = convBnSilu(network, weightMap, *conv6->getOutput(0), 64, 3, 1, 1, "model.7");
|
|
IElementWiseLayer* conv8 = convBnSilu(network, weightMap, *conv7->getOutput(0), 64, 3, 1, 1, "model.8");
|
|
IElementWiseLayer* conv9 = convBnSilu(network, weightMap, *conv8->getOutput(0), 64, 3, 1, 1, "model.9");
|
|
IElementWiseLayer* conv10 = convBnSilu(network, weightMap, *conv9->getOutput(0), 64, 3, 1, 1, "model.10");
|
|
IElementWiseLayer* conv11 = convBnSilu(network, weightMap, *conv10->getOutput(0), 64, 3, 1, 1, "model.11");
|
|
|
|
ITensor* input_tensor_12[] = { conv11->getOutput(0), conv9->getOutput(0), conv7->getOutput(0), conv5->getOutput(0),conv4->getOutput(0) };
|
|
IConcatenationLayer* concat12 = network->addConcatenation(input_tensor_12, 5);
|
|
//concat9->setAxis(0);
|
|
IElementWiseLayer* conv13 = convBnSilu(network, weightMap, *concat12->getOutput(0), 320, 1, 1, 0, "model.13");
|
|
|
|
|
|
|
|
IPoolingLayer* mp1 = network->addPoolingNd(*conv13->getOutput(0), PoolingType::kMAX, DimsHW{ 2, 2 });
|
|
mp1->setStrideNd(DimsHW{ 2, 2 });
|
|
IElementWiseLayer* conv15 = convBnSilu(network, weightMap, *mp1->getOutput(0), 160, 1, 1, 0, "model.15");
|
|
|
|
IElementWiseLayer* conv16 = convBnSilu(network, weightMap, *conv13->getOutput(0), 160, 1, 1, 0, "model.16");
|
|
IElementWiseLayer* conv17 = convBnSilu(network, weightMap, *conv16->getOutput(0), 160, 3, 2, 1, "model.17");
|
|
ITensor* input_tensor_18[] = { conv17->getOutput(0), conv15->getOutput(0) };
|
|
IConcatenationLayer* concat18 = network->addConcatenation(input_tensor_18, 2);
|
|
|
|
//IConcatenationLayer* mp1 = MPC3(network, weightMap, *conv13->getOutput(0), 160, "model.15", "model.16", "model.17");
|
|
|
|
|
|
IElementWiseLayer* conv19 = convBnSilu(network, weightMap, *concat18->getOutput(0), 128, 1, 1, 0, "model.19");
|
|
|
|
IElementWiseLayer* conv20 = convBnSilu(network, weightMap, *concat18->getOutput(0), 128, 1, 1, 0, "model.20");
|
|
IElementWiseLayer* conv21 = convBnSilu(network, weightMap, *conv20->getOutput(0), 128, 3, 1, 1, "model.21");
|
|
IElementWiseLayer* conv22 = convBnSilu(network, weightMap, *conv21->getOutput(0), 128, 3, 1, 1, "model.22");
|
|
IElementWiseLayer* conv23 = convBnSilu(network, weightMap, *conv22->getOutput(0), 128, 3, 1, 1, "model.23");
|
|
IElementWiseLayer* conv24 = convBnSilu(network, weightMap, *conv23->getOutput(0), 128, 3, 1, 1, "model.24");
|
|
IElementWiseLayer* conv25 = convBnSilu(network, weightMap, *conv24->getOutput(0), 128, 3, 1, 1, "model.25");
|
|
IElementWiseLayer* conv26 = convBnSilu(network, weightMap, *conv25->getOutput(0), 128, 3, 1, 1, "model.26");
|
|
|
|
ITensor* input_tensor_27[] = { conv26->getOutput(0), conv24->getOutput(0), conv22->getOutput(0), conv20->getOutput(0),conv19->getOutput(0) };
|
|
IConcatenationLayer* concat27 = network->addConcatenation(input_tensor_27, 5);
|
|
//concat9->setAxis(0);
|
|
IElementWiseLayer* conv28 = convBnSilu(network, weightMap, *concat27->getOutput(0), 640, 1, 1, 0, "model.28");
|
|
|
|
|
|
IPoolingLayer* mp2 = network->addPoolingNd(*conv28->getOutput(0), PoolingType::kMAX, DimsHW{ 2, 2 });
|
|
mp1->setStrideNd(DimsHW{ 2, 2 });
|
|
IElementWiseLayer* conv30 = convBnSilu(network, weightMap, *mp2->getOutput(0), 320, 1, 1, 0, "model.30");
|
|
|
|
IElementWiseLayer* conv31 = convBnSilu(network, weightMap, *conv28->getOutput(0), 320, 1, 1, 0, "model.31");
|
|
IElementWiseLayer* conv32 = convBnSilu(network, weightMap, *conv31->getOutput(0), 320, 3, 2, 1, "model.32");
|
|
ITensor* input_tensor_33[] = { conv32->getOutput(0), conv30->getOutput(0) };
|
|
IConcatenationLayer* concat33 = network->addConcatenation(input_tensor_33, 2);
|
|
//IConcatenationLayer* mp2 = MPC3(network, weightMap, *conv28->getOutput(0), 320, "model.30", "model.31", "model.32");
|
|
|
|
|
|
IElementWiseLayer* conv34 = convBnSilu(network, weightMap, *concat33->getOutput(0), 256, 1, 1, 0, "model.34");
|
|
|
|
IElementWiseLayer* conv35 = convBnSilu(network, weightMap, *concat33->getOutput(0), 256, 1, 1, 0, "model.35");
|
|
IElementWiseLayer* conv36 = convBnSilu(network, weightMap, *conv35->getOutput(0), 256, 3, 1, 1, "model.36");
|
|
IElementWiseLayer* conv37 = convBnSilu(network, weightMap, *conv36->getOutput(0), 256, 3, 1, 1, "model.37");
|
|
IElementWiseLayer* conv38 = convBnSilu(network, weightMap, *conv37->getOutput(0), 256, 3, 1, 1, "model.38");
|
|
IElementWiseLayer* conv39 = convBnSilu(network, weightMap, *conv38->getOutput(0), 256, 3, 1, 1, "model.39");
|
|
IElementWiseLayer* conv40 = convBnSilu(network, weightMap, *conv39->getOutput(0), 256, 3, 1, 1, "model.40");
|
|
IElementWiseLayer* conv41 = convBnSilu(network, weightMap, *conv40->getOutput(0), 256, 3, 1, 1, "model.41");
|
|
|
|
ITensor* input_tensor_42[] = { conv41->getOutput(0), conv39->getOutput(0), conv37->getOutput(0), conv35->getOutput(0),conv34->getOutput(0) };
|
|
IConcatenationLayer* concat42 = network->addConcatenation(input_tensor_42, 5);
|
|
//concat9->setAxis(0);
|
|
IElementWiseLayer* conv43 = convBnSilu(network, weightMap, *concat42->getOutput(0), 1280, 1, 1, 0, "model.43");
|
|
|
|
|
|
IPoolingLayer* mp3 = network->addPoolingNd(*conv43->getOutput(0), PoolingType::kMAX, DimsHW{ 2, 2 });
|
|
mp1->setStrideNd(DimsHW{ 2, 2 });
|
|
IElementWiseLayer* conv45 = convBnSilu(network, weightMap, *mp3->getOutput(0), 640, 1, 1, 0, "model.45");
|
|
|
|
IElementWiseLayer* conv46 = convBnSilu(network, weightMap, *conv43->getOutput(0), 640, 1, 1, 0, "model.46");
|
|
IElementWiseLayer* conv47 = convBnSilu(network, weightMap, *conv46->getOutput(0), 640, 3, 2, 1, "model.47");
|
|
ITensor* input_tensor_48[] = { conv47->getOutput(0), conv45->getOutput(0) };
|
|
IConcatenationLayer* concat48 = network->addConcatenation(input_tensor_48, 2);
|
|
|
|
//IConcatenationLayer* mp3 = MPC3(network, weightMap, *conv43->getOutput(0), 640, "model.45", "model.46", "model.47");
|
|
|
|
|
|
IElementWiseLayer* conv49 = convBnSilu(network, weightMap, *concat48->getOutput(0), 256, 1, 1, 0, "model.49");
|
|
|
|
IElementWiseLayer* conv50 = convBnSilu(network, weightMap, *concat48->getOutput(0), 256, 1, 1, 0, "model.50");
|
|
IElementWiseLayer* conv51 = convBnSilu(network, weightMap, *conv50->getOutput(0), 256, 3, 1, 1, "model.51");
|
|
IElementWiseLayer* conv52 = convBnSilu(network, weightMap, *conv51->getOutput(0), 256, 3, 1, 1, "model.52");
|
|
IElementWiseLayer* conv53 = convBnSilu(network, weightMap, *conv52->getOutput(0), 256, 3, 1, 1, "model.53");
|
|
IElementWiseLayer* conv54 = convBnSilu(network, weightMap, *conv53->getOutput(0), 256, 3, 1, 1, "model.54");
|
|
IElementWiseLayer* conv55 = convBnSilu(network, weightMap, *conv54->getOutput(0), 256, 3, 1, 1, "model.55");
|
|
IElementWiseLayer* conv56 = convBnSilu(network, weightMap, *conv55->getOutput(0), 256, 3, 1, 1, "model.56");
|
|
|
|
ITensor* input_tensor_57[] = { conv56->getOutput(0), conv54->getOutput(0), conv52->getOutput(0), conv50->getOutput(0),conv49->getOutput(0) };
|
|
IConcatenationLayer* concat57 = network->addConcatenation(input_tensor_57, 5);
|
|
//concat9->setAxis(0);
|
|
IElementWiseLayer* conv58 = convBnSilu(network, weightMap, *concat57->getOutput(0), 1280, 1, 1, 0, "model.58");
|
|
|
|
|
|
//-----------------------yolov7 head---------------------------
|
|
//-----SPPCSPC-----------
|
|
IElementWiseLayer* conv59 = SPPCSPC(network, weightMap, *conv58->getOutput(0), 640, "model.59");
|
|
|
|
IElementWiseLayer* conv60 = convBnSilu(network, weightMap, *conv59->getOutput(0), 320, 1, 1, 0, "model.60");
|
|
|
|
|
|
float scale[] = { 1.0, 2.0, 2.0 };
|
|
IResizeLayer* re61 = network->addResize(*conv60->getOutput(0));
|
|
re61->setResizeMode(ResizeMode::kNEAREST);
|
|
re61->setScales(scale, 3);
|
|
|
|
IElementWiseLayer* conv62 = convBnSilu(network, weightMap, *conv43->getOutput(0), 320, 1, 1, 0, "model.62");
|
|
|
|
|
|
ITensor* input_tensor_63[] = { conv62->getOutput(0), re61->getOutput(0) };
|
|
IConcatenationLayer* concat63 = network->addConcatenation(input_tensor_63, 2);
|
|
//concat63->setAxis(0);
|
|
|
|
|
|
IElementWiseLayer* conv64 = convBnSilu(network, weightMap, *concat63->getOutput(0), 256, 1, 1, 0, "model.64");
|
|
|
|
IElementWiseLayer* conv65 = convBnSilu(network, weightMap, *concat63->getOutput(0), 256, 1, 1, 0, "model.65");
|
|
IElementWiseLayer* conv66 = convBnSilu(network, weightMap, *conv65->getOutput(0), 256, 3, 1, 1, "model.66");
|
|
IElementWiseLayer* conv67 = convBnSilu(network, weightMap, *conv66->getOutput(0), 256, 3, 1, 1, "model.67");
|
|
IElementWiseLayer* conv68 = convBnSilu(network, weightMap, *conv67->getOutput(0), 256, 3, 1, 1, "model.68");
|
|
IElementWiseLayer* conv69 = convBnSilu(network, weightMap, *conv68->getOutput(0), 256, 3, 1, 1, "model.69");
|
|
IElementWiseLayer* conv70 = convBnSilu(network, weightMap, *conv69->getOutput(0), 256, 3, 1, 1, "model.70");
|
|
IElementWiseLayer* conv71 = convBnSilu(network, weightMap, *conv70->getOutput(0), 256, 3, 1, 1, "model.71");
|
|
|
|
ITensor* input_tensor_72[] = { conv71->getOutput(0), conv69->getOutput(0), conv67->getOutput(0), conv65->getOutput(0),conv64->getOutput(0) };
|
|
IConcatenationLayer* concat72 = network->addConcatenation(input_tensor_72, 5);
|
|
//concat9->setAxis(0);
|
|
IElementWiseLayer* conv73 = convBnSilu(network, weightMap, *concat72->getOutput(0), 320, 1, 1, 0, "model.73");
|
|
|
|
IElementWiseLayer* conv74 = convBnSilu(network, weightMap, *conv73->getOutput(0), 160, 1, 1, 0, "model.74");
|
|
|
|
IResizeLayer* re75 = network->addResize(*conv74->getOutput(0));
|
|
re75->setResizeMode(ResizeMode::kNEAREST);
|
|
re75->setScales(scale, 3);
|
|
|
|
|
|
IElementWiseLayer* conv76 = convBnSilu(network, weightMap, *conv28->getOutput(0), 160, 1, 1, 0, "model.76");
|
|
|
|
|
|
ITensor* input_tensor_77[] = { conv76->getOutput(0), re75->getOutput(0) };
|
|
IConcatenationLayer* concat77 = network->addConcatenation(input_tensor_77, 2);
|
|
|
|
|
|
|
|
IElementWiseLayer* conv78 = convBnSilu(network, weightMap, *concat77->getOutput(0), 128, 1, 1, 0, "model.78");
|
|
|
|
IElementWiseLayer* conv79 = convBnSilu(network, weightMap, *concat77->getOutput(0), 128, 1, 1, 0, "model.79");
|
|
IElementWiseLayer* conv80 = convBnSilu(network, weightMap, *conv79->getOutput(0), 128, 3, 1, 1, "model.80");
|
|
IElementWiseLayer* conv81 = convBnSilu(network, weightMap, *conv80->getOutput(0), 128, 3, 1, 1, "model.81");
|
|
IElementWiseLayer* conv82 = convBnSilu(network, weightMap, *conv81->getOutput(0), 128, 3, 1, 1, "model.82");
|
|
IElementWiseLayer* conv83 = convBnSilu(network, weightMap, *conv82->getOutput(0), 128, 3, 1, 1, "model.83");
|
|
IElementWiseLayer* conv84 = convBnSilu(network, weightMap, *conv83->getOutput(0), 128, 3, 1, 1, "model.84");
|
|
IElementWiseLayer* conv85 = convBnSilu(network, weightMap, *conv84->getOutput(0), 128, 3, 1, 1, "model.85");
|
|
|
|
|
|
ITensor* input_tensor_86[] = { conv85->getOutput(0), conv83->getOutput(0), conv81->getOutput(0), conv79->getOutput(0),conv78->getOutput(0) };
|
|
IConcatenationLayer* concat86 = network->addConcatenation(input_tensor_86, 5);
|
|
//concat9->setAxis(0);
|
|
IElementWiseLayer* conv87 = convBnSilu(network, weightMap, *concat86->getOutput(0), 160, 1, 1, 0, "model.87");
|
|
|
|
|
|
IPoolingLayer* mp88 = network->addPoolingNd(*conv87->getOutput(0), PoolingType::kMAX, DimsHW{ 2, 2 });
|
|
mp88->setStrideNd(DimsHW{ 2, 2 });
|
|
IElementWiseLayer* conv89 = convBnSilu(network, weightMap, *mp88->getOutput(0), 160, 1, 1, 0, "model.89");
|
|
|
|
IElementWiseLayer* conv90 = convBnSilu(network, weightMap, *conv87->getOutput(0), 160, 1, 1, 0, "model.90");
|
|
IElementWiseLayer* conv91 = convBnSilu(network, weightMap, *conv90->getOutput(0), 160, 3, 2, 1, "model.91");
|
|
|
|
|
|
ITensor* input_tensor_92[] = { conv91->getOutput(0), conv89->getOutput(0),conv73->getOutput(0) };
|
|
IConcatenationLayer* concat92 = network->addConcatenation(input_tensor_92, 3);
|
|
|
|
|
|
IElementWiseLayer* conv93 = convBnSilu(network, weightMap, *concat92->getOutput(0), 256, 1, 1, 0, "model.93");
|
|
|
|
IElementWiseLayer* conv94 = convBnSilu(network, weightMap, *concat92->getOutput(0), 256, 1, 1, 0, "model.94");
|
|
IElementWiseLayer* conv95 = convBnSilu(network, weightMap, *conv94->getOutput(0), 256, 3, 1, 1, "model.95");
|
|
IElementWiseLayer* conv96 = convBnSilu(network, weightMap, *conv95->getOutput(0), 256, 3, 1, 1, "model.96");
|
|
IElementWiseLayer* conv97 = convBnSilu(network, weightMap, *conv96->getOutput(0), 256, 3, 1, 1, "model.97");
|
|
IElementWiseLayer* conv98 = convBnSilu(network, weightMap, *conv97->getOutput(0), 256, 3, 1, 1, "model.98");
|
|
IElementWiseLayer* conv99 = convBnSilu(network, weightMap, *conv98->getOutput(0), 256, 3, 1, 1, "model.99");
|
|
IElementWiseLayer* conv100 = convBnSilu(network, weightMap, *conv99->getOutput(0), 256, 3, 1, 1, "model.100");
|
|
|
|
|
|
ITensor* input_tensor_101[] = { conv100->getOutput(0), conv98->getOutput(0), conv96->getOutput(0), conv94->getOutput(0),conv93->getOutput(0) };
|
|
IConcatenationLayer* concat101 = network->addConcatenation(input_tensor_101, 5);
|
|
//concat9->setAxis(0);
|
|
IElementWiseLayer* conv102 = convBnSilu(network, weightMap, *concat101->getOutput(0), 320, 1, 1, 0, "model.102");
|
|
|
|
IPoolingLayer* mp103 = network->addPoolingNd(*conv102->getOutput(0), PoolingType::kMAX, DimsHW{ 2, 2 });
|
|
mp103->setStrideNd(DimsHW{ 2, 2 });
|
|
IElementWiseLayer* conv104 = convBnSilu(network, weightMap, *mp103->getOutput(0), 320, 1, 1, 0, "model.104");
|
|
|
|
IElementWiseLayer* conv105 = convBnSilu(network, weightMap, *conv102->getOutput(0), 320, 1, 1, 0, "model.105");
|
|
IElementWiseLayer* conv106 = convBnSilu(network, weightMap, *conv105->getOutput(0), 320, 3, 2, 1, "model.106");
|
|
|
|
|
|
ITensor* input_tensor_107[] = { conv106->getOutput(0), conv104->getOutput(0),conv59->getOutput(0) };
|
|
IConcatenationLayer* concat107 = network->addConcatenation(input_tensor_107, 3);
|
|
|
|
|
|
|
|
IElementWiseLayer* conv108 = convBnSilu(network, weightMap, *concat107->getOutput(0), 512, 1, 1, 0, "model.108");
|
|
|
|
IElementWiseLayer* conv109 = convBnSilu(network, weightMap, *concat107->getOutput(0), 512, 1, 1, 0, "model.109");
|
|
IElementWiseLayer* conv110 = convBnSilu(network, weightMap, *conv109->getOutput(0), 512, 3, 1, 1, "model.110");
|
|
IElementWiseLayer* conv111 = convBnSilu(network, weightMap, *conv110->getOutput(0), 512, 3, 1, 1, "model.111");
|
|
IElementWiseLayer* conv112 = convBnSilu(network, weightMap, *conv111->getOutput(0), 512, 3, 1, 1, "model.112");
|
|
IElementWiseLayer* conv113 = convBnSilu(network, weightMap, *conv112->getOutput(0), 512, 3, 1, 1, "model.113");
|
|
IElementWiseLayer* conv114 = convBnSilu(network, weightMap, *conv113->getOutput(0), 512, 3, 1, 1, "model.114");
|
|
IElementWiseLayer* conv115 = convBnSilu(network, weightMap, *conv114->getOutput(0), 512, 3, 1, 1, "model.115");
|
|
|
|
ITensor* input_tensor_116[] = { conv115->getOutput(0), conv113->getOutput(0), conv111->getOutput(0), conv109->getOutput(0),conv108->getOutput(0) };
|
|
IConcatenationLayer* concat116 = network->addConcatenation(input_tensor_116, 5);
|
|
//concat9->setAxis(0);
|
|
IElementWiseLayer* conv117 = convBnSilu(network, weightMap, *concat116->getOutput(0), 640, 1, 1, 0, "model.117");
|
|
|
|
|
|
IElementWiseLayer* con_0 = convBnSilu(network, weightMap, *conv87->getOutput(0), 320, 3, 1, 1, "model.118");
|
|
IElementWiseLayer* con_1 = convBnSilu(network, weightMap, *conv102->getOutput(0), 640, 3, 1, 1, "model.119");
|
|
IElementWiseLayer* con_2 = convBnSilu(network, weightMap, *conv117->getOutput(0), 1280, 3, 1, 1, "model.120");
|
|
|
|
|
|
/*----------------------------------yolov7 out-----------------------------------------*/
|
|
IConvolutionLayer* det0 = network->addConvolutionNd(*con_0->getOutput(0), 3 * (Yolo::CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.121.m.0.weight"], weightMap["model.121.m.0.bias"]);
|
|
assert(det0);
|
|
det0->setName("det0");
|
|
IConvolutionLayer* det1 = network->addConvolutionNd(*con_1->getOutput(0), 3 * (Yolo::CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.121.m.1.weight"], weightMap["model.121.m.1.bias"]);
|
|
assert(det1);
|
|
det1->setName("det1");
|
|
IConvolutionLayer* det2 = network->addConvolutionNd(*con_2->getOutput(0), 3 * (Yolo::CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.121.m.2.weight"], weightMap["model.121.m.2.bias"]);
|
|
assert(det2);
|
|
det2->setName("det2");
|
|
|
|
|
|
auto yolo = addYoLoLayer(network, weightMap, "model.121", std::vector<IConvolutionLayer*>{det0, det1, det2});
|
|
yolo->getOutput(0)->setName(OUTPUT_BLOB_NAME);
|
|
network->markOutput(*yolo->getOutput(0));
|
|
|
|
builder->setMaxBatchSize(maxBatchSize);
|
|
config->setMaxWorkspaceSize(16 * (1 << 20));
|
|
config->setFlag(BuilderFlag::kFP16);
|
|
|
|
std::cout << "Building engine, please wait for a while..." << std::endl;
|
|
ICudaEngine* engine = builder->buildEngineWithConfig(*network, *config);
|
|
std::cout << "Build engine successfully!" << std::endl;
|
|
|
|
// Don't need the network any more
|
|
network->destroy();
|
|
|
|
// Release host memory
|
|
for (auto& mem : weightMap) {
|
|
free((void*)(mem.second.values));
|
|
}
|
|
return engine;
|
|
}
|
|
|
|
ICudaEngine* build_engine_yolov7(unsigned int maxBatchSize,IBuilder* builder, IBuilderConfig* config, DataType dt, const std::string& wts_path) {
|
|
std::map<std::string, Weights> weightMap = loadWeights(wts_path);
|
|
|
|
INetworkDefinition* network = builder->createNetworkV2(0U);
|
|
ITensor* data = network->addInput(INPUT_BLOB_NAME, dt, Dims3{ 3, INPUT_H, INPUT_W });
|
|
assert(data);
|
|
/*----------------------------------yolov7 backbone-----------------------------------------*/
|
|
IElementWiseLayer* conv0 = convBnSilu(network, weightMap, *data, 32, 3, 1, 1, "model.0");
|
|
|
|
IElementWiseLayer* conv1 = convBnSilu(network, weightMap, *conv0->getOutput(0), 64, 3, 2, 1, "model.1");
|
|
IElementWiseLayer* conv2 = convBnSilu(network, weightMap, *conv1->getOutput(0), 64, 3, 1, 1, "model.2");
|
|
|
|
IElementWiseLayer* conv3 = convBnSilu(network, weightMap, *conv2->getOutput(0), 128, 3, 2, 1, "model.3");
|
|
IElementWiseLayer* conv4 = convBnSilu(network, weightMap, *conv3->getOutput(0), 64, 1, 1, 0, "model.4");
|
|
IElementWiseLayer* conv5 = convBnSilu(network, weightMap, *conv3->getOutput(0), 64, 1, 1, 0, "model.5");
|
|
IElementWiseLayer* conv6 = convBnSilu(network, weightMap, *conv5->getOutput(0), 64, 3, 1, 1, "model.6");
|
|
IElementWiseLayer* conv7 = convBnSilu(network, weightMap, *conv6->getOutput(0), 64, 3, 1, 1, "model.7");
|
|
IElementWiseLayer* conv8 = convBnSilu(network, weightMap, *conv7->getOutput(0), 64, 3, 1, 1, "model.8");
|
|
IElementWiseLayer* conv9 = convBnSilu(network, weightMap, *conv8->getOutput(0), 64, 3, 1, 1, "model.9");
|
|
ITensor* input_tensor_10[] = { conv9->getOutput(0), conv7->getOutput(0), conv5->getOutput(0), conv4->getOutput(0) };
|
|
IConcatenationLayer* concat10 = network->addConcatenation(input_tensor_10, 4);
|
|
concat10->setAxis(0);
|
|
IElementWiseLayer* conv11 = convBnSilu(network, weightMap, *concat10->getOutput(0), 256, 1, 1, 0, "model.11");
|
|
|
|
IPoolingLayer* mp12 = network->addPoolingNd(*conv11->getOutput(0), PoolingType::kMAX, DimsHW{ 2, 2 });
|
|
mp12->setStrideNd(DimsHW{ 2, 2 });
|
|
IElementWiseLayer* conv13 = convBnSilu(network, weightMap, *mp12->getOutput(0), 128, 1, 1, 0, "model.13");
|
|
IElementWiseLayer* conv14 = convBnSilu(network, weightMap, *conv11->getOutput(0), 128, 1, 1, 0, "model.14");
|
|
IElementWiseLayer* conv15 = convBnSilu(network, weightMap, *conv14->getOutput(0), 128, 3, 2, 1, "model.15");
|
|
ITensor* input_tensor_16[] = { conv15->getOutput(0), conv13->getOutput(0) };
|
|
IConcatenationLayer* concat16 = network->addConcatenation(input_tensor_16, 2);
|
|
IElementWiseLayer* conv17 = convBnSilu(network, weightMap, *concat16->getOutput(0), 128, 1, 1, 0, "model.17");
|
|
IElementWiseLayer* conv18 = convBnSilu(network, weightMap, *concat16->getOutput(0), 128, 1, 1, 0, "model.18");
|
|
IElementWiseLayer* conv19 = convBnSilu(network, weightMap, *conv18->getOutput(0), 128, 3, 1, 1, "model.19");
|
|
IElementWiseLayer* conv20 = convBnSilu(network, weightMap, *conv19->getOutput(0), 128, 3, 1, 1, "model.20");
|
|
IElementWiseLayer* conv21 = convBnSilu(network, weightMap, *conv20->getOutput(0), 128, 3, 1, 1, "model.21");
|
|
IElementWiseLayer* conv22 = convBnSilu(network, weightMap, *conv21->getOutput(0), 128, 3, 1, 1, "model.22");
|
|
ITensor* input_tensor_23[] = { conv22->getOutput(0), conv20->getOutput(0), conv18->getOutput(0), conv17->getOutput(0) };
|
|
IConcatenationLayer* concat23 = network->addConcatenation(input_tensor_23, 4);
|
|
concat23->setAxis(0);
|
|
IElementWiseLayer* conv24 = convBnSilu(network, weightMap, *concat23->getOutput(0), 512, 1, 1, 0, "model.24");
|
|
|
|
IPoolingLayer* mp25 = network->addPoolingNd(*conv24->getOutput(0), PoolingType::kMAX, DimsHW{ 2, 2 });
|
|
mp25->setStrideNd(DimsHW{ 2, 2 });
|
|
IElementWiseLayer* conv26 = convBnSilu(network, weightMap, *mp25->getOutput(0), 256, 1, 1, 0, "model.26");
|
|
IElementWiseLayer* conv27 = convBnSilu(network, weightMap, *conv24->getOutput(0), 256, 1, 1, 0, "model.27");
|
|
IElementWiseLayer* conv28 = convBnSilu(network, weightMap, *conv27->getOutput(0), 256, 3, 2, 1, "model.28");
|
|
ITensor* input_tensor_29[] = { conv28->getOutput(0), conv26->getOutput(0) };
|
|
IConcatenationLayer* concat29 = network->addConcatenation(input_tensor_29, 2);
|
|
IElementWiseLayer* conv30 = convBnSilu(network, weightMap, *concat29->getOutput(0), 256, 1, 1, 0, "model.30");
|
|
IElementWiseLayer* conv31 = convBnSilu(network, weightMap, *concat29->getOutput(0), 256, 1, 1, 0, "model.31");
|
|
IElementWiseLayer* conv32 = convBnSilu(network, weightMap, *conv31->getOutput(0), 256, 3, 1, 1, "model.32");
|
|
IElementWiseLayer* conv33 = convBnSilu(network, weightMap, *conv32->getOutput(0), 256, 3, 1, 1, "model.33");
|
|
IElementWiseLayer* conv34 = convBnSilu(network, weightMap, *conv33->getOutput(0), 256, 3, 1, 1, "model.34");
|
|
IElementWiseLayer* conv35 = convBnSilu(network, weightMap, *conv34->getOutput(0), 256, 3, 1, 1, "model.35");
|
|
ITensor* input_tensor_36[] = { conv35->getOutput(0), conv33->getOutput(0), conv31->getOutput(0), conv30->getOutput(0) };
|
|
IConcatenationLayer* concat36 = network->addConcatenation(input_tensor_36, 4);
|
|
concat36->setAxis(0);
|
|
IElementWiseLayer* conv37 = convBnSilu(network, weightMap, *concat36->getOutput(0), 1024, 1, 1, 0, "model.37");
|
|
|
|
IPoolingLayer* mp38 = network->addPoolingNd(*conv37->getOutput(0), PoolingType::kMAX, DimsHW{ 2, 2 });
|
|
mp38->setStrideNd(DimsHW{ 2, 2 });
|
|
IElementWiseLayer* conv39 = convBnSilu(network, weightMap, *mp38->getOutput(0), 512, 1, 1, 0, "model.39");
|
|
IElementWiseLayer* conv40 = convBnSilu(network, weightMap, *conv37->getOutput(0), 512, 1, 1, 0, "model.40");
|
|
IElementWiseLayer* conv41 = convBnSilu(network, weightMap, *conv40->getOutput(0), 512, 3, 2, 1, "model.41");
|
|
ITensor* input_tensor_42[] = { conv41->getOutput(0), conv39->getOutput(0) };
|
|
IConcatenationLayer* concat42 = network->addConcatenation(input_tensor_42, 2);
|
|
concat42->setAxis(0);
|
|
IElementWiseLayer* conv43 = convBnSilu(network, weightMap, *concat42->getOutput(0), 256, 1, 1, 0, "model.43");
|
|
IElementWiseLayer* conv44 = convBnSilu(network, weightMap, *concat42->getOutput(0), 256, 1, 1, 0, "model.44");
|
|
IElementWiseLayer* conv45 = convBnSilu(network, weightMap, *conv44->getOutput(0), 256, 3, 1, 1, "model.45");
|
|
IElementWiseLayer* conv46 = convBnSilu(network, weightMap, *conv45->getOutput(0), 256, 3, 1, 1, "model.46");
|
|
IElementWiseLayer* conv47 = convBnSilu(network, weightMap, *conv46->getOutput(0), 256, 3, 1, 1, "model.47");
|
|
IElementWiseLayer* conv48 = convBnSilu(network, weightMap, *conv47->getOutput(0), 256, 3, 1, 1, "model.48");
|
|
ITensor* input_tensor_49[] = { conv48->getOutput(0), conv46->getOutput(0), conv44->getOutput(0), conv43->getOutput(0) };
|
|
IConcatenationLayer* concat49 = network->addConcatenation(input_tensor_49, 4);
|
|
concat49->setAxis(0);
|
|
IElementWiseLayer* conv50 = convBnSilu(network, weightMap, *concat49->getOutput(0), 1024, 1, 1, 0, "model.50");
|
|
|
|
/*----------------------------------yolov7 head-----------------------------------------*/
|
|
IElementWiseLayer* conv51 = SPPCSPC(network, weightMap, *conv50->getOutput(0), 512, "model.51");
|
|
|
|
IElementWiseLayer* conv52 = convBnSilu(network, weightMap, *conv51->getOutput(0), 256, 1, 1, 0, "model.52");
|
|
float scale[] = { 1.0, 2.0, 2.0 };
|
|
IResizeLayer* re53 = network->addResize(*conv52->getOutput(0));
|
|
re53->setResizeMode(ResizeMode::kNEAREST);
|
|
re53->setScales(scale, 3);
|
|
IElementWiseLayer* conv54 = convBnSilu(network, weightMap, *conv37->getOutput(0), 256, 1, 1, 0, "model.54");
|
|
ITensor* input_tensor_55[] = { conv54->getOutput(0), re53->getOutput(0) };
|
|
IConcatenationLayer* concat55 = network->addConcatenation(input_tensor_55, 2);
|
|
concat55->setAxis(0);
|
|
|
|
IElementWiseLayer* conv56 = convBnSilu(network, weightMap, *concat55->getOutput(0), 256, 1, 1, 0, "model.56");
|
|
IElementWiseLayer* conv57 = convBnSilu(network, weightMap, *concat55->getOutput(0), 256, 1, 1, 0, "model.57");
|
|
IElementWiseLayer* conv58 = convBnSilu(network, weightMap, *conv57->getOutput(0), 128, 3, 1, 1, "model.58");
|
|
IElementWiseLayer* conv59 = convBnSilu(network, weightMap, *conv58->getOutput(0), 128, 3, 1, 1, "model.59");
|
|
IElementWiseLayer* conv60 = convBnSilu(network, weightMap, *conv59->getOutput(0), 128, 3, 1, 1, "model.60");
|
|
IElementWiseLayer* conv61 = convBnSilu(network, weightMap, *conv60->getOutput(0), 128, 3, 1, 1, "model.61");
|
|
ITensor* input_tensor_62[] = { conv61->getOutput(0), conv60->getOutput(0), conv59->getOutput(0), conv58->getOutput(0), conv57->getOutput(0), conv56->getOutput(0) };
|
|
IConcatenationLayer* concat62 = network->addConcatenation(input_tensor_62, 6);
|
|
concat62->setAxis(0);
|
|
IElementWiseLayer* conv63 = convBnSilu(network, weightMap, *concat62->getOutput(0), 256, 1, 1, 0, "model.63");
|
|
|
|
IElementWiseLayer* conv64 = convBnSilu(network, weightMap, *conv63->getOutput(0), 128, 1, 1, 0, "model.64");
|
|
IResizeLayer* re65 = network->addResize(*conv64->getOutput(0));
|
|
re65->setResizeMode(ResizeMode::kNEAREST);
|
|
re65->setScales(scale, 3);
|
|
IElementWiseLayer* conv66 = convBnSilu(network, weightMap, *conv24->getOutput(0), 128, 1, 1, 0, "model.66");
|
|
ITensor* input_tensor_67[] = { conv66->getOutput(0), re65->getOutput(0) };
|
|
IConcatenationLayer* concat67 = network->addConcatenation(input_tensor_67, 2);
|
|
concat67->setAxis(0);
|
|
|
|
IElementWiseLayer* conv68 = convBnSilu(network, weightMap, *concat67->getOutput(0), 128, 1, 1, 0, "model.68");
|
|
IElementWiseLayer* conv69 = convBnSilu(network, weightMap, *concat67->getOutput(0), 128, 1, 1, 0, "model.69");
|
|
IElementWiseLayer* conv70 = convBnSilu(network, weightMap, *conv69->getOutput(0), 64, 3, 1, 1, "model.70");
|
|
IElementWiseLayer* conv71 = convBnSilu(network, weightMap, *conv70->getOutput(0), 64, 3, 1, 1, "model.71");
|
|
IElementWiseLayer* conv72 = convBnSilu(network, weightMap, *conv71->getOutput(0), 64, 3, 1, 1, "model.72");
|
|
IElementWiseLayer* conv73 = convBnSilu(network, weightMap, *conv72->getOutput(0), 64, 3, 1, 1, "model.73");
|
|
ITensor* input_tensor_74[] = { conv73->getOutput(0), conv72->getOutput(0), conv71->getOutput(0), conv70->getOutput(0), conv69->getOutput(0), conv68->getOutput(0) };
|
|
IConcatenationLayer* concat74 = network->addConcatenation(input_tensor_74, 6);
|
|
concat74->setAxis(0);
|
|
IElementWiseLayer* conv75 = convBnSilu(network, weightMap, *concat74->getOutput(0), 128, 1, 1, 0, "model.75");
|
|
|
|
IPoolingLayer* mp76 = network->addPoolingNd(*conv75->getOutput(0), PoolingType::kMAX, DimsHW{ 2, 2 });
|
|
mp76->setStrideNd(DimsHW{ 2, 2 });
|
|
IElementWiseLayer* conv77 = convBnSilu(network, weightMap, *mp76->getOutput(0), 128, 1, 1, 0, "model.77");
|
|
IElementWiseLayer* conv78 = convBnSilu(network, weightMap, *conv75->getOutput(0), 128, 1, 1, 0, "model.78");
|
|
IElementWiseLayer* conv79 = convBnSilu(network, weightMap, *conv78->getOutput(0), 128, 3, 2, 1, "model.79");
|
|
ITensor* input_tensor_80[] = { conv79->getOutput(0), conv77->getOutput(0), conv63->getOutput(0) };
|
|
IConcatenationLayer* concat80 = network->addConcatenation(input_tensor_80, 3);
|
|
concat80->setAxis(0);
|
|
|
|
IElementWiseLayer* conv81 = convBnSilu(network, weightMap, *concat80->getOutput(0), 256, 1, 1, 0, "model.81");
|
|
IElementWiseLayer* conv82 = convBnSilu(network, weightMap, *concat80->getOutput(0), 256, 1, 1, 0, "model.82");
|
|
IElementWiseLayer* conv83 = convBnSilu(network, weightMap, *conv82->getOutput(0), 128, 3, 1, 1, "model.83");
|
|
IElementWiseLayer* conv84 = convBnSilu(network, weightMap, *conv83->getOutput(0), 128, 3, 1, 1, "model.84");
|
|
IElementWiseLayer* conv85 = convBnSilu(network, weightMap, *conv84->getOutput(0), 128, 3, 1, 1, "model.85");
|
|
IElementWiseLayer* conv86 = convBnSilu(network, weightMap, *conv85->getOutput(0), 128, 3, 1, 1, "model.86");
|
|
ITensor* input_tensor_87[] = { conv86->getOutput(0), conv85->getOutput(0), conv84->getOutput(0), conv83->getOutput(0), conv82->getOutput(0), conv81->getOutput(0) };
|
|
IConcatenationLayer* concat87 = network->addConcatenation(input_tensor_87, 6);
|
|
concat87->setAxis(0);
|
|
IElementWiseLayer* conv88 = convBnSilu(network, weightMap, *concat87->getOutput(0), 256, 1, 1, 0, "model.88");
|
|
|
|
IPoolingLayer* mp89 = network->addPoolingNd(*conv88->getOutput(0), PoolingType::kMAX, DimsHW{ 2, 2 });
|
|
mp89->setStrideNd(DimsHW{ 2, 2 });
|
|
IElementWiseLayer* conv90 = convBnSilu(network, weightMap, *mp89->getOutput(0), 256, 1, 1, 0, "model.90");
|
|
IElementWiseLayer* conv91 = convBnSilu(network, weightMap, *conv88->getOutput(0), 256, 1, 1, 0, "model.91");
|
|
IElementWiseLayer* conv92 = convBnSilu(network, weightMap, *conv91->getOutput(0), 256, 3, 2, 1, "model.92");
|
|
ITensor* input_tensor_93[] = { conv92->getOutput(0), conv90->getOutput(0), conv51->getOutput(0) };
|
|
IConcatenationLayer* concat93 = network->addConcatenation(input_tensor_93, 3);
|
|
concat93->setAxis(0);
|
|
|
|
IElementWiseLayer* conv94 = convBnSilu(network, weightMap, *concat93->getOutput(0), 512, 1, 1, 0, "model.94");
|
|
IElementWiseLayer* conv95 = convBnSilu(network, weightMap, *concat93->getOutput(0), 512, 1, 1, 0, "model.95");
|
|
IElementWiseLayer* conv96 = convBnSilu(network, weightMap, *conv95->getOutput(0), 256, 3, 1, 1, "model.96");
|
|
IElementWiseLayer* conv97 = convBnSilu(network, weightMap, *conv96->getOutput(0), 256, 3, 1, 1, "model.97");
|
|
IElementWiseLayer* conv98 = convBnSilu(network, weightMap, *conv97->getOutput(0), 256, 3, 1, 1, "model.98");
|
|
IElementWiseLayer* conv99 = convBnSilu(network, weightMap, *conv98->getOutput(0), 256, 3, 1, 1, "model.99");
|
|
ITensor* input_tensor_100[] = { conv99->getOutput(0), conv98->getOutput(0), conv97->getOutput(0), conv96->getOutput(0), conv95->getOutput(0), conv94->getOutput(0) };
|
|
IConcatenationLayer* concat100 = network->addConcatenation(input_tensor_100, 6);
|
|
concat100->setAxis(0);
|
|
IElementWiseLayer* conv101 = convBnSilu(network, weightMap, *concat100->getOutput(0), 512, 1, 1, 0, "model.101");
|
|
|
|
IElementWiseLayer* conv102 = RepConv(network, weightMap, *conv75->getOutput(0), 256, 3, 1, "model.102");
|
|
IElementWiseLayer* conv103 = RepConv(network, weightMap, *conv88->getOutput(0), 512, 3, 1, "model.103");
|
|
IElementWiseLayer* conv104 = RepConv(network, weightMap, *conv101->getOutput(0), 1024, 3, 1, "model.104");
|
|
|
|
/*----------------------------------yolov7 out-----------------------------------------*/
|
|
IConvolutionLayer* cv105_0 = network->addConvolutionNd(*conv102->getOutput(0), 3 * (CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.105.m.0.weight"], weightMap["model.105.m.0.bias"]);
|
|
assert(cv105_0);
|
|
cv105_0->setName("cv105.0");
|
|
IConvolutionLayer* cv105_1 = network->addConvolutionNd(*conv103->getOutput(0), 3 * (CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.105.m.1.weight"], weightMap["model.105.m.1.bias"]);
|
|
assert(cv105_1);
|
|
cv105_1->setName("cv105.1");
|
|
IConvolutionLayer* cv105_2 = network->addConvolutionNd(*conv104->getOutput(0), 3 * (CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.105.m.2.weight"], weightMap["model.105.m.2.bias"]);
|
|
assert(cv105_2);
|
|
cv105_2->setName("cv105.2");
|
|
|
|
auto yolo = addYoLoLayer(network, weightMap, "model.105", std::vector<IConvolutionLayer*>{cv105_0, cv105_1, cv105_2});
|
|
yolo->getOutput(0)->setName(OUTPUT_BLOB_NAME);
|
|
network->markOutput(*yolo->getOutput(0));
|
|
|
|
builder->setMaxBatchSize(maxBatchSize);
|
|
config->setMaxWorkspaceSize(16 * (1 << 20));
|
|
config->setFlag(BuilderFlag::kFP16);
|
|
|
|
std::cout << "Building engine, please wait for a while..." << std::endl;
|
|
ICudaEngine* engine = builder->buildEngineWithConfig(*network, *config);
|
|
std::cout << "Build engine successfully!" << std::endl;
|
|
|
|
// Don't need the network any more
|
|
network->destroy();
|
|
|
|
// Release host memory
|
|
for (auto& mem : weightMap) {
|
|
free((void*)(mem.second.values));
|
|
}
|
|
return engine;
|
|
}
|
|
|
|
ICudaEngine* build_engine_yolov7_tiny(unsigned int maxBatchSize, IBuilder* builder, IBuilderConfig* config, DataType dt, std::string& wts_name) {
|
|
INetworkDefinition* network = builder->createNetworkV2(0U);
|
|
|
|
|
|
ITensor* data = network->addInput(INPUT_BLOB_NAME, dt, Dims3{ 3, INPUT_H, INPUT_W });
|
|
assert(data);
|
|
std::map<std::string, Weights> weightMap = loadWeights(wts_name);
|
|
|
|
|
|
/* ------ yolov7-tiny backbone------ */
|
|
// [32, 3, 2, None, 1, nn.LeakyReLU(0.1)]]---> outch、ksize、stride、padding、groups------
|
|
auto conv0 = convBlockLeakRelu(network, weightMap, *data, 32, 3, 2, 1, "model.0");
|
|
assert(conv0);
|
|
|
|
// [-1, 1, Conv, [64, 3, 2, None, 1, nn.LeakyReLU(0.1)]], # 1-P2/4
|
|
auto conv1 = convBlockLeakRelu(network, weightMap, *conv0->getOutput(0), 64, 3, 2, 1, "model.1");
|
|
assert(conv1);
|
|
|
|
// [-1, 1, Conv, [32, 1, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv2 = convBlockLeakRelu(network, weightMap, *conv1->getOutput(0), 32, 1, 1, 0, "model.2");
|
|
assert(conv2);
|
|
|
|
// [-2, 1, Conv, [32, 1, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv3 = convBlockLeakRelu(network, weightMap, *conv1->getOutput(0), 32, 1, 1, 0, "model.3");
|
|
assert(conv3);
|
|
|
|
// [-1, 1, Conv, [32, 3, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv4 = convBlockLeakRelu(network, weightMap, *conv3->getOutput(0), 32, 3, 1, 1, "model.4");
|
|
assert(conv4);
|
|
|
|
// [-1, 1, Conv, [32, 3, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv5 = convBlockLeakRelu(network, weightMap, *conv4->getOutput(0), 32, 3, 1, 1, "model.5");
|
|
assert(conv5);
|
|
|
|
|
|
ITensor* input_tensor_6[] = { conv5->getOutput(0), conv4->getOutput(0), conv3->getOutput(0), conv2->getOutput(0) };
|
|
auto cat6 = network->addConcatenation(input_tensor_6, 4);
|
|
//cat6->setAxis(0);
|
|
|
|
// [-1, 1, Conv, [64, 1, 1, None, 1, nn.LeakyReLU(0.1)]], # 7
|
|
auto conv7 = convBlockLeakRelu(network, weightMap, *cat6->getOutput(0), 64, 1, 1, 0, "model.7");
|
|
assert(conv7);
|
|
|
|
|
|
auto* pool8 = network->addPoolingNd(*conv7->getOutput(0), PoolingType::kMAX, DimsHW{ 2, 2 });
|
|
assert(pool8);
|
|
pool8->setStrideNd(DimsHW{ 2, 2 });
|
|
|
|
|
|
//[-1, 1, Conv, [64, 1, 1, None, 1, nn.LeakyReLU(0.1)]] ,
|
|
auto conv9 = convBlockLeakRelu(network, weightMap, *pool8->getOutput(0), 64, 1, 1, 0, "model.9");
|
|
assert(conv9);
|
|
|
|
// [-2, 1, Conv, [64, 1, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv10 = convBlockLeakRelu(network, weightMap, *pool8->getOutput(0), 64, 1, 1, 0, "model.10");
|
|
assert(conv10);
|
|
//[-1, 1, Conv, [64, 3, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv11 = convBlockLeakRelu(network, weightMap, *conv10->getOutput(0), 64, 3, 1, 1, "model.11");
|
|
assert(conv11);
|
|
//[-1, 1, Conv, [64, 3, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv12 = convBlockLeakRelu(network, weightMap, *conv11->getOutput(0), 64, 3, 1, 1, "model.12");
|
|
assert(conv12);
|
|
|
|
ITensor* input_tensor_13[] = { conv12->getOutput(0), conv11->getOutput(0), conv10->getOutput(0), conv9->getOutput(0) };
|
|
auto cat13 = network->addConcatenation(input_tensor_13, 4);
|
|
//cat2->setAxis(0);
|
|
|
|
// [-1, 1, Conv, [128, 1, 1, None, 1, nn.LeakyReLU(0.1)]], # 14
|
|
auto conv14 = convBlockLeakRelu(network, weightMap, *cat13->getOutput(0), 128, 1, 1, 0, "model.14");
|
|
assert(conv14);
|
|
|
|
|
|
auto* pool15 = network->addPoolingNd(*conv14->getOutput(0), PoolingType::kMAX, DimsHW{ 2, 2 });
|
|
assert(pool15);
|
|
pool15->setStrideNd(DimsHW{ 2, 2 });
|
|
|
|
|
|
|
|
|
|
|
|
// [-1, 1, Conv, [128, 1, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv16 = convBlockLeakRelu(network, weightMap, *pool15->getOutput(0), 128, 1, 1, 0, "model.16");
|
|
assert(conv16);
|
|
//[-2, 1, Conv, [128, 1, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv17 = convBlockLeakRelu(network, weightMap, *pool15->getOutput(0), 128, 1, 1, 0, "model.17");
|
|
assert(conv17);
|
|
//[-1, 1, Conv, [128, 3, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv18 = convBlockLeakRelu(network, weightMap, *conv17->getOutput(0), 128, 3, 1, 1, "model.18");
|
|
assert(conv18);
|
|
// [-1, 1, Conv, [128, 3, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv19 = convBlockLeakRelu(network, weightMap, *conv18->getOutput(0), 128, 3, 1, 1, "model.19");
|
|
assert(conv19);
|
|
|
|
ITensor* input_tensor_20[] = { conv19->getOutput(0), conv18->getOutput(0), conv17->getOutput(0), conv16->getOutput(0) };
|
|
auto cat20 = network->addConcatenation(input_tensor_20, 4);
|
|
//cat20->setAxis(0);
|
|
//[-1, 1, Conv, [256, 1, 1, None, 1, nn.LeakyReLU(0.1)]], # 21
|
|
auto conv21 = convBlockLeakRelu(network, weightMap, *cat20->getOutput(0), 256, 1, 1, 0, "model.21");
|
|
assert(conv21);
|
|
|
|
|
|
auto* pool22 = network->addPoolingNd(*conv21->getOutput(0), PoolingType::kMAX, DimsHW{ 2, 2 });
|
|
assert(pool22);
|
|
pool22->setStrideNd(DimsHW{ 2, 2 });
|
|
|
|
|
|
|
|
// [-1, 1, Conv, [256, 1, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv23 = convBlockLeakRelu(network, weightMap, *pool22->getOutput(0), 256, 1, 1, 0, "model.23");
|
|
assert(conv23);
|
|
|
|
// [-2, 1, Conv, [256, 1, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv24 = convBlockLeakRelu(network, weightMap, *pool22->getOutput(0), 256, 1, 1, 0, "model.24");
|
|
assert(conv24);
|
|
|
|
// [-1, 1, Conv, [256, 3, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv25 = convBlockLeakRelu(network, weightMap, *conv24->getOutput(0), 256, 3, 1, 1, "model.25");
|
|
assert(conv25);
|
|
|
|
// [-1, 1, Conv, [256, 3, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv26 = convBlockLeakRelu(network, weightMap, *conv25->getOutput(0), 256, 3, 1, 1, "model.26");
|
|
assert(conv26);
|
|
|
|
|
|
ITensor* input_tensor_27[] = { conv26->getOutput(0), conv25->getOutput(0), conv24->getOutput(0), conv23->getOutput(0) };
|
|
auto cat27 = network->addConcatenation(input_tensor_27, 4);
|
|
//cat27->setAxis(0);
|
|
|
|
// [-1, 1, Conv, [512, 1, 1, None, 1, nn.LeakyReLU(0.1)]], # 28
|
|
auto conv28 = convBlockLeakRelu(network, weightMap, *cat27->getOutput(0), 512, 1, 1, 0, "model.28");
|
|
assert(conv28);
|
|
|
|
/*===============================yolov7-tiny head======================================*/
|
|
|
|
// [-1, 1, Conv, [256, 1, 1, None, 1, nn.LeakyReLU(0.1)]]
|
|
auto conv29 = convBlockLeakRelu(network, weightMap, *conv28->getOutput(0), 256, 1, 1, 0, "model.29");
|
|
assert(conv29);
|
|
|
|
// [-2, 1, Conv, [256, 1, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv30 = convBlockLeakRelu(network, weightMap, *conv28->getOutput(0), 256, 1, 1, 0, "model.30");
|
|
assert(conv30);
|
|
|
|
//[-1, 1, SP, [5]],
|
|
auto* pool31 = network->addPoolingNd(*conv30->getOutput(0), PoolingType::kMAX, DimsHW{ 5, 5 });
|
|
assert(pool31);
|
|
pool31->setStrideNd(DimsHW{ 1, 1 });
|
|
pool31->setPaddingNd(DimsHW{2,2});
|
|
// [-2, 1, SP, [9]],
|
|
auto* pool32 = network->addPoolingNd(*conv30->getOutput(0), PoolingType::kMAX, DimsHW{ 9, 9 });
|
|
assert(pool32);
|
|
pool32->setStrideNd(DimsHW{ 1, 1 });
|
|
pool32->setPaddingNd(DimsHW{ 4, 4 });
|
|
|
|
// [-3, 1, SP, [13]],
|
|
auto* pool33 = network->addPoolingNd(*conv30->getOutput(0), PoolingType::kMAX, DimsHW{ 13, 13 });
|
|
assert(pool33);
|
|
pool33->setStrideNd(DimsHW{ 1, 1 });
|
|
pool33->setPaddingNd(DimsHW{ 6, 6 });
|
|
|
|
|
|
|
|
ITensor* input_tensor_34[] = { pool33->getOutput(0), pool32->getOutput(0), pool31->getOutput(0), conv30->getOutput(0) };
|
|
auto cat34 = network->addConcatenation(input_tensor_34, 4);
|
|
//cat34->setAxis(0);
|
|
|
|
// [-1, 1, Conv, [256, 1, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv35 = convBlockLeakRelu(network, weightMap, *cat34->getOutput(0), 256, 1, 1, 0, "model.35");
|
|
assert(conv35);
|
|
|
|
|
|
|
|
|
|
|
|
ITensor* input_tensor_36[] = { conv35->getOutput(0), conv29->getOutput(0) };
|
|
auto cat36 = network->addConcatenation(input_tensor_36, 2);
|
|
//cat36->setAxis(0);
|
|
|
|
// [-1, 1, Conv, [256, 1, 1, None, 1, nn.LeakyReLU(0.1)]], # 37
|
|
auto conv37 = convBlockLeakRelu(network, weightMap, *cat36->getOutput(0), 256, 1, 1, 0, "model.37");
|
|
assert(conv37);
|
|
|
|
// [-1, 1, Conv, [128, 1, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv38 = convBlockLeakRelu(network, weightMap, *conv37->getOutput(0), 128, 1, 1, 0, "model.38");
|
|
assert(conv38);
|
|
|
|
|
|
float scale[] = { 1.0, 2.0, 2.0 };
|
|
IResizeLayer* resize39 = network->addResize(*conv38->getOutput(0));
|
|
resize39->setResizeMode(ResizeMode::kNEAREST);
|
|
resize39->setScales(scale, 3);
|
|
|
|
// [21, 1, Conv, [128, 1, 1, None, 1, nn.LeakyReLU(0.1)]], # route backbone P4 ---->conv16
|
|
auto conv40 = convBlockLeakRelu(network, weightMap, *conv21->getOutput(0), 128, 1, 1, 0, "model.40");
|
|
assert(conv40);
|
|
|
|
|
|
|
|
ITensor* input_tensor_41[] = { conv40->getOutput(0), resize39->getOutput(0) };
|
|
auto cat41 = network->addConcatenation(input_tensor_41, 2);
|
|
//cat41->setAxis(0);
|
|
|
|
|
|
|
|
// [-1, 1, Conv, [64, 1, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv42 = convBlockLeakRelu(network, weightMap, *cat41->getOutput(0), 64, 1, 1, 0, "model.42");
|
|
assert(conv42);
|
|
|
|
//[-2, 1, Conv, [64, 1, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv43 = convBlockLeakRelu(network, weightMap, *cat41->getOutput(0), 64, 1, 1, 0, "model.43");
|
|
assert(conv43);
|
|
|
|
// [-1, 1, Conv, [64, 3, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv44 = convBlockLeakRelu(network, weightMap, *conv43->getOutput(0), 64, 3, 1, 1, "model.44");
|
|
assert(conv44);
|
|
|
|
// [-1, 1, Conv, [64, 3, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv45 = convBlockLeakRelu(network, weightMap, *conv44->getOutput(0), 64, 3, 1, 1, "model.45");
|
|
assert(conv45);
|
|
|
|
|
|
ITensor* input_tensor_46[] = { conv45->getOutput(0), conv44->getOutput(0), conv43->getOutput(0), conv42->getOutput(0) };
|
|
auto cat46 = network->addConcatenation(input_tensor_46, 4);
|
|
//cat46->setAxis(0);
|
|
|
|
// [-1, 1, Conv, [128, 1, 1, None, 1, nn.LeakyReLU(0.1)]], # 47
|
|
auto conv47 = convBlockLeakRelu(network, weightMap, *cat46->getOutput(0), 128, 1, 1, 0, "model.47");
|
|
assert(conv47);
|
|
|
|
// [-1, 1, Conv, [64, 1, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv48 = convBlockLeakRelu(network, weightMap, *conv47->getOutput(0), 64, 1, 1, 0, "model.48");
|
|
assert(conv48);
|
|
|
|
|
|
|
|
IResizeLayer* resize49 = network->addResize(*conv48->getOutput(0));
|
|
resize49->setResizeMode(ResizeMode::kNEAREST);
|
|
resize49->setScales(scale, 3);
|
|
|
|
// [14, 1, Conv, [64, 1, 1, None, 1, nn.LeakyReLU(0.1)]], # route backbone P3 conv11
|
|
auto conv50 = convBlockLeakRelu(network, weightMap, *conv14->getOutput(0), 64, 1, 1, 0, "model.50");
|
|
assert(conv50);
|
|
|
|
|
|
|
|
ITensor* input_tensor_51[] = { conv50->getOutput(0), resize49->getOutput(0) };
|
|
IConcatenationLayer* cat51 = network->addConcatenation(input_tensor_51, 2);
|
|
//cat51->setAxis(0);
|
|
|
|
|
|
// [-1, 1, Conv, [32, 1, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv52 = convBlockLeakRelu(network, weightMap, *cat51->getOutput(0), 32, 1, 1, 0, "model.52");
|
|
assert(conv52);
|
|
// [-2, 1, Conv, [32, 1, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv53 = convBlockLeakRelu(network, weightMap, *cat51->getOutput(0), 32, 1, 1, 0, "model.53");
|
|
assert(conv53);
|
|
|
|
// [-1, 1, Conv, [32, 3, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv54 = convBlockLeakRelu(network, weightMap, *conv53->getOutput(0), 32, 3, 1, 1, "model.54");
|
|
assert(conv54);
|
|
// [-1, 1, Conv, [32, 3, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv55 = convBlockLeakRelu(network, weightMap, *conv54->getOutput(0), 32, 3, 1, 1, "model.55");
|
|
assert(conv55);
|
|
|
|
|
|
ITensor* input_tensor_56[] = { conv55->getOutput(0), conv54->getOutput(0), conv53->getOutput(0),conv52->getOutput(0) };
|
|
IConcatenationLayer* cat56 = network->addConcatenation(input_tensor_56, 4);
|
|
//cat56->setAxis(0);
|
|
|
|
// [-1, 1, Conv, [64, 1, 1, None, 1, nn.LeakyReLU(0.1)]], # 57
|
|
auto conv57 = convBlockLeakRelu(network, weightMap, *cat56->getOutput(0), 64, 1, 1, 0, "model.57");
|
|
assert(conv57);
|
|
|
|
// [-1, 1, Conv, [128, 3, 2, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv58 = convBlockLeakRelu(network, weightMap, *conv57->getOutput(0), 128, 3, 2, 1, "model.58");
|
|
assert(conv58);
|
|
|
|
// conv32 [[-1, 47], 1, Concat, [1]],
|
|
|
|
|
|
ITensor* input_tensor_59[] = { conv58->getOutput(0), conv47->getOutput(0) };
|
|
IConcatenationLayer* cat59 = network->addConcatenation(input_tensor_59, 2);
|
|
//cat59->setAxis(0);
|
|
|
|
|
|
// [-1, 1, Conv, [64, 1, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv60 = convBlockLeakRelu(network, weightMap, *cat59->getOutput(0), 64, 1, 1, 0, "model.60");
|
|
assert(conv60);
|
|
// [-2, 1, Conv, [64, 1, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv61 = convBlockLeakRelu(network, weightMap, *cat59->getOutput(0), 64, 1, 1, 0, "model.61");
|
|
assert(conv61);
|
|
|
|
// [-1, 1, Conv, [64, 3, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv62 = convBlockLeakRelu(network, weightMap, *conv61->getOutput(0), 64, 3, 1, 1, "model.62");
|
|
assert(conv62);
|
|
// [-1, 1, Conv, [64, 3, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv63 = convBlockLeakRelu(network, weightMap, *conv62->getOutput(0), 64, 3, 1, 1, "model.63");
|
|
assert(conv63);
|
|
|
|
|
|
ITensor* input_tensor_64[] = { conv63->getOutput(0), conv62->getOutput(0), conv61->getOutput(0), conv60->getOutput(0) };
|
|
IConcatenationLayer* cat64 = network->addConcatenation(input_tensor_64, 4);
|
|
//cat64->setAxis(0);
|
|
|
|
// [-1, 1, Conv, [128, 1, 1, None, 1, nn.LeakyReLU(0.1)]] , # 65
|
|
auto conv65 = convBlockLeakRelu(network, weightMap, *cat64->getOutput(0), 128, 1, 1, 0, "model.65");
|
|
assert(conv65);
|
|
|
|
|
|
//[-1, 1, Conv, [256, 3, 2, None, 1, nn.LeakyReLU(0.1)]] ,
|
|
auto conv66 = convBlockLeakRelu(network, weightMap, *conv65->getOutput(0), 256, 3, 2, 1, "model.66");
|
|
assert(conv66);
|
|
|
|
|
|
ITensor* input_tensor_67[] = { conv66->getOutput(0), conv37->getOutput(0) };
|
|
IConcatenationLayer* cat67 = network->addConcatenation(input_tensor_67, 2);
|
|
//cat67->setAxis(0);
|
|
|
|
// [-1, 1, Conv, [128, 1, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv68 = convBlockLeakRelu(network, weightMap, *cat67->getOutput(0), 128, 1, 1, 0, "model.68");
|
|
assert(conv68);
|
|
// [-2, 1, Conv, [128, 1, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv69 = convBlockLeakRelu(network, weightMap, *cat67->getOutput(0), 128, 1, 1, 0, "model.69");
|
|
assert(conv69);
|
|
|
|
// [-1, 1, Conv, [128, 3, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv70 = convBlockLeakRelu(network, weightMap, *conv69->getOutput(0), 128, 3, 1, 1, "model.70");
|
|
assert(conv70);
|
|
// [-1, 1, Conv, [128, 3, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv71 = convBlockLeakRelu(network, weightMap, *conv70->getOutput(0), 128, 3, 1, 1, "model.71");
|
|
assert(conv71);
|
|
|
|
|
|
ITensor* input_tensor_72[] = { conv71->getOutput(0), conv70->getOutput(0), conv69->getOutput(0), conv68->getOutput(0) };
|
|
IConcatenationLayer* cat72 = network->addConcatenation(input_tensor_72, 4);
|
|
//cat72->setAxis(0);
|
|
|
|
// [-1, 1, Conv, [256, 1, 1, None, 1, nn.LeakyReLU(0.1)]], # 73
|
|
auto conv73 = convBlockLeakRelu(network, weightMap, *cat72->getOutput(0), 256, 1, 1, 0, "model.73");
|
|
assert(conv73);
|
|
|
|
|
|
// [57, 1, Conv, [128, 3, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv74 = convBlockLeakRelu(network, weightMap, *conv57->getOutput(0), 128, 3, 1, 1, "model.74");
|
|
assert(conv74);
|
|
// [65, 1, Conv, [256, 3, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv75 = convBlockLeakRelu(network, weightMap, *conv65->getOutput(0), 256, 3, 1, 1, "model.75");
|
|
assert(conv75);
|
|
// [73, 1, Conv, [512, 3, 1, None, 1, nn.LeakyReLU(0.1)]],
|
|
auto conv76 = convBlockLeakRelu(network, weightMap, *conv73->getOutput(0), 512, 3, 1, 1, "model.76");
|
|
assert(conv76);
|
|
|
|
/*--------------------detect--------------*/
|
|
/* ------ detect ------ */
|
|
IConvolutionLayer* det0 = network->addConvolutionNd(*conv74->getOutput(0), 3 * (Yolo::CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.77.m.0.weight"], weightMap["model.77.m.0.bias"]);
|
|
|
|
IConvolutionLayer* det1 = network->addConvolutionNd(*conv75->getOutput(0), 3 * (Yolo::CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.77.m.1.weight"], weightMap["model.77.m.1.bias"]);
|
|
|
|
IConvolutionLayer* det2 = network->addConvolutionNd(*conv76->getOutput(0), 3 * (Yolo::CLASS_NUM + 5), DimsHW{ 1, 1 }, weightMap["model.77.m.2.weight"], weightMap["model.77.m.2.bias"]);
|
|
|
|
|
|
auto yolo = addYoLoLayer(network, weightMap, "model.77", std::vector<IConvolutionLayer*>{det0, det1, det2});
|
|
yolo->getOutput(0)->setName(OUTPUT_BLOB_NAME);
|
|
network->markOutput(*yolo->getOutput(0));
|
|
// Build engine
|
|
builder->setMaxBatchSize(maxBatchSize);
|
|
config->setMaxWorkspaceSize(16 * (1 << 20)); // 16MB
|
|
#if defined(USE_FP16)
|
|
config->setFlag(BuilderFlag::kFP16);
|
|
#elif defined(USE_INT8)
|
|
std::cout << "Your platform support int8: " << (builder->platformHasFastInt8() ? "true" : "false") << std::endl;
|
|
assert(builder->platformHasFastInt8());
|
|
config->setFlag(BuilderFlag::kINT8);
|
|
Int8EntropyCalibrator2* calibrator = new Int8EntropyCalibrator2(1, INPUT_W, INPUT_H, "./coco_calib/", "int8calib.table", INPUT_BLOB_NAME);
|
|
config->setInt8Calibrator(calibrator);
|
|
#endif
|
|
|
|
std::cout << "Building engine, please wait for a while..." << std::endl;
|
|
ICudaEngine* engine = builder->buildEngineWithConfig(*network, *config);
|
|
std::cout << "Build engine successfully!" << std::endl;
|
|
|
|
// Don't need the network any more
|
|
network->destroy();
|
|
|
|
// Release host memory
|
|
for (auto& mem : weightMap) {
|
|
free((void*)(mem.second.values));
|
|
}
|
|
return engine;
|
|
}
|
|
|
|
void APIToModel(unsigned int maxBatchSize, IHostMemory** modelStream,std::string& wts_name,std::string &model_check) {
|
|
// Create builder
|
|
IBuilder* builder = createInferBuilder(gLogger);
|
|
IBuilderConfig* config = builder->createBuilderConfig();
|
|
// Create model to populate the network, then set the outputs and create an engine
|
|
ICudaEngine* engine = nullptr;
|
|
|
|
|
|
if (model_check == "yolov7-tiny") {
|
|
engine = build_engine_yolov7_tiny(maxBatchSize, builder, config, DataType::kFLOAT, wts_name);
|
|
} else if (model_check == "yolov7") {
|
|
engine = build_engine_yolov7(maxBatchSize, builder, config, DataType::kFLOAT, wts_name);
|
|
} else if (model_check == "yolov7x") {
|
|
engine = build_engine_yolov7x(maxBatchSize, builder, config, DataType::kFLOAT, wts_name);
|
|
} else if (model_check == "yolov7w6") {
|
|
engine = build_engine_yolov7w6(maxBatchSize, builder, config, DataType::kFLOAT, wts_name);
|
|
} else if (model_check == "yolov7e6") {
|
|
engine = build_engine_yolov7e6(maxBatchSize, builder, config, DataType::kFLOAT, wts_name);
|
|
} else if (model_check == "yolov7d6") {
|
|
engine = build_engine_yolov7d6(maxBatchSize, builder, config, DataType::kFLOAT, wts_name);
|
|
} else if (model_check == "yolov7e6e") {
|
|
engine = build_engine_yolov7e6e(maxBatchSize, builder, config, DataType::kFLOAT, wts_name);
|
|
}
|
|
assert(engine != nullptr);
|
|
|
|
// Serialize the engine
|
|
(*modelStream) = engine->serialize();
|
|
|
|
// Close everything down
|
|
engine->destroy();
|
|
builder->destroy();
|
|
config->destroy();
|
|
}
|
|
|
|
void doInference(IExecutionContext& context, cudaStream_t& stream, void** buffers, float* output, int batchSize) {
|
|
// infer on the batch asynchronously, and DMA output back to host
|
|
context.enqueue(batchSize, buffers, stream, nullptr);
|
|
CUDA_CHECK(cudaMemcpyAsync(output, buffers[1], batchSize * OUTPUT_SIZE * sizeof(float), cudaMemcpyDeviceToHost, stream));
|
|
cudaStreamSynchronize(stream);
|
|
}
|
|
|
|
bool parse_args(int argc, char** argv, std::string& wts, std::string& engine, float& gd, float& gw, std::string& img_dir,std::string& model_check) {
|
|
if (argc < 4) return false;
|
|
if (std::string(argv[1]) == "-s" && (argc == 5 || argc == 7)) {
|
|
wts = std::string(argv[2]);
|
|
engine = std::string(argv[3]);
|
|
auto net = std::string(argv[4]);
|
|
|
|
if (net.size() == 1 && net[0] == 't' ) {
|
|
model_check = "yolov7-tiny";
|
|
gd = 1.0;
|
|
gw = 1.0;
|
|
}
|
|
|
|
if (net.size() == 2 && net[0] == 'v' && net[1]=='7') {
|
|
model_check ="yolov7";
|
|
gd = 5.0;
|
|
gw = 1.0;
|
|
}
|
|
|
|
if (net.size() == 1 && net[0] == 'x' ) {
|
|
model_check = "yolov7x";
|
|
gd = 1.0;
|
|
gw = 1.0;
|
|
}
|
|
|
|
if (net.size() == 2 && net[0] == 'w' && net[1]=='6') {
|
|
model_check = "yolov7w6";
|
|
gd = 1.0;
|
|
gw = 1.0;
|
|
}
|
|
if (net.size() == 2 && net[0] == 'e' && net[1]=='6') {
|
|
model_check ="yolov7e6";
|
|
gd = 1.0;
|
|
gw = 1.0;
|
|
}
|
|
if (net.size() == 2 && net[0] == 'd' && net[1]=='6') {
|
|
model_check ="yolov7d6";
|
|
gd = 1.0;
|
|
gw = 1.0;
|
|
}
|
|
if (net.size() == 3 && net[0] == 'e' && net[1]=='6' && net[2]=='e' ) {
|
|
model_check = "yolov7e6e";
|
|
gd = 1.0;
|
|
gw = 1.0;
|
|
|
|
}
|
|
} else if (std::string(argv[1]) == "-d" && argc == 4) {
|
|
engine = std::string(argv[2]);
|
|
img_dir = std::string(argv[3]);
|
|
|
|
} else {
|
|
return false;
|
|
}
|
|
return true;
|
|
}
|
|
|
|
int main(int argc, char** argv) {
|
|
cudaSetDevice(DEVICE);
|
|
|
|
std::string wts_name = "";
|
|
std::string engine_name = "";
|
|
bool is_p6 = false;
|
|
float gd = 0.0f, gw = 0.0f;
|
|
std::string img_dir;
|
|
std::string model_check="";
|
|
|
|
if (!parse_args(argc, argv, wts_name, engine_name, gd, gw, img_dir,model_check)) {
|
|
std::cerr << "arguments not right!" << std::endl;
|
|
std::cerr << "./yolov7 -s [.wts] [.engine] [t/v7/x/w6/e6/d6/e6e gd gw] // serialize model to plan file" << std::endl;
|
|
std::cerr << "./yolov7 -d [.engine] ../samples // deserialize plan file and run inference" << std::endl;
|
|
return -1;
|
|
}
|
|
|
|
// create a model using the API directly and serialize it to a stream
|
|
if (!wts_name.empty()) {
|
|
IHostMemory* modelStream{ nullptr };
|
|
|
|
APIToModel(BATCH_SIZE, &modelStream, wts_name, model_check);
|
|
assert(modelStream != nullptr);
|
|
std::ofstream p(engine_name, std::ios::binary);
|
|
if (!p) {
|
|
std::cerr << "could not open plan output file" << std::endl;
|
|
return -1;
|
|
}
|
|
p.write(reinterpret_cast<const char*>(modelStream->data()), modelStream->size());
|
|
modelStream->destroy();
|
|
return 0;
|
|
}
|
|
|
|
// deserialize the .engine and run inference
|
|
std::ifstream file(engine_name, std::ios::binary);
|
|
if (!file.good()) {
|
|
std::cerr << "read " << engine_name << " error!" << std::endl;
|
|
return -1;
|
|
}
|
|
char* trtModelStream = nullptr;
|
|
size_t size = 0;
|
|
file.seekg(0, file.end);
|
|
size = file.tellg();
|
|
file.seekg(0, file.beg);
|
|
trtModelStream = new char[size];
|
|
assert(trtModelStream);
|
|
file.read(trtModelStream, size);
|
|
file.close();
|
|
|
|
std::vector<std::string> file_names;
|
|
if (read_files_in_dir(img_dir.c_str(), file_names) < 0) {
|
|
std::cerr << "read_files_in_dir failed." << std::endl;
|
|
return -1;
|
|
}
|
|
|
|
static float prob[BATCH_SIZE * OUTPUT_SIZE];
|
|
IRuntime* runtime = createInferRuntime(gLogger);
|
|
assert(runtime != nullptr);
|
|
ICudaEngine* engine = runtime->deserializeCudaEngine(trtModelStream, size);
|
|
assert(engine != nullptr);
|
|
IExecutionContext* context = engine->createExecutionContext();
|
|
assert(context != nullptr);
|
|
delete[] trtModelStream;
|
|
assert(engine->getNbBindings() == 2);
|
|
float* buffers[2];
|
|
// In order to bind the buffers, we need to know the names of the input and output tensors.
|
|
// Note that indices are guaranteed to be less than IEngine::getNbBindings()
|
|
const int inputIndex = engine->getBindingIndex(INPUT_BLOB_NAME);
|
|
const int outputIndex = engine->getBindingIndex(OUTPUT_BLOB_NAME);
|
|
assert(inputIndex == 0);
|
|
assert(outputIndex == 1);
|
|
// Create GPU buffers on device
|
|
CUDA_CHECK(cudaMalloc((void**)&buffers[inputIndex], BATCH_SIZE * 3 * INPUT_H * INPUT_W * sizeof(float)));
|
|
CUDA_CHECK(cudaMalloc((void**)&buffers[outputIndex], BATCH_SIZE * OUTPUT_SIZE * sizeof(float)));
|
|
|
|
// Create stream
|
|
cudaStream_t stream;
|
|
CUDA_CHECK(cudaStreamCreate(&stream));
|
|
uint8_t *img_host = nullptr;
|
|
uint8_t *img_device = nullptr;
|
|
// prepare input data cache in pinned memory
|
|
CUDA_CHECK(cudaMallocHost((void**)&img_host, MAX_IMAGE_INPUT_SIZE_THRESH * 3));
|
|
// prepare input data cache in device memory
|
|
CUDA_CHECK(cudaMalloc((void**)&img_device, MAX_IMAGE_INPUT_SIZE_THRESH * 3));
|
|
int fcount = 0;
|
|
std::vector<cv::Mat> imgs_buffer(BATCH_SIZE);
|
|
for (int f = 0; f < (int)file_names.size(); f++) {
|
|
fcount++;
|
|
if (fcount < BATCH_SIZE && f + 1 != (int)file_names.size()) continue;
|
|
//auto start = std::chrono::system_clock::now();
|
|
float* buffer_idx = (float*)buffers[inputIndex];
|
|
for (int b = 0; b < fcount; b++) {
|
|
cv::Mat img = cv::imread(img_dir + "/" + file_names[f - fcount + 1 + b]);
|
|
if (img.empty()) continue;
|
|
imgs_buffer[b] = img;
|
|
size_t size_image = img.cols * img.rows * 3;
|
|
size_t size_image_dst = INPUT_H * INPUT_W * 3;
|
|
//copy data to pinned memory
|
|
memcpy(img_host, img.data, size_image);
|
|
//copy data to device memory
|
|
CUDA_CHECK(cudaMemcpyAsync(img_device, img_host, size_image, cudaMemcpyHostToDevice, stream));
|
|
preprocess_kernel_img(img_device, img.cols, img.rows, buffer_idx, INPUT_W, INPUT_H, stream);
|
|
buffer_idx += size_image_dst;
|
|
}
|
|
// Run inference
|
|
auto start = std::chrono::system_clock::now();
|
|
doInference(*context, stream, (void**)buffers, prob, BATCH_SIZE);
|
|
auto end = std::chrono::system_clock::now();
|
|
std::cout << "inference time: " << std::chrono::duration_cast<std::chrono::milliseconds>(end - start).count() << "ms" << std::endl;
|
|
std::vector<std::vector<Yolo::Detection>> batch_res(fcount);
|
|
for (int b = 0; b < fcount; b++) {
|
|
auto& res = batch_res[b];
|
|
nms(res, &prob[b * OUTPUT_SIZE], CONF_THRESH, NMS_THRESH);
|
|
}
|
|
for (int b = 0; b < fcount; b++) {
|
|
auto& res = batch_res[b];
|
|
cv::Mat img = imgs_buffer[b];
|
|
for (size_t j = 0; j < res.size(); j++) {
|
|
cv::Rect r = get_rect(img, res[j].bbox);
|
|
cv::rectangle(img, r, cv::Scalar(0x27, 0xC1, 0x36), 2);
|
|
cv::putText(img, std::to_string((int)res[j].class_id), cv::Point(r.x, r.y - 1), cv::FONT_HERSHEY_PLAIN, 1.2, cv::Scalar(0xFF, 0xFF, 0xFF), 2);
|
|
}
|
|
cv::imwrite("__" + file_names[f - fcount + 1 + b], img);
|
|
}
|
|
fcount = 0;
|
|
}
|
|
|
|
// Release stream and buffers
|
|
cudaStreamDestroy(stream);
|
|
CUDA_CHECK(cudaFree(img_device));
|
|
CUDA_CHECK(cudaFreeHost(img_host));
|
|
CUDA_CHECK(cudaFree(buffers[inputIndex]));
|
|
CUDA_CHECK(cudaFree(buffers[outputIndex]));
|
|
// Destroy the engine
|
|
context->destroy();
|
|
engine->destroy();
|
|
runtime->destroy();
|
|
|
|
|
|
// Print histogram of the output distribution
|
|
//std::cout << "\nOutput:\n\n";
|
|
//for (unsigned int i = 0; i < OUTPUT_SIZE; i++)
|
|
//{
|
|
// std::cout << prob[i] << ", ";
|
|
// if (i % 10 == 0) std::cout << std::endl;
|
|
//}
|
|
//std::cout << std::endl;
|
|
|
|
return 0;
|
|
}
|