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added yolo4x and yolo4-csp from the github repo and download file corrections

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hchandirasekar
2021-03-26 12:18:46 +05:30
parent 557fb732a5
commit a2b0dd62d1
12 changed files with 1444 additions and 40 deletions
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src/Activation.cpp
+5 -1
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@@ -52,7 +52,11 @@ dnnType* Activation::infer(dataDim_t &dim, dnnType* srcData) {
else if(act_mode == ACTIVATION_MISH) {
activationMishForward(srcData, dstData, dim.tot());
} else {
}
else if(act_mode == ACTIVATION_LOGISTIC) {
activationLOGISTICForward(srcData, dstData, dim.tot());
}else {
dnnType alpha = dnnType(1);
dnnType beta = dnnType(0);
checkCUDNN( cudnnActivationForward(net->cudnnHandle,
src/DarknetParser.cpp
+1
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@@ -187,6 +187,7 @@ namespace tk { namespace dnn {
if(f.activation == "relu") act = tkdnnActivationMode_t(CUDNN_ACTIVATION_RELU);
else if(f.activation == "leaky") act = tk::dnn::ACTIVATION_LEAKY;
else if(f.activation == "mish") act = tk::dnn::ACTIVATION_MISH;
else if(f.activation == "logistic") act = tk::dnn::ACTIVATION_LOGISTIC;
else { FatalError("activation not supported: " + f.activation); }
netLayers[netLayers.size()-1] = new tk::dnn::Activation(net, act);
};
src/NetworkRT.cpp
+12 -9
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@@ -229,7 +229,7 @@ ILayer* NetworkRT::convert_layer(ITensor *input, Layer *l) {
return convert_layer(input, (Conv2d*) l);
if(type == LAYER_POOLING)
return convert_layer(input, (Pooling*) l);
if(type == LAYER_ACTIVATION || type == LAYER_ACTIVATION_CRELU || type == LAYER_ACTIVATION_LEAKY || type == LAYER_ACTIVATION_MISH)
if(type == LAYER_ACTIVATION || type == LAYER_ACTIVATION_CRELU || type == LAYER_ACTIVATION_LEAKY || type == LAYER_ACTIVATION_MISH || type == LAYER_ACTIVATION_LOGISTIC)
return convert_layer(input, (Activation*) l);
if(type == LAYER_SOFTMAX)
return convert_layer(input, (Softmax*) l);
@@ -424,6 +424,12 @@ ILayer* NetworkRT::convert_layer(ITensor *input, Activation *l) {
checkNULL(lRT);
return lRT;
}
else if(l->act_mode == ACTIVATION_LOGISTIC) {
IPlugin *plugin = new ActivationLogisticRT();
IPluginLayer *lRT = networkRT->addPlugin(&input, 1, *plugin);
checkNULL(lRT);
return lRT;
}
else {
FatalError("this Activation mode is not yet implemented");
return NULL;
@@ -660,6 +666,11 @@ IPlugin* PluginFactory::createPlugin(const char* layerName, const void* serialDa
assert(buf == bufCheck + serialLength);
return a;
}
if(name.find("ActivationLogistic") == 0) {
ActivationLogisticRT *a = new ActivationLogisticRT();
a->size = readBUF<int>(buf);
return a;
}
if(name.find("ActivationCReLU") == 0) {
float activationReluTemp = readBUF<float>(buf);
//ActivationReLUCeiling *a = new ActivationReLUCeiling(readBUF<float>(buf));
@@ -784,17 +795,9 @@ IPlugin* PluginFactory::createPlugin(const char* layerName, const void* serialDa
float nms_thresh_temp = readBUF<float>(buf);
int nms_kind_temp = readBUF<int>(buf);
int new_coords_temp = readBUF<int>(buf);
std::cout << classes_temp << ":" << num_temp << ":" << ":" << n_masks_temp << ":" << nms_thresh_temp << ":" << nms_kind_temp << ":" << new_coords_temp << std::endl;
YoloRT *r = new YoloRT(classes_temp,num_temp,nullptr,n_masks_temp,scale_xy_temp,nms_thresh_temp,nms_kind_temp,new_coords_temp);
/* std::cout << "classes : " << r->classes;
std::cout << "num : " << r->num;
std::cout << "n_masks : " << r->n_masks;
std::cout << "scalexy : " << r->scaleXY;
std::cout << "nms_thresh : " << r->nms_thresh;
std::cout << "nms_kind : " << r->nms_kind;
std::cout << "new_coords : " << r->new_coords;*/
r->c = readBUF<int>(buf);
src/Yolo.cpp
+12 -9
View File
@@ -73,8 +73,8 @@ Yolo::box get_yolo_box(float *x, float *biases, int n, int index, int i, int j,
b.h = exp(x[index + 3*stride]) * biases[2*n+1] / h;
}
else{
b.x = (i + x[index + 0 * stride] * 2 - 0.5) / lw;
b.y = (j + x[index + 1 * stride] * 2 - 0.5) / lh;
b.x = (i + x[index + 0 * stride] ) / lw;
b.y = (j + x[index + 1 * stride] ) / lh;
b.w = x[index + 2 * stride] * x[index + 2 * stride] * 4 * biases[2 * n] / w;
b.h = x[index + 3 * stride] * x[index + 3 * stride] * 4 * biases[2 * n + 1] / h;
}
@@ -88,15 +88,18 @@ dnnType* Yolo::infer(dataDim_t &dim, dnnType* srcData) {
for (int b = 0; b < dim.n; ++b){
for(int n = 0; n < n_masks; ++n){
int index = entry_index(b, n*dim.w*dim.h, 0, classes, input_dim, output_dim);
if (new_coords == 1)
activationLOGISTICForward(srcData + index, dstData + index, 4*dim.w*dim.h);
else
std::cout<<"new_coords"<<new_coords<<std::endl;
if (new_coords == 1){
if (this->scaleXY != 1) scalAdd(dstData + index, 2 * dim.w*dim.h, this->scaleXY, -0.5*(this->scaleXY - 1), 1);
}
else{
activationLOGISTICForward(srcData + index, dstData + index, 2*dim.w*dim.h);
if (this->scaleXY != 1) scalAdd(dstData + index, 2 * dim.w*dim.h, this->scaleXY, -0.5*(this->scaleXY - 1), 1);
index = entry_index(b, n*dim.w*dim.h, 4, classes, input_dim, output_dim);
activationLOGISTICForward(srcData + index, dstData + index, (1+classes)*dim.w*dim.h);
if (this->scaleXY != 1) scalAdd(dstData + index, 2 * dim.w*dim.h, this->scaleXY, -0.5*(this->scaleXY - 1), 1);
index = entry_index(b, n*dim.w*dim.h, 4, classes, input_dim, output_dim);
activationLOGISTICForward(srcData + index, dstData + index, (1+classes)*dim.w*dim.h);
}
}
}