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Add support for yolov4x-mish.

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Changes:
- add parameters nms_kind, nms_thresh, new_coords to yolo layer and darknet parser
- added diou nms, new method to compute the BBs
- created test for yolov4x-mish called yolo4x

Tested, all tests work.
Problem to solve: little loss in mAP of yolo4x

Signed-off-by: Micaela Verucchi <micaelaverucchi@gmail.com>
This commit is contained in:
Micaela Verucchi
2020-11-23 11:25:52 +01:00
parent 86478f9384
commit 702791e41a
10 changed files with 1571 additions and 31 deletions
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include/tkDNN/pluginsRT/YoloRT.h
+16 -4
View File
@@ -8,12 +8,15 @@ class YoloRT : public IPlugin {
public:
YoloRT(int classes, int num, tk::dnn::Yolo *yolo = nullptr, int n_masks=3, float scale_xy=1) {
YoloRT(int classes, int num, tk::dnn::Yolo *yolo = nullptr, int n_masks=3, float scale_xy=1, float nms_thresh=0.45, int nms_kind=0, int new_coords=0) {
this->classes = classes;
this->num = num;
this->n_masks = n_masks;
this->scaleXY = scale_xy;
this->nms_thresh = nms_thresh;
this->nms_kind = nms_kind;
this->new_coords = new_coords;
mask = new dnnType[n_masks];
bias = new dnnType[num*n_masks*2];
@@ -64,7 +67,10 @@ public:
for (int b = 0; b < batchSize; ++b){
for(int n = 0; n < n_masks; ++n){
int index = entry_index(b, n*w*h, 0);
activationLOGISTICForward(srcData + index, dstData + index, 2*w*h, stream);
if (new_coords == 1)
activationLOGISTICForward(srcData + index, dstData + index, 4*w*h, stream); //x,y,w,h
else
activationLOGISTICForward(srcData + index, dstData + index, 2*w*h, stream); //x,y
if (this->scaleXY != 1) scalAdd(dstData + index, 2 * w*h, this->scaleXY, -0.5*(this->scaleXY - 1), 1);
@@ -79,7 +85,7 @@ public:
virtual size_t getSerializationSize() override {
return 6*sizeof(int) + sizeof(float)+ n_masks*sizeof(dnnType) + num*n_masks*2*sizeof(dnnType) + YOLORT_CLASSNAME_W*classes*sizeof(char);
return 8*sizeof(int) + 2*sizeof(float)+ n_masks*sizeof(dnnType) + num*n_masks*2*sizeof(dnnType) + YOLORT_CLASSNAME_W*classes*sizeof(char);
}
virtual void serialize(void* buffer) override {
@@ -87,10 +93,13 @@ public:
tk::dnn::writeBUF(buf, classes);
tk::dnn::writeBUF(buf, num);
tk::dnn::writeBUF(buf, n_masks);
tk::dnn::writeBUF(buf, scaleXY);
tk::dnn::writeBUF(buf, nms_thresh);
tk::dnn::writeBUF(buf, nms_kind);
tk::dnn::writeBUF(buf, new_coords);
tk::dnn::writeBUF(buf, c);
tk::dnn::writeBUF(buf, h);
tk::dnn::writeBUF(buf, w);
tk::dnn::writeBUF(buf, scaleXY);
for(int i=0; i<n_masks; i++)
tk::dnn::writeBUF(buf, mask[i]);
for(int i=0; i<n_masks*2*num; i++)
@@ -109,6 +118,9 @@ public:
int c, h, w;
int classes, num, n_masks;
float scaleXY;
float nms_thresh;
int nms_kind;
int new_coords;
std::vector<std::string> classesNames;
dnnType *mask;