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tkDNN can now deserialize tensorrt-8 engine (both through test_* and trtexec)

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but demo has issues in yolo::computeDetections
This commit is contained in:
Harshvardhan Chandirasekar
2021-09-05 01:06:56 +05:30
parent de83ae5d25
commit 65ba5c9844
35 changed files with 3527 additions and 2322 deletions
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src/Yolo.cpp
+3 -2
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@@ -133,10 +133,11 @@ void correct_yolo_boxes(Yolo::detection *dets, int n, int w, int h, int netw, in
}
}
int Yolo::computeDetections(Yolo::detection *dets, int &ndets, int netw, int neth, float thresh, int new_coords) {
int Yolo::computeDetections(Yolo::detection *dets, int &ndets, int netw, int neth, float thresh, int newCoords) {
if(predictions == nullptr)
predictions = new dnnType[output_dim.tot()];
checkCuda(cudaDeviceSynchronize());
checkCuda( cudaMemcpy(predictions, dstData, output_dim.tot()*sizeof(dnnType), cudaMemcpyDeviceToHost));
int lw = output_dim.w;
@@ -157,7 +158,7 @@ int Yolo::computeDetections(Yolo::detection *dets, int &ndets, int netw, int net
if(objectness <= thresh) continue;
int box_index = entry_index(0, n*lw*lh + i, 0, classes, input_dim, output_dim);
dets[count].bbox = get_yolo_box(predictions, bias_h, mask_h[n], box_index, col, row, lw, lh, netw, neth, lw*lh, new_coords);
dets[count].bbox = get_yolo_box(predictions, bias_h, mask_h[n], box_index, col, row, lw, lh, netw, neth, lw*lh, newCoords);
dets[count].objectness = objectness;
dets[count].classes = classes;
for(j = 0; j < classes; ++j){