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New optimized NMS

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This commit is contained in:
Marcos Luciano
2022-08-15 02:48:23 -03:00
parent 8ad99d3f8d
commit c8a4a49f16
24 changed files with 206 additions and 394 deletions
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45
nvdsinfer_custom_impl_Yolo/yoloForward_v2.cu
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@@ -29,9 +29,9 @@ __device__ void softmaxGPU(
}
__global__ void gpuRegionLayer(
const float* input, float* softmax, int* d_indexes, float* d_scores, float* d_boxes, int* d_classes, int* countData,
const float scoreThreshold, const uint netWidth, const uint netHeight, const uint gridSizeX, const uint gridSizeY,
const uint numOutputClasses, const uint numBBoxes, const float* anchors)
const float* input, float* softmax, int* num_detections, float* detection_boxes, float* detection_scores,
int* detection_classes, const float scoreThreshold, const uint netWidth, const uint netHeight, const uint gridSizeX,
const uint gridSizeY, const uint numOutputClasses, const uint numBBoxes, const float* anchors)
{
uint x_id = blockIdx.x * blockDim.x + threadIdx.x;
uint y_id = blockIdx.y * blockDim.y + threadIdx.y;
@@ -49,7 +49,7 @@ __global__ void gpuRegionLayer(
if (objectness < scoreThreshold)
return;
int count = (int)atomicAdd(countData, 1);
int count = (int)atomicAdd(num_detections, 1);
float x
= (sigmoidGPU(input[bbindex + numGridCells * (z_id * (5 + numOutputClasses) + 0)])
@@ -84,26 +84,25 @@ __global__ void gpuRegionLayer(
}
}
d_indexes[count] = count;
d_scores[count] = objectness * maxProb + 1.f;
d_boxes[count * 4 + 0] = x - 0.5 * w;
d_boxes[count * 4 + 1] = y - 0.5 * h;
d_boxes[count * 4 + 2] = x + 0.5 * w;
d_boxes[count * 4 + 3] = y + 0.5 * h;
d_classes[count] = maxIndex;
detection_boxes[count * 4 + 0] = x - 0.5 * w;
detection_boxes[count * 4 + 1] = y - 0.5 * h;
detection_boxes[count * 4 + 2] = x + 0.5 * w;
detection_boxes[count * 4 + 3] = y + 0.5 * h;
detection_scores[count] = objectness * maxProb;
detection_classes[count] = maxIndex;
}
cudaError_t cudaRegionLayer(
const void* input, void* softmax, void* d_indexes, void* d_scores, void* d_boxes, void* d_classes, void* countData,
const uint& batchSize, uint64_t& inputSize, uint64_t& outputSize, const float& scoreThreshold, const uint& netWidth,
const uint& netHeight, const uint& gridSizeX, const uint& gridSizeY, const uint& numOutputClasses, const uint& numBBoxes,
const void* anchors, cudaStream_t stream);
const void* input, void* softmax, void* num_detections, void* detection_boxes, void* detection_scores,
void* detection_classes, const uint& batchSize, uint64_t& inputSize, uint64_t& outputSize, const float& scoreThreshold,
const uint& netWidth, const uint& netHeight, const uint& gridSizeX, const uint& gridSizeY, const uint& numOutputClasses,
const uint& numBBoxes, const void* anchors, cudaStream_t stream);
cudaError_t cudaRegionLayer(
const void* input, void* softmax, void* d_indexes, void* d_scores, void* d_boxes, void* d_classes, void* countData,
const uint& batchSize, uint64_t& inputSize, uint64_t& outputSize, const float& scoreThreshold, const uint& netWidth,
const uint& netHeight, const uint& gridSizeX, const uint& gridSizeY, const uint& numOutputClasses, const uint& numBBoxes,
const void* anchors, cudaStream_t stream)
const void* input, void* softmax, void* num_detections, void* detection_boxes, void* detection_scores,
void* detection_classes, const uint& batchSize, uint64_t& inputSize, uint64_t& outputSize, const float& scoreThreshold,
const uint& netWidth, const uint& netHeight, const uint& gridSizeX, const uint& gridSizeY, const uint& numOutputClasses,
const uint& numBBoxes, const void* anchors, cudaStream_t stream)
{
dim3 threads_per_block(16, 16, 4);
dim3 number_of_blocks((gridSizeX / threads_per_block.x) + 1,
@@ -115,10 +114,10 @@ cudaError_t cudaRegionLayer(
gpuRegionLayer<<<number_of_blocks, threads_per_block, 0, stream>>>(
reinterpret_cast<const float*>(input) + (batch * inputSize),
reinterpret_cast<float*>(softmax) + (batch * inputSize),
reinterpret_cast<int*>(d_indexes) + (batch * outputSize),
reinterpret_cast<float*>(d_scores) + (batch * outputSize),
reinterpret_cast<float*>(d_boxes) + (batch * 4 * outputSize),
reinterpret_cast<int*>(d_classes) + (batch * outputSize), reinterpret_cast<int*>(countData) + (batch),
reinterpret_cast<int*>(num_detections) + (batch),
reinterpret_cast<float*>(detection_boxes) + (batch * 4 * outputSize),
reinterpret_cast<float*>(detection_scores) + (batch * outputSize),
reinterpret_cast<int*>(detection_classes) + (batch * outputSize),
scoreThreshold, netWidth, netHeight, gridSizeX, gridSizeY, numOutputClasses, numBBoxes,
reinterpret_cast<const float*>(anchors));
}