thebears/deepstream_yolo
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New features and fixes

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This commit is contained in:
Marcos Luciano
2023-06-05 14:48:23 -03:00
parent 3f14b0d95d
commit 66a6754b77
57 changed files with 2137 additions and 1534 deletions
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45
nvdsinfer_custom_impl_Yolo/yoloForward_v2.cu
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@@ -27,9 +27,9 @@ __device__ void softmaxGPU(const float* input, const int bbindex, const int numG
}
}
__global__ void gpuRegionLayer(const float* input, float* softmax, float* output, int* count, const uint netWidth,
const uint netHeight, const uint gridSizeX, const uint gridSizeY, const uint numOutputClasses, const uint numBBoxes,
const float* anchors)
__global__ void gpuRegionLayer(const float* input, float* softmax, float* boxes, float* scores, int* classes,
const uint netWidth, const uint netHeight, const uint gridSizeX, const uint gridSizeY, const uint numOutputClasses,
const uint numBBoxes, const uint64_t lastInputSize, const float* anchors)
{
uint x_id = blockIdx.x * blockDim.x + threadIdx.x;
uint y_id = blockIdx.y * blockDim.y + threadIdx.y;
@@ -41,8 +41,6 @@ __global__ void gpuRegionLayer(const float* input, float* softmax, float* output
const int numGridCells = gridSizeX * gridSizeY;
const int bbindex = y_id * gridSizeX + x_id;
const float objectness = sigmoidGPU(input[bbindex + numGridCells * (z_id * (5 + numOutputClasses) + 4)]);
float xc = (sigmoidGPU(input[bbindex + numGridCells * (z_id * (5 + numOutputClasses) + 0)]) + x_id) * netWidth / gridSizeX;
float yc = (sigmoidGPU(input[bbindex + numGridCells * (z_id * (5 + numOutputClasses) + 1)]) + y_id) * netHeight / gridSizeY;
@@ -53,6 +51,8 @@ __global__ void gpuRegionLayer(const float* input, float* softmax, float* output
float h = __expf(input[bbindex + numGridCells * (z_id * (5 + numOutputClasses) + 3)]) * anchors[z_id * 2 + 1] * netHeight /
gridSizeY;
const float objectness = sigmoidGPU(input[bbindex + numGridCells * (z_id * (5 + numOutputClasses) + 4)]);
softmaxGPU(input, bbindex, numGridCells, z_id, numOutputClasses, 1.0, softmax);
float maxProb = 0.0f;
@@ -66,23 +66,25 @@ __global__ void gpuRegionLayer(const float* input, float* softmax, float* output
}
}
int _count = (int)atomicAdd(count, 1);
int count = z_id * gridSizeX * gridSizeY + y_id * gridSizeY + x_id + lastInputSize;
output[_count * 6 + 0] = xc;
output[_count * 6 + 1] = yc;
output[_count * 6 + 2] = w;
output[_count * 6 + 3] = h;
output[_count * 6 + 4] = maxProb * objectness;
output[_count * 6 + 5] = maxIndex;
boxes[count * 4 + 0] = xc;
boxes[count * 4 + 1] = yc;
boxes[count * 4 + 2] = w;
boxes[count * 4 + 3] = h;
scores[count] = maxProb * objectness;
classes[count] = maxIndex;
}
cudaError_t cudaRegionLayer(const void* input, void* softmax, void* output, void* count, const uint& batchSize,
uint64_t& inputSize, uint64_t& outputSize, 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* boxes, void* scores, void* classes,
const uint& batchSize, const uint64_t& inputSize, const uint64_t& outputSize, const uint64_t& lastInputSize,
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* output, void* count, const uint& batchSize,
uint64_t& inputSize, uint64_t& outputSize, 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* boxes, void* scores, void* classes,
const uint& batchSize, const uint64_t& inputSize, const uint64_t& outputSize, const uint64_t& lastInputSize,
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, (gridSizeY / threads_per_block.y) + 1,
@@ -92,9 +94,10 @@ cudaError_t cudaRegionLayer(const void* input, void* softmax, void* output, void
gpuRegionLayer<<<number_of_blocks, threads_per_block, 0, stream>>>(
reinterpret_cast<const float*> (input) + (batch * inputSize),
reinterpret_cast<float*> (softmax) + (batch * inputSize),
reinterpret_cast<float*> (output) + (batch * 6 * outputSize),
reinterpret_cast<int*> (count) + (batch),
netWidth, netHeight, gridSizeX, gridSizeY, numOutputClasses, numBBoxes,
reinterpret_cast<float*> (boxes) + (batch * 4 * outputSize),
reinterpret_cast<float*> (scores) + (batch * 1 * outputSize),
reinterpret_cast<int*> (classes) + (batch * 1 * outputSize),
netWidth, netHeight, gridSizeX, gridSizeY, numOutputClasses, numBBoxes, lastInputSize,
reinterpret_cast<const float*> (anchors));
}
return cudaGetLastError();