diff --git a/build/darknet/yolo_console_dll.vcxproj b/build/darknet/yolo_console_dll.vcxproj
index 104863fa..176d70ba 100644
--- a/build/darknet/yolo_console_dll.vcxproj
+++ b/build/darknet/yolo_console_dll.vcxproj
@@ -115,14 +115,14 @@
true
true
true
- C:\opencv_3.0\opencv\build\include
+ C:\opencv_source\opencv\bin\install\include
_CRT_SECURE_NO_WARNINGS;_MBCS;%(PreprocessorDefinitions)
Async
true
true
- C:\opencv_3.0\opencv\build\x64\vc14\lib;C:\opencv_2.4.13\opencv\build\x64\vc12\lib
+ C:\opencv_source\opencv\bin\install\x64\vc14\lib;C:\opencv_3.0\opencv\build\x64\vc14\lib;C:\opencv_2.4.13\opencv\build\x64\vc12\lib
diff --git a/src/activation_kernels.cu b/src/activation_kernels.cu
index 994e2068..d5f25a0b 100644
--- a/src/activation_kernels.cu
+++ b/src/activation_kernels.cu
@@ -154,7 +154,7 @@ __global__ void gradient_array_kernel(float *x, int n, ACTIVATION a, float *delt
extern "C" void activate_array_ongpu(float *x, int n, ACTIVATION a)
{
- activate_array_kernel<<>>(x, n, a);
+ activate_array_kernel<<>>(x, n, a);
check_error(cudaPeekAtLastError());
}
diff --git a/src/blas_kernels.cu b/src/blas_kernels.cu
index 79fc1c1d..8e1cf19e 100644
--- a/src/blas_kernels.cu
+++ b/src/blas_kernels.cu
@@ -23,7 +23,7 @@ void scale_bias_gpu(float *output, float *biases, int batch, int n, int size)
dim3 dimGrid((size-1)/BLOCK + 1, n, batch);
dim3 dimBlock(BLOCK, 1, 1);
- scale_bias_kernel<<>>(output, biases, n, size);
+ scale_bias_kernel<<>>(output, biases, n, size);
check_error(cudaPeekAtLastError());
}
@@ -67,7 +67,7 @@ void add_bias_gpu(float *output, float *biases, int batch, int n, int size)
dim3 dimGrid((size-1)/BLOCK + 1, n, batch);
dim3 dimBlock(BLOCK, 1, 1);
- add_bias_kernel<<>>(output, biases, n, size);
+ add_bias_kernel<<>>(output, biases, n, size);
check_error(cudaPeekAtLastError());
}
@@ -427,7 +427,7 @@ __global__ void mul_kernel(int N, float *X, int INCX, float *Y, int INCY)
extern "C" void normalize_gpu(float *x, float *mean, float *variance, int batch, int filters, int spatial)
{
size_t N = batch*filters*spatial;
- normalize_kernel<<>>(N, x, mean, variance, batch, filters, spatial);
+ normalize_kernel<<>>(N, x, mean, variance, batch, filters, spatial);
check_error(cudaPeekAtLastError());
}
@@ -490,13 +490,13 @@ __global__ void fast_variance_kernel(float *x, float *mean, int batch, int filt
extern "C" void fast_mean_gpu(float *x, int batch, int filters, int spatial, float *mean)
{
- fast_mean_kernel<<>>(x, batch, filters, spatial, mean);
+ fast_mean_kernel<<>>(x, batch, filters, spatial, mean);
check_error(cudaPeekAtLastError());
}
extern "C" void fast_variance_gpu(float *x, float *mean, int batch, int filters, int spatial, float *variance)
{
- fast_variance_kernel<<>>(x, mean, batch, filters, spatial, variance);
+ fast_variance_kernel<<>>(x, mean, batch, filters, spatial, variance);
check_error(cudaPeekAtLastError());
}
@@ -520,13 +520,13 @@ extern "C" void axpy_ongpu(int N, float ALPHA, float * X, int INCX, float * Y, i
extern "C" void pow_ongpu(int N, float ALPHA, float * X, int INCX, float * Y, int INCY)
{
- pow_kernel<<>>(N, ALPHA, X, INCX, Y, INCY);
+ pow_kernel<<>>(N, ALPHA, X, INCX, Y, INCY);
check_error(cudaPeekAtLastError());
}
extern "C" void axpy_ongpu_offset(int N, float ALPHA, float * X, int OFFX, int INCX, float * Y, int OFFY, int INCY)
{
- axpy_kernel<<>>(N, ALPHA, X, OFFX, INCX, Y, OFFY, INCY);
+ axpy_kernel<<>>(N, ALPHA, X, OFFX, INCX, Y, OFFY, INCY);
check_error(cudaPeekAtLastError());
}
@@ -543,7 +543,7 @@ extern "C" void mul_ongpu(int N, float * X, int INCX, float * Y, int INCY)
extern "C" void copy_ongpu_offset(int N, float * X, int OFFX, int INCX, float * Y, int OFFY, int INCY)
{
- copy_kernel<<>>(N, X, OFFX, INCX, Y, OFFY, INCY);
+ copy_kernel<<>>(N, X, OFFX, INCX, Y, OFFY, INCY);
check_error(cudaPeekAtLastError());
}
@@ -567,20 +567,20 @@ __global__ void flatten_kernel(int N, float *x, int spatial, int layers, int bat
extern "C" void flatten_ongpu(float *x, int spatial, int layers, int batch, int forward, float *out)
{
int size = spatial*batch*layers;
- flatten_kernel<<>>(size, x, spatial, layers, batch, forward, out);
+ flatten_kernel<<>>(size, x, spatial, layers, batch, forward, out);
check_error(cudaPeekAtLastError());
}
extern "C" void reorg_ongpu(float *x, int w, int h, int c, int batch, int stride, int forward, float *out)
{
int size = w*h*c*batch;
- reorg_kernel<<>>(size, x, w, h, c, batch, stride, forward, out);
+ reorg_kernel<<>>(size, x, w, h, c, batch, stride, forward, out);
check_error(cudaPeekAtLastError());
}
extern "C" void mask_ongpu(int N, float * X, float mask_num, float * mask)
{
- mask_kernel<<>>(N, X, mask_num, mask);
+ mask_kernel<<>>(N, X, mask_num, mask);
check_error(cudaPeekAtLastError());
}
@@ -599,7 +599,7 @@ extern "C" void constrain_ongpu(int N, float ALPHA, float * X, int INCX)
extern "C" void scal_ongpu(int N, float ALPHA, float * X, int INCX)
{
- scal_kernel<<>>(N, ALPHA, X, INCX);
+ scal_kernel<<>>(N, ALPHA, X, INCX);
check_error(cudaPeekAtLastError());
}
@@ -611,7 +611,7 @@ extern "C" void supp_ongpu(int N, float ALPHA, float * X, int INCX)
extern "C" void fill_ongpu(int N, float ALPHA, float * X, int INCX)
{
- fill_kernel<<>>(N, ALPHA, X, INCX);
+ fill_kernel<<>>(N, ALPHA, X, INCX);
check_error(cudaPeekAtLastError());
}
@@ -766,6 +766,6 @@ extern "C" void softmax_gpu(float *input, int n, int offset, int groups, float t
{
int inputs = n;
int batch = groups;
- softmax_kernel<<>>(inputs, offset, batch, input, temp, output);
+ softmax_kernel<<>>(inputs, offset, batch, input, temp, output);
check_error(cudaPeekAtLastError());
}
diff --git a/src/cuda.c b/src/cuda.c
index 1b51271f..f168e4e2 100644
--- a/src/cuda.c
+++ b/src/cuda.c
@@ -61,6 +61,19 @@ dim3 cuda_gridsize(size_t n){
return d;
}
+static cudaStream_t streamsArray[16]; // cudaStreamSynchronize( get_cuda_stream() );
+static int streamInit[16] = { 0 };
+
+cudaStream_t get_cuda_stream() {
+ int i = cuda_get_device();
+ if (!streamInit[i]) {
+ cudaStreamCreate(&streamsArray[i]);
+ streamInit[i] = 1;
+ }
+ return streamsArray[i];
+}
+
+
#ifdef CUDNN
cudnnHandle_t cudnn_handle()
{
@@ -70,6 +83,7 @@ cudnnHandle_t cudnn_handle()
if(!init[i]) {
cudnnCreate(&handle[i]);
init[i] = 1;
+ cudnnStatus_t status = cudnnSetStream(handle[i], get_cuda_stream());
}
return handle[i];
}
@@ -94,7 +108,8 @@ float *cuda_make_array(float *x, size_t n)
cudaError_t status = cudaMalloc((void **)&x_gpu, size);
check_error(status);
if(x){
- status = cudaMemcpy(x_gpu, x, size, cudaMemcpyHostToDevice);
+ //status = cudaMemcpy(x_gpu, x, size, cudaMemcpyHostToDevice);
+ status = cudaMemcpyAsync(x_gpu, x, size, cudaMemcpyHostToDevice, get_cuda_stream());
check_error(status);
}
if(!x_gpu) error("Cuda malloc failed\n");
@@ -139,6 +154,7 @@ int *cuda_make_int_array(size_t n)
void cuda_free(float *x_gpu)
{
+ //cudaStreamSynchronize(get_cuda_stream());
cudaError_t status = cudaFree(x_gpu);
check_error(status);
}
@@ -146,15 +162,18 @@ void cuda_free(float *x_gpu)
void cuda_push_array(float *x_gpu, float *x, size_t n)
{
size_t size = sizeof(float)*n;
- cudaError_t status = cudaMemcpy(x_gpu, x, size, cudaMemcpyHostToDevice);
+ //cudaError_t status = cudaMemcpy(x_gpu, x, size, cudaMemcpyHostToDevice);
+ cudaError_t status = cudaMemcpyAsync(x_gpu, x, size, cudaMemcpyHostToDevice, get_cuda_stream());
check_error(status);
}
void cuda_pull_array(float *x_gpu, float *x, size_t n)
{
size_t size = sizeof(float)*n;
- cudaError_t status = cudaMemcpy(x, x_gpu, size, cudaMemcpyDeviceToHost);
+ //cudaError_t status = cudaMemcpy(x, x_gpu, size, cudaMemcpyDeviceToHost);
+ cudaError_t status = cudaMemcpyAsync(x, x_gpu, size, cudaMemcpyDeviceToHost, get_cuda_stream());
check_error(status);
+ cudaStreamSynchronize(get_cuda_stream());
}
#endif
diff --git a/src/cuda.h b/src/cuda.h
index 32aaabb4..31f9092a 100644
--- a/src/cuda.h
+++ b/src/cuda.h
@@ -30,6 +30,7 @@ void cuda_free(float *x_gpu);
void cuda_random(float *x_gpu, size_t n);
float cuda_compare(float *x_gpu, float *x, size_t n, char *s);
dim3 cuda_gridsize(size_t n);
+cudaStream_t get_cuda_stream();
#ifdef CUDNN
cudnnHandle_t cudnn_handle();
diff --git a/src/gemm.c b/src/gemm.c
index a4db8a4b..c3154ec9 100644
--- a/src/gemm.c
+++ b/src/gemm.c
@@ -177,6 +177,7 @@ void gemm_ongpu(int TA, int TB, int M, int N, int K, float ALPHA,
float *C_gpu, int ldc)
{
cublasHandle_t handle = blas_handle();
+ cudaError_t stream_status = cublasSetStream(handle, get_cuda_stream());
cudaError_t status = cublasSgemm(handle, (TB ? CUBLAS_OP_T : CUBLAS_OP_N),
(TA ? CUBLAS_OP_T : CUBLAS_OP_N), N, M, K, &ALPHA, B_gpu, ldb, A_gpu, lda, &BETA, C_gpu, ldc);
check_error(status);
diff --git a/src/im2col_kernels.cu b/src/im2col_kernels.cu
index d42d600b..8a15e504 100644
--- a/src/im2col_kernels.cu
+++ b/src/im2col_kernels.cu
@@ -54,7 +54,7 @@ void im2col_ongpu(float *im,
int width_col = (width + 2 * pad - ksize) / stride + 1;
int num_kernels = channels * height_col * width_col;
im2col_gpu_kernel<<<(num_kernels+BLOCK-1)/BLOCK,
- BLOCK>>>(
+ BLOCK, 0, get_cuda_stream()>>>(
num_kernels, im, height, width, ksize, pad,
stride, height_col,
width_col, data_col);
diff --git a/src/maxpool_layer_kernels.cu b/src/maxpool_layer_kernels.cu
index 6381cc1e..d40d3c0b 100644
--- a/src/maxpool_layer_kernels.cu
+++ b/src/maxpool_layer_kernels.cu
@@ -92,7 +92,7 @@ extern "C" void forward_maxpool_layer_gpu(maxpool_layer layer, network_state sta
size_t n = h*w*c*layer.batch;
- forward_maxpool_layer_kernel<<>>(n, layer.h, layer.w, layer.c, layer.stride, layer.size, layer.pad, state.input, layer.output_gpu, layer.indexes_gpu);
+ forward_maxpool_layer_kernel<<>>(n, layer.h, layer.w, layer.c, layer.stride, layer.size, layer.pad, state.input, layer.output_gpu, layer.indexes_gpu);
check_error(cudaPeekAtLastError());
}
diff --git a/src/region_layer.c b/src/region_layer.c
index 9095b3ce..0638301f 100644
--- a/src/region_layer.c
+++ b/src/region_layer.c
@@ -409,6 +409,7 @@ void forward_region_layer_gpu(const region_layer l, network_state state)
cuda_pull_array(state.truth, truth_cpu, num_truth);
}
cuda_pull_array(l.output_gpu, in_cpu, l.batch*l.inputs);
+ cudaStreamSynchronize(get_cuda_stream());
network_state cpu_state = state;
cpu_state.train = state.train;
cpu_state.truth = truth_cpu;
diff --git a/src/yolo_console_dll.cpp b/src/yolo_console_dll.cpp
index ebafe110..16a90496 100644
--- a/src/yolo_console_dll.cpp
+++ b/src/yolo_console_dll.cpp
@@ -169,8 +169,8 @@ int main(int argc, char *argv[])
//if (x > 10) return;
if (result_vec.size() == 0) return;
bbox_t i = result_vec[0];
- //cv::Rect r(i.x, i.y, i.w, i.h);
- cv::Rect r(i.x + (i.w-31)/2, i.y + (i.h - 31)/2, 31, 31);
+ cv::Rect r(i.x, i.y, i.w, i.h);
+ //cv::Rect r(i.x + (i.w-31)/2, i.y + (i.h - 31)/2, 31, 31);
cv::Rect img_rect(cv::Point2i(0, 0), src_frame.size());
cv::Rect rect_roi = r & img_rect;
if (rect_roi.width < 1 || rect_roi.height < 1) return;
@@ -188,16 +188,25 @@ int main(int argc, char *argv[])
// track optical flow
if (track_optflow_queue.size() > 0) {
+ //show_flow = track_optflow_queue.front().clone();
+ //draw_boxes(show_flow, result_vec, obj_names, 3, current_det_fps, current_cap_fps);
+
std::queue new_track_optflow_queue;
- std::cout << "\n !!!! all = " << track_optflow_queue.size() << ", cur = " << passed_flow_frames << std::endl;
- //draw_boxes(track_optflow_queue.front().clone(), result_vec, obj_names, 3, current_det_fps, current_cap_fps);
- //cv::waitKey(10);
+ //std::cout << "\n !!!! all = " << track_optflow_queue.size() << ", cur = " << passed_flow_frames << std::endl;
+ if (result_vec.size() > 0) {
+ draw_boxes(track_optflow_queue.front().clone(), result_vec, obj_names, 3, current_det_fps, current_cap_fps);
+ std::cout << "\n frame_size = " << track_optflow_queue.size() << std::endl;
+ cv::waitKey(1000);
+ }
tracker_flow.update_tracking_flow(track_optflow_queue.front());
lambda(show_flow, track_optflow_queue.front(), result_vec);
track_optflow_queue.pop();
while(track_optflow_queue.size() > 0) {
- //draw_boxes(track_optflow_queue.front().clone(), result_vec, obj_names, 3, current_det_fps, current_cap_fps);
- //cv::waitKey(10);
+ if (result_vec.size() > 0) {
+ draw_boxes(track_optflow_queue.front().clone(), result_vec, obj_names, 3, current_det_fps, current_cap_fps);
+ std::cout << "\n frame_size = " << track_optflow_queue.size() << std::endl;
+ cv::waitKey(1000);
+ }
result_vec = tracker_flow.tracking_flow(track_optflow_queue.front(), result_vec);
if (track_optflow_queue.size() <= passed_flow_frames && new_track_optflow_queue.size() == 0)
new_track_optflow_queue = track_optflow_queue;
@@ -207,10 +216,13 @@ int main(int argc, char *argv[])
track_optflow_queue = new_track_optflow_queue;
new_track_optflow_queue.swap(std::queue());
passed_flow_frames = 0;
- std::cout << "\n !!!! now = " << track_optflow_queue.size() << ", cur = " << passed_flow_frames << std::endl;
+ //std::cout << "\n !!!! now = " << track_optflow_queue.size() << ", cur = " << passed_flow_frames << std::endl;
cv::imshow("flow", show_flow);
cv::waitKey(3);
+ //if (result_vec.size() > 0) {
+ // cv::waitKey(1000);
+ //}
}
#endif
@@ -222,7 +234,8 @@ int main(int argc, char *argv[])
consumed = true;
while (current_image.use_count() > 0) {
auto result = detector.detect_resized(*current_image, frame_size, 0.24, false); // true
- Sleep(500);
+ //Sleep(200);
+ Sleep(50);
++fps_det_counter;
std::unique_lock lock(mtx);
thread_result_vec = result;