branch_detection.cuh
4.17 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
#include <iostream>
#include <fstream>
#include <cuda_runtime.h>
#include <stim/math/vector.h>
//#include <math.h>
#include <stim/visualization/colormap.h>
#include <stim/cuda/cuda_texture.cuh>
#include <stim/cuda/templates/gradient.cuh>
#include <stim/cuda/templates/gaussian_blur.cuh>
#include <stim/cuda/arraymath.cuh>
#include <stim/cuda/ivote.cuh>
#include <stim/cuda/testKernel.cuh>
typedef unsigned int uint;
typedef unsigned int uchar;
stim::cuda::cuda_texture t;
float* gpuTable;
float* gpuGrad;
float* gpuVote;
float* gpuI;
float* gpuCenters;
void atan_2d(float* cpuTable, unsigned int rmax)
{
//initialize the width and height of the window which atan2 are computed in.
int xsize = 2*rmax +1;
int ysize = 2*rmax +1;
// assign the center coordinates of the atan2 window to yi and xi
int yi = rmax;
int xi = rmax;
for (int xt = 0; xt < xsize; xt++){
for(int yt = 0; yt < ysize; yt++){
//convert the current 2D coordinates to 1D
int id = yt * xsize + xt;
// calculate the distance between the pixel and the center of the atan2 window
float xd = xi - xt;
float yd = yi - yt;
// calculate the angle between the pixel and the center of the atan2 window and store the result.
float atan_2d_vote = atan2(yd, xd);
cpuTable[id] = atan_2d_vote;
}
}
}
void initCuda(unsigned int bytes_table, unsigned int bytes_ds)
{
HANDLE_ERROR(
cudaMalloc((void**) &gpuTable, bytes_table)
);
HANDLE_ERROR(
cudaMalloc((void**) &gpuI, bytes_ds)
);
HANDLE_ERROR(
cudaMalloc((void**) &gpuGrad, bytes_ds*2)
);
HANDLE_ERROR(
cudaMalloc((void**) &gpuVote, bytes_ds)
);
HANDLE_ERROR(
cudaMalloc((void**) &gpuCenters, bytes_ds)
);
}
void cleanCuda()
{
HANDLE_ERROR(
cudaFree(gpuTable)
);
HANDLE_ERROR(
cudaFree(gpuGrad)
);
HANDLE_ERROR(
cudaFree(gpuVote)
);
HANDLE_ERROR(
cudaFree(gpuCenters)
);
HANDLE_ERROR(
cudaFree(gpuI)
);
}
std::vector< stim::vec<float> >
find_branch(GLint texbufferID, GLenum texType, unsigned int x, unsigned int y)
{
float phi = 15.1*M_PI/180;
int iter = 5;
float dphi = phi/iter;
float rmax = 10;
float sigma = 4;
unsigned int pixels = x * y;
unsigned int bytes = sizeof(float) * pixels;
unsigned int bytes_table = sizeof(float) * (2*rmax + 1) * (2*rmax + 1);
unsigned int x_ds = (x + (x % 1 == 0 ? 0:1));
unsigned int y_ds = (y + (x % 1 == 0 ? 0:1));
unsigned int bytes_ds = sizeof(float) * x_ds * y_ds;
unsigned int conn = 5;
float final_t = 200.0;
float* cpuTable = (float*) malloc(bytes_table);
float* cpuCenters = (float*) malloc(bytes_ds);
stringstream name;
test(texbufferID, texType, x, y);
std::vector<stim::vec<float> > output;
initCuda(bytes_table, bytes_ds);
atan_2d(cpuTable, rmax);
cudaMemcpy(gpuTable, cpuTable, bytes_table, cudaMemcpyHostToDevice);
t.MapCudaTexture(texbufferID, texType);
cudaDeviceSynchronize();
stim::cuda::tex_gaussian_blur2<float>(
gpuI, sigma, x, y, t.getTexture(), t.getArray()
);
stim::gpu2image<float>(gpuI, "Blur.jpg", x,y , 0, 255);
// stim::gpu2image<float>(t.getArray(), "ORIGINAL.jpg", x,y , 0, 255);
cudaDeviceSynchronize();
stim::cuda::gpu_gradient_2d<float>(
gpuGrad, gpuI, x, y
);
cudaDeviceSynchronize();
stim::cuda::gpu_cart2polar<float>(gpuGrad, x, y);
cudaDeviceSynchronize();
cudaDeviceSynchronize();
for (int i = 0; i < iter; i++)
{
stim::cuda::gpu_vote<float>(gpuVote, gpuGrad, gpuTable, phi, rmax, x, y);
cudaDeviceSynchronize();
stim::cuda::gpu_update_dir<float>(gpuVote, gpuGrad, gpuTable, phi, rmax, x, y);
cudaDeviceSynchronize();
phi = phi - dphi;
}
cudaDeviceSynchronize();
stim::cuda::gpu_local_max<float>(gpuCenters, gpuVote, final_t, conn, x, y);
stim::gpu2image<float>(gpuCenters, "Centers.jpg", x, y, 0, 1);
cudaMemcpy(cpuCenters, gpuCenters, bytes_ds, cudaMemcpyDeviceToHost);
stim::cpu2image<float>(cpuCenters, "CentersXPU.jpg", x, y, 0, 1);
for(int i = 0; i < pixels; i++)
{
int ix = (i % x);
int iy = (i / x);
if((cpuCenters[i] != 0))
{
float x_v = (float) ix;
float y_v = (float) iy;
output.push_back(stim::vec<float>((x_v/(float)x),
(y_v/(float)y), 0.0));
}
}
t.UnmapCudaTexture();
cleanCuda();
free(cpuTable);
free(cpuCenters);
return output;
}