OrgLion-ML
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darknet
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..... and back to coords

This commit is contained in:
Joseph Redmon 2015-03-30 12:04:03 -07:00
parent ad59d7e68e
commit 81751b47dd
2 changed files with 31 additions and 31 deletions
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43
src/data.c
View File

@ -114,7 +114,7 @@ void fill_truth_detection(char *path, float *truth, int classes, int num_boxes,
int count = 0;
box *boxes = read_boxes(labelpath, &count);
randomize_boxes(boxes, count);
float l,r,t,b;
float x,y,w,h;
int id;
int i;
if(background){
@ -123,46 +123,41 @@ void fill_truth_detection(char *path, float *truth, int classes, int num_boxes,
}
}
for(i = 0; i < count; ++i){
l = boxes[i].left;
r = boxes[i].right;
t = boxes[i].top;
b = boxes[i].bottom;
x = boxes[i].x;
y = boxes[i].y;
w = boxes[i].w;
h = boxes[i].h;
id = boxes[i].id;
if(flip){
float left = l;
float right = r;
r = 1-left;
l = 1-right;
x = 1-x;
}
l = l*sx-dx;
r = r*sx-dx;
t = t*sy-dy;
b = b*sy-dy;
float x = (l+r)/2.;
float y = (t+b)/2.;
x = x*sx-dx;
y = y*sy-dy;
w = w*sx;
h = h*sy;
if (x < 0 || x >= 1 || y < 0 || y >= 1) continue;
int i = (int)(x*num_boxes);
int j = (int)(y*num_boxes);
l = constrain(0, 1, l);
r = constrain(0, 1, r);
t = constrain(0, 1, t);
b = constrain(0, 1, b);
x = x*num_boxes - i;
y = y*num_boxes - j;
w = constrain(0, 1, w);
h = constrain(0, 1, h);
int index = (i+j*num_boxes)*(4+classes+background);
if(truth[index+classes+background+2]) continue;
if(background) truth[index++] = 0;
truth[index+id] = 1;
index += classes;
truth[index++] = l;
truth[index++] = r;
truth[index++] = t;
truth[index++] = b;
truth[index++] = y;
truth[index++] = x;
truth[index++] = w;
truth[index++] = h;
}
free(boxes);
}

19
src/detection.c
View File

@ -111,7 +111,9 @@ void validate_detection(char *cfgfile, char *weightfile)
int classes = 20;
int background = 0;
int nuisance = 1;
int num_output = 7*7*(4+classes+background+nuisance);
int num_boxes = 7;
int per_box = 4+classes+background+nuisance;
int num_output = num_boxes*num_boxes*per_box;
int m = plist->size;
int i = 0;
@ -135,16 +137,19 @@ void validate_detection(char *cfgfile, char *weightfile)
matrix pred = network_predict_data(net, val);
int j, k, class;
for(j = 0; j < pred.rows; ++j){
for(k = 0; k < pred.cols; k += classes+4+background+nuisance){
for(k = 0; k < pred.cols; k += per_box){
float scale = 1.;
int index = k/per_box;
int row = index / num_boxes;
int col = index % num_boxes;
if (nuisance) scale = 1.-pred.vals[j][k];
for (class = 0; class < classes; ++class){
int ci = k+classes+background+nuisance;
float left = pred.vals[j][ci + 0];
float right = pred.vals[j][ci + 1];
float top = pred.vals[j][ci + 2];
float bot = pred.vals[j][ci + 3];
printf("%d %d %f %f %f %f %f\n", (i-1)*m/splits + j, class, scale*pred.vals[j][k+class+background+nuisance], left, right, top, bot);
float y = (pred.vals[j][ci + 0] + row)/num_boxes;
float x = (pred.vals[j][ci + 1] + col)/num_boxes;
float h = pred.vals[j][ci + 2];
float w = pred.vals[j][ci + 3];
printf("%d %d %f %f %f %f %f\n", (i-1)*m/splits + j, class, scale*pred.vals[j][k+class+background+nuisance], y, x, h, w);
}
}
}