void test_dice(char *cfgfile, char *weightfile, char *filename)
{
network * net = parse_network_cfg(cfgfile);
if(weightfile){
load_weights(net, weightfile);
}
set_batch_network(net, 1);
srand(2222222);
int i = 0;
char **names = dice_labels;
char buff[256];
char *input = buff;
int indexes[6];
while(1){
if(filename){
strncpy(input, filename, 256);
}else{
printf("Enter Image Path: ");
fflush(stdout);
input = fgets(input, 256, stdin);
if(!input) return;
strtok(input, "\n");
}
image im = load_image_color(input, net->w, net->h);
float *X = im.data;
float *predictions = network_predict(net, X);
top_predictions(net, 6, indexes);
for(i = 0; i < 6; ++i){
int index = indexes[i];
printf("%s: %f\n", names[index], predictions[index]);
}
free_image(im);
if (filename) break;
}
}
void predict_classifier(char *datacfg, char *cfgfile, char *weightfile, char *filename)
{
network net = parse_network_cfg(cfgfile);
if(weightfile){
load_weights(&net, weightfile);
}
set_batch_network(&net, 1);
srand(2222222);
list *options = read_data_cfg(datacfg);
char *name_list = option_find_str(options, "names", 0);
if(!name_list) name_list = option_find_str(options, "labels", "data/labels.list");
int top = option_find_int(options, "top", 1);
int i = 0;
char **names = get_labels(name_list);
clock_t time;
int *indexes = calloc(top, sizeof(int));
char buff[256];
char *input = buff;
int size = net.w;
while(1){
if(filename){
strncpy(input, filename, 256);
}else{
printf("Enter Image Path: ");
fflush(stdout);
input = fgets(input, 256, stdin);
if(!input) return;
strtok(input, "\n");
}
image im = load_image_color(input, 0, 0);
image r = resize_min(im, size);
resize_network(&net, r.w, r.h);
printf("%d %d\n", r.w, r.h);
float *X = r.data;
time=clock();
float *predictions = network_predict(net, X);
top_predictions(net, top, indexes);
printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
for(i = 0; i < top; ++i){
int index = indexes[i];
printf("%s: %f\n", names[index], predictions[index]);
}
if(r.data != im.data) free_image(r);
free_image(im);
if (filename) break;
}
}
void test_tag(char *cfgfile, char *weightfile, char *filename)
{
network net = parse_network_cfg(cfgfile);
if(weightfile){
load_weights(&net, weightfile);
}
set_batch_network(&net, 1);
srand(2222222);
int i = 0;
char **names = get_labels("data/tags.txt");
clock_t time;
int indexes[10];
char buff[256];
char *input = buff;
int size = net.w;
while(1){
if(filename){
strncpy(input, filename, 256);
}else{
printf("Enter Image Path: ");
fflush(stdout);
input = fgets(input, 256, stdin);
if(!input) return;
strtok(input, "\n");
}
image im = load_image_color(input, 0, 0);
image r = resize_min(im, size);
resize_network(&net, r.w, r.h);
printf("%d %d\n", r.w, r.h);
float *X = r.data;
time=clock();
float *predictions = network_predict(net, X);
top_predictions(net, 10, indexes);
printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
for(i = 0; i < 10; ++i){
int index = indexes[i];
printf("%.1f%%: %s\n", predictions[index]*100, names[index]);
}
if(r.data != im.data) free_image(r);
free_image(im);
if (filename) break;
}
}
void test_captcha(char *cfgfile, char *weightfile, char *filename)
{
network net = parse_network_cfg(cfgfile);
if(weightfile){
load_weights(&net, weightfile);
}
set_batch_network(&net, 1);
srand(2222222);
int i = 0;
char **names = get_labels("/data/captcha/reimgs.labels.list");
char buff[256];
char *input = buff;
int indexes[26];
while(1){
if(filename){
strncpy(input, filename, 256);
}else{
//printf("Enter Image Path: ");
//fflush(stdout);
input = fgets(input, 256, stdin);
if(!input) return;
strtok(input, "\n");
}
image im = load_image_color(input, net.w, net.h);
float *X = im.data;
float *predictions = network_predict(net, X);
top_predictions(net, 26, indexes);
//printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
for(i = 0; i < 26; ++i){
int index = indexes[i];
if(i != 0) printf(", ");
printf("%s %f", names[index], predictions[index]);
}
printf("\n");
fflush(stdout);
free_image(im);
if (filename) break;
}
}
void test_imagenet(char *cfgfile, char *weightfile, char *filename)
{
network net = parse_network_cfg(cfgfile, 1);
if(weightfile){
load_weights(&net, weightfile);
}
set_batch_network(&net, 1);
srand(2222222);
int i = 0;
char **names = get_labels("data/shortnames.txt");
clock_t time;
int indexes[10];
char buff[256];
char *input = buff;
while(1){
if(filename){
strncpy(input, filename, 256);
}else{
printf("Enter Image Path: ");
fflush(stdout);
input = fgets(input, 256, stdin);
if(!input) return;
strtok(input, "\n");
}
image im = load_image_color(input, 256, 256);
float *X = im.data;
time=clock();
float *predictions = network_predict(net, X);
top_predictions(net, 10, indexes);
printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
for(i = 0; i < 10; ++i){
int index = indexes[i];
printf("%s: %f\n", names[index], predictions[index]);
}
free_image(im);
if (filename) break;
}
}
void demo_classifier(char *datacfg, char *cfgfile, char *weightfile, int cam_index, const char *filename)
{
#ifdef OPENCV
printf("Classifier Demo\n");
network *net = load_network(cfgfile, weightfile, 0);
set_batch_network(net, 1);
list *options = read_data_cfg(datacfg);
srand(2222222);
CvCapture * cap;
if(filename){
cap = cvCaptureFromFile(filename);
}else{
cap = cvCaptureFromCAM(cam_index);
}
int top = option_find_int(options, "top", 1);
char *name_list = option_find_str(options, "names", 0);
char **names = get_labels(name_list);
int *indexes = calloc(top, sizeof(int));
if(!cap) error("Couldn't connect to webcam.\n");
cvNamedWindow("Classifier", CV_WINDOW_NORMAL);
cvResizeWindow("Classifier", 512, 512);
float fps = 0;
int i;
while(1){
struct timeval tval_before, tval_after, tval_result;
gettimeofday(&tval_before, NULL);
image in = get_image_from_stream(cap);
image in_s = resize_image(in, net->w, net->h);
show_image(in, "Classifier");
float *predictions = network_predict(net, in_s.data);
if(net->hierarchy) hierarchy_predictions(predictions, net->outputs, net->hierarchy, 1, 1);
top_predictions(net, top, indexes);
printf("\033[2J");
printf("\033[1;1H");
printf("\nFPS:%.0f\n",fps);
for(i = 0; i < top; ++i){
int index = indexes[i];
printf("%.1f%%: %s\n", predictions[index]*100, names[index]);
}
free_image(in_s);
free_image(in);
cvWaitKey(10);
gettimeofday(&tval_after, NULL);
timersub(&tval_after, &tval_before, &tval_result);
float curr = 1000000.f/((long int)tval_result.tv_usec);
fps = .9*fps + .1*curr;
}
#endif
}
void gun_classifier(char *datacfg, char *cfgfile, char *weightfile, int cam_index, const char *filename)
{
#ifdef OPENCV
int bad_cats[] = {218, 539, 540, 1213, 1501, 1742, 1911, 2415, 4348, 19223, 368, 369, 370, 1133, 1200, 1306, 2122, 2301, 2537, 2823, 3179, 3596, 3639, 4489, 5107, 5140, 5289, 6240, 6631, 6762, 7048, 7171, 7969, 7984, 7989, 8824, 8927, 9915, 10270, 10448, 13401, 15205, 18358, 18894, 18895, 19249, 19697};
printf("Classifier Demo\n");
network *net = load_network(cfgfile, weightfile, 0);
set_batch_network(net, 1);
list *options = read_data_cfg(datacfg);
srand(2222222);
CvCapture * cap;
if(filename){
cap = cvCaptureFromFile(filename);
}else{
cap = cvCaptureFromCAM(cam_index);
}
int top = option_find_int(options, "top", 1);
char *name_list = option_find_str(options, "names", 0);
char **names = get_labels(name_list);
int *indexes = calloc(top, sizeof(int));
if(!cap) error("Couldn't connect to webcam.\n");
cvNamedWindow("Threat Detection", CV_WINDOW_NORMAL);
cvResizeWindow("Threat Detection", 512, 512);
float fps = 0;
int i;
while(1){
struct timeval tval_before, tval_after, tval_result;
gettimeofday(&tval_before, NULL);
image in = get_image_from_stream(cap);
image in_s = resize_image(in, net->w, net->h);
show_image(in, "Threat Detection");
float *predictions = network_predict(net, in_s.data);
top_predictions(net, top, indexes);
printf("\033[2J");
printf("\033[1;1H");
int threat = 0;
for(i = 0; i < sizeof(bad_cats)/sizeof(bad_cats[0]); ++i){
int index = bad_cats[i];
if(predictions[index] > .01){
printf("Threat Detected!\n");
threat = 1;
break;
}
}
if(!threat) printf("Scanning...\n");
for(i = 0; i < sizeof(bad_cats)/sizeof(bad_cats[0]); ++i){
int index = bad_cats[i];
if(predictions[index] > .01){
printf("%s\n", names[index]);
}
}
free_image(in_s);
free_image(in);
cvWaitKey(10);
gettimeofday(&tval_after, NULL);
timersub(&tval_after, &tval_before, &tval_result);
float curr = 1000000.f/((long int)tval_result.tv_usec);
fps = .9*fps + .1*curr;
}
#endif
}
void threat_classifier(char *datacfg, char *cfgfile, char *weightfile, int cam_index, const char *filename)
{
#ifdef OPENCV
float threat = 0;
float roll = .2;
printf("Classifier Demo\n");
network *net = load_network(cfgfile, weightfile, 0);
set_batch_network(net, 1);
list *options = read_data_cfg(datacfg);
srand(2222222);
CvCapture * cap;
if(filename){
cap = cvCaptureFromFile(filename);
}else{
cap = cvCaptureFromCAM(cam_index);
}
int top = option_find_int(options, "top", 1);
char *name_list = option_find_str(options, "names", 0);
char **names = get_labels(name_list);
int *indexes = calloc(top, sizeof(int));
if(!cap) error("Couldn't connect to webcam.\n");
//cvNamedWindow("Threat", CV_WINDOW_NORMAL);
//cvResizeWindow("Threat", 512, 512);
float fps = 0;
int i;
int count = 0;
while(1){
++count;
struct timeval tval_before, tval_after, tval_result;
gettimeofday(&tval_before, NULL);
image in = get_image_from_stream(cap);
if(!in.data) break;
image in_s = resize_image(in, net->w, net->h);
image out = in;
int x1 = out.w / 20;
int y1 = out.h / 20;
int x2 = 2*x1;
int y2 = out.h - out.h/20;
int border = .01*out.h;
int h = y2 - y1 - 2*border;
int w = x2 - x1 - 2*border;
float *predictions = network_predict(net, in_s.data);
float curr_threat = 0;
if(1){
curr_threat = predictions[0] * 0 +
predictions[1] * .6 +
predictions[2];
} else {
curr_threat = predictions[218] +
predictions[539] +
predictions[540] +
predictions[368] +
predictions[369] +
predictions[370];
}
threat = roll * curr_threat + (1-roll) * threat;
draw_box_width(out, x2 + border, y1 + .02*h, x2 + .5 * w, y1 + .02*h + border, border, 0,0,0);
if(threat > .97) {
draw_box_width(out, x2 + .5 * w + border,
y1 + .02*h - 2*border,
x2 + .5 * w + 6*border,
y1 + .02*h + 3*border, 3*border, 1,0,0);
}
draw_box_width(out, x2 + .5 * w + border,
y1 + .02*h - 2*border,
x2 + .5 * w + 6*border,
y1 + .02*h + 3*border, .5*border, 0,0,0);
draw_box_width(out, x2 + border, y1 + .42*h, x2 + .5 * w, y1 + .42*h + border, border, 0,0,0);
if(threat > .57) {
draw_box_width(out, x2 + .5 * w + border,
y1 + .42*h - 2*border,
x2 + .5 * w + 6*border,
y1 + .42*h + 3*border, 3*border, 1,1,0);
}
draw_box_width(out, x2 + .5 * w + border,
y1 + .42*h - 2*border,
x2 + .5 * w + 6*border,
y1 + .42*h + 3*border, .5*border, 0,0,0);
draw_box_width(out, x1, y1, x2, y2, border, 0,0,0);
for(i = 0; i < threat * h ; ++i){
float ratio = (float) i / h;
float r = (ratio < .5) ? (2*(ratio)) : 1;
float g = (ratio < .5) ? 1 : 1 - 2*(ratio - .5);
draw_box_width(out, x1 + border, y2 - border - i, x2 - border, y2 - border - i, 1, r, g, 0);
}
top_predictions(net, top, indexes);
char buff[256];
sprintf(buff, "/home/pjreddie/tmp/threat_%06d", count);
//save_image(out, buff);
printf("\033[2J");
printf("\033[1;1H");
printf("\nFPS:%.0f\n",fps);
for(i = 0; i < top; ++i){
int index = indexes[i];
printf("%.1f%%: %s\n", predictions[index]*100, names[index]);
}
if(1){
show_image(out, "Threat");
cvWaitKey(10);
}
free_image(in_s);
free_image(in);
gettimeofday(&tval_after, NULL);
timersub(&tval_after, &tval_before, &tval_result);
float curr = 1000000.f/((long int)tval_result.tv_usec);
fps = .9*fps + .1*curr;
}
#endif
}
void try_classifier(char *datacfg, char *cfgfile, char *weightfile, char *filename, int layer_num)
{
network *net = load_network(cfgfile, weightfile, 0);
set_batch_network(net, 1);
srand(2222222);
list *options = read_data_cfg(datacfg);
char *name_list = option_find_str(options, "names", 0);
if(!name_list) name_list = option_find_str(options, "labels", "data/labels.list");
int top = option_find_int(options, "top", 1);
int i = 0;
char **names = get_labels(name_list);
clock_t time;
int *indexes = calloc(top, sizeof(int));
char buff[256];
char *input = buff;
while(1){
if(filename){
strncpy(input, filename, 256);
}else{
printf("Enter Image Path: ");
fflush(stdout);
input = fgets(input, 256, stdin);
if(!input) return;
strtok(input, "\n");
}
image orig = load_image_color(input, 0, 0);
image r = resize_min(orig, 256);
image im = crop_image(r, (r.w - 224 - 1)/2 + 1, (r.h - 224 - 1)/2 + 1, 224, 224);
float mean[] = {0.48263312050943, 0.45230225481413, 0.40099074308742};
float std[] = {0.22590347483426, 0.22120921437787, 0.22103996251583};
float var[3];
var[0] = std[0]*std[0];
var[1] = std[1]*std[1];
var[2] = std[2]*std[2];
normalize_cpu(im.data, mean, var, 1, 3, im.w*im.h);
float *X = im.data;
time=clock();
float *predictions = network_predict(net, X);
layer l = net->layers[layer_num];
for(i = 0; i < l.c; ++i){
if(l.rolling_mean) printf("%f %f %f\n", l.rolling_mean[i], l.rolling_variance[i], l.scales[i]);
}
#ifdef GPU
cuda_pull_array(l.output_gpu, l.output, l.outputs);
#endif
for(i = 0; i < l.outputs; ++i){
printf("%f\n", l.output[i]);
}
/*
printf("\n\nWeights\n");
for(i = 0; i < l.n*l.size*l.size*l.c; ++i){
printf("%f\n", l.filters[i]);
}
printf("\n\nBiases\n");
for(i = 0; i < l.n; ++i){
printf("%f\n", l.biases[i]);
}
*/
top_predictions(net, top, indexes);
printf("%s: Predicted in %f seconds.\n", input, sec(clock()-time));
for(i = 0; i < top; ++i){
int index = indexes[i];
printf("%s: %f\n", names[index], predictions[index]);
}
free_image(im);
if (filename) break;
}
}
