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Fixed xnor for random=1

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This commit is contained in:
AlexeyAB
2018-05-19 16:52:05 +03:00
parent 94c84da850
commit c1bb8c129d
2 changed files with 40 additions and 1 deletions
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9
src/convolutional_layer.c
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@ -465,6 +465,10 @@ void resize_convolutional_layer(convolutional_layer *l, int w, int h)
l->x_norm = realloc(l->x_norm, l->batch*l->outputs*sizeof(float)); l->x_norm = realloc(l->x_norm, l->batch*l->outputs*sizeof(float));
} }
if (l->xnor) {
//l->binary_input = realloc(l->inputs*l->batch, sizeof(float));
}
#ifdef GPU #ifdef GPU
if (old_w < w || old_h < h) { if (old_w < w || old_h < h) {
cuda_free(l->delta_gpu); cuda_free(l->delta_gpu);
@ -480,6 +484,11 @@ void resize_convolutional_layer(convolutional_layer *l, int w, int h)
l->x_gpu = cuda_make_array(l->output, l->batch*l->outputs); l->x_gpu = cuda_make_array(l->output, l->batch*l->outputs);
l->x_norm_gpu = cuda_make_array(l->output, l->batch*l->outputs); l->x_norm_gpu = cuda_make_array(l->output, l->batch*l->outputs);
} }
if (l->xnor) {
cuda_free(l->binary_input_gpu);
l->binary_input_gpu = cuda_make_array(0, l->inputs*l->batch);
}
} }
#ifdef CUDNN #ifdef CUDNN
cudnn_convolutional_setup(l, cudnn_fastest); cudnn_convolutional_setup(l, cudnn_fastest);

32
src/detector.c
View File

@ -1109,12 +1109,42 @@ void test_detector(char *datacfg, char *cfgfile, char *weightfile, char *filenam
detection *dets = get_network_boxes(&net, im.w, im.h, thresh, hier_thresh, 0, 1, &nboxes, letterbox); detection *dets = get_network_boxes(&net, im.w, im.h, thresh, hier_thresh, 0, 1, &nboxes, letterbox);
if (nms) do_nms_sort(dets, nboxes, l.classes, nms); if (nms) do_nms_sort(dets, nboxes, l.classes, nms);
draw_detections_v3(im, dets, nboxes, thresh, names, alphabet, l.classes, ext_output); draw_detections_v3(im, dets, nboxes, thresh, names, alphabet, l.classes, ext_output);
free_detections(dets, nboxes);
save_image(im, "predictions"); save_image(im, "predictions");
if (!dont_show) { if (!dont_show) {
show_image(im, "predictions"); show_image(im, "predictions");
} }
/*
// pseudo labeling concept - fast.ai
{
char labelpath[4096];
find_replace(input, ".jpg", ".txt", labelpath);
find_replace(labelpath, ".png", ".txt", labelpath);
find_replace(labelpath, ".bmp", ".txt", labelpath);
find_replace(labelpath, ".JPG", ".txt", labelpath);
find_replace(labelpath, ".JPEG", ".txt", labelpath);
find_replace(labelpath, ".ppm", ".txt", labelpath);
FILE* fw = fopen(labelpath, "wb");
int i;
for (i = 0; i < nboxes; ++i) {
char buff[1024];
int class_id = -1;
float prob = 0;
for (j = 0; j < l.classes; ++j) {
if (dets[i].prob[j] > thresh && dets[i].prob[j] > prob) {
prob = dets[i].prob[j];
class_id = j;
}
}
if (class_id >= 0) {
sprintf(buff, "%d %2.4f %2.4f %2.4f %2.4f\n", class_id, dets[i].bbox.x, dets[i].bbox.y, dets[i].bbox.w, dets[i].bbox.h);
fwrite(buff, sizeof(char), strlen(buff), fw);
}
}
fclose(fw);
}
*/
free_detections(dets, nboxes);
free_image(im); free_image(im);
free_image(sized); free_image(sized);
//free(boxes); //free(boxes);