OrgLion-ML
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darknet
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Minor fix

This commit is contained in:
AlexeyAB 2020-02-14 18:28:10 +03:00
parent d51d89053a
commit 8dc4833e7f
5 changed files with 10 additions and 7 deletions
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2
src/dark_cuda.c
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@ -495,7 +495,7 @@ void show_cuda_cudnn_info()
CHECK_CUDA(cudaRuntimeGetVersion(&cuda_version));
CHECK_CUDA(cudaDriverGetVersion(&cuda_driver_version));
fprintf(stderr, " CUDA-version: %d (%d)", cuda_version, cuda_driver_version);
if(cuda_version < cuda_driver_version) fprintf(stderr, "\n Warning: CUDA-version is lower than Driver-version! \n");
if(cuda_version > cuda_driver_version) fprintf(stderr, "\n Warning: CUDA-version is higher than Driver-version! \n");
#ifdef CUDNN
fprintf(stderr, ", cuDNN: %d.%d.%d", CUDNN_MAJOR, CUDNN_MINOR, CUDNN_PATCHLEVEL);
#endif // CUDNN

5
src/detector.c
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@ -225,7 +225,10 @@ void train_detector(char *datacfg, char *cfgfile, char *weightfile, int *gpus, i
save_image(im, "truth11");
*/
printf("Loaded: %lf seconds\n", (what_time_is_it_now() - time));
const double load_time = (what_time_is_it_now() - time);
printf("Loaded: %lf seconds", load_time);
if (load_time > 0.1 && avg_loss > 0) printf(" - performance bottleneck on CPU or Disk HDD/SSD");
printf("\n");
time = what_time_is_it_now();
float loss = 0;

4
src/gaussian_yolo_layer.c
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@ -661,9 +661,9 @@ void forward_gaussian_yolo_layer(const layer l, network_state state)
uc_loss /= l.batch;
iou_loss /= l.batch;
printf("Region %d Avg IOU: %f, Class: %f, Obj: %f, No Obj: %f, .5R: %f, .75R: %f, count: %d, loss = %.2f, class_loss = %.2f, iou_loss = %.2f, uc_loss = %.2f \n",
printf("Region %d Avg IOU: %f, Class: %f, Obj: %f, No Obj: %f, .5R: %f, .75R: %f, count: %d, class_loss = %.2f, iou_loss = %.2f, uc_loss = %.2f, total_loss = %.2f \n",
state.index, avg_iou/count, avg_cat/class_count, avg_obj/count, avg_anyobj/(l.w*l.h*l.n*l.batch), recall/count, recall75/count, count,
loss, class_loss, iou_loss, uc_loss);
class_loss, iou_loss, uc_loss, loss);
}
void backward_gaussian_yolo_layer(const layer l, network_state state)

2
src/parser.c
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@ -1965,7 +1965,7 @@ network *load_network_custom(char *cfg, char *weights, int clear, int batch)
printf(" Try to load weights: %s \n", weights);
load_weights(net, weights);
}
//fuse_conv_batchnorm(*net);
fuse_conv_batchnorm(*net);
if (clear) (*net->seen) = 0;
return net;
}

4
src/yolo_layer.c
View File

@ -575,9 +575,9 @@ void forward_yolo_layer(const layer l, network_state state)
classification_loss /= l.batch;
iou_loss /= l.batch;
printf("v3 (%s loss, Normalizer: (iou: %f, cls: %f) Region %d Avg (IOU: %f, GIOU: %f), Class: %f, Obj: %f, No Obj: %f, .5R: %f, .75R: %f, count: %d, loss = %f, class_loss = %f, iou_loss = %f\n",
printf("v3 (%s loss, Normalizer: (iou: %.2f, cls: %.2f) Region %d Avg (IOU: %f, GIOU: %f), Class: %f, Obj: %f, No Obj: %f, .5R: %f, .75R: %f, count: %d, class_loss = %f, iou_loss = %f, total_loss = %f \n",
(l.iou_loss == MSE ? "mse" : (l.iou_loss == GIOU ? "giou" : "iou")), l.iou_normalizer, l.cls_normalizer, state.index, tot_iou / count, tot_giou / count, avg_cat / class_count, avg_obj / count, avg_anyobj / (l.w*l.h*l.n*l.batch), recall / count, recall75 / count, count,
loss, classification_loss, iou_loss);
classification_loss, iou_loss, loss);
}
void backward_yolo_layer(const layer l, network_state state)