Loss-graph store automatically (iterations == max_batches) at the end of training

src/convolutional_layer.c

@@ -248,7 +248,7 @@ void cudnn_convolutional_setup(layer *l, int cudnn_preference)
 			//printf("Tensor Cores - Backward-filter enabled: l->bf_algo = CUDNN_CONVOLUTION_BWD_FILTER_ALGO_WINOGRAD_NONFUSED \n");
 
 		if (fw == 2 && bd == 2 && bf == 2) printf("TF ");
-		else if (fw >= 1 && bd >= 1 && bf >= 1) printf("TH ");
+		else if (fw == 1 && bd == 1 && bf == 1) printf("TH ");
 	}
 }
 #endif

src/detector.c

@@ -99,7 +99,7 @@ void train_detector(char *datacfg, char *cfgfile, char *weightfile, int *gpus, i
     args.hue = net.hue;
 
 #ifdef OPENCV
-	args.threads = 7;
+	args.threads = 3;
 	IplImage* img = NULL;
 	float max_img_loss = 5;
 	int number_of_lines = 100;

src/image.c

@@ -572,7 +572,7 @@ void draw_train_loss(IplImage* img, int img_size, float avg_loss, float max_img_
 	cvPutText(img, char_buff, pt1, &font, CV_RGB(0, 0, 0));
 	cvShowImage("average loss", img);
 	int k = cvWaitKey(20);
-	if (k == 's') cvSaveImage("chart.jpg", img, 0);
+	if (k == 's' || current_batch == (max_batches-1)) cvSaveImage("chart.jpg", img, 0);
 }
 #endif	// OPENCV