diff --git a/Makefile b/Makefile
index 0a9d42bb503..3f10ed353ae 100644
--- a/Makefile
+++ b/Makefile
@@ -23,6 +23,9 @@ OS := $(shell uname)
 # Tesla V100
 # ARCH= -gencode arch=compute_70,code=[sm_70,compute_70]
 
+# GeForce RTX 2080 Ti, RTX 2080, RTX 2070	Quadro RTX 8000, Quadro RTX 6000, Quadro RTX 5000	Tesla T4
+# ARCH= -gencode arch=compute_75,code=[sm_75,compute_75]
+
 # Jetson XAVIER
 # ARCH= -gencode arch=compute_72,code=[sm_72,compute_72]
 
diff --git a/README.md b/README.md
index 8de98c29df9..dc4bf62941a 100644
--- a/README.md
+++ b/README.md
@@ -370,7 +370,7 @@ If you made you custom model that isn't based on other models, then you can trai
  
 ## When should I stop training:
 
-Usually sufficient 2000 iterations for each class(object). But for a more precise definition when you should stop training, use the following manual:
+Usually sufficient 2000 iterations for each class(object), but not less than 4000 iterations in total. But for a more precise definition when you should stop training, use the following manual:
 
 1. During training, you will see varying indicators of error, and you should stop when no longer decreases **0.XXXXXXX avg**:
 
diff --git a/src/http_stream.cpp b/src/http_stream.cpp
index 57feea0e6b9..c6ace438d42 100644
--- a/src/http_stream.cpp
+++ b/src/http_stream.cpp
@@ -322,6 +322,11 @@ image image_data_augmentation(IplImage* ipl, int w, int h,
         sized *= dexp;
     }
 
+    //std::stringstream window_name;
+    //window_name << "augmentation - " << ipl;
+    //cv::imshow(window_name.str(), sized);
+    //cv::waitKey(0);
+
     // Mat -> IplImage -> image
     IplImage src = sized;
     image out = ipl_to_image(&src);