HI @cpeters , interesting points! My datasets vary in image quality (brightness, colors, etc) and in scene elements (cars, people, etc). I am working on a model to estimate a robot’s pose. In the first dataset, it is known that it lacks image sequences when the robot is at high speeds. Thus, I am trying to create another dataset to supplement the first one. However, in a different scenario and weather conditions (image quality). So, I am not sure if this strategy works. Maybe, I can merge both datasets and test the trained model in a separated dataset, just as you suggested. Do you think it is a reasonable alternative?