Maybe this may not be the place to ask this, but I am a beginner and I feel like someone here may think this is an easy question. I'll start with a little background. I am in the process of creating a Real-time object detection program that can detect some US traffic signs and maybe traffic lights. I have decided that openCV with the use of Keras/Tensorflow are probably my best options in achieving this goal. Within these I figured (I'm still new to this field) that transfer-learning on ImageNet would be my best option in building an image classifier. I have downloaded the LISA traffic sign data set and decided this is what I want to use for Transfer-learning on ImageNet. The part that's hanging me up in this whole process would be would it be better to show a street view with signs on it (this is what the LISA dataset contains) or just gather my own pictures (from the internet) of closeups of these signs. Also if any other part of my logic is flawed please let me know I am very interested in learning.
Thanks.