How can I detect the frame from video streaming that contains a graffiti on city wall? I am working on a graffiti detection project. I need to analyze data stream from a camera mounted sideways on a vehicle to identify graffiti on city walls and notify authorities with the single best capture of graffiti and its geolocation, etc. 

I am trying to use a ResNet50 model pre-trained on ImageNet using transfer learning for my graffiti image dataset. The classification will be done on an edge device as network connectivity may not be reliable.

Suppose I have a series of frames that have been detected to contain graffiti, as the vehicle goes past it, but I only need to report one image (so not all frames containing graffiti in the series). How can I do that? 

Ideally, I would like to report the frame where the camera is perpendicular to the wall. Why perpendicular? I think that images containing the graffiti when the camera is perpendicular to the wall will more clearly show the graffiti.
ResNet is an architecture for object recognition and you may use it to do your classification task.  Fast RCNN may improve your results but is a more difficult architecture to implement.  If you want to go in this direction the best place to start is the arxiv paper of the Fast R-CNN (arxiv.org/abs/1504.08083).  If I am not wrong, there is an implementation of fast-rcnn in pytorch if you really want that.

You seem to be new to deep learning.  I would strongly recommend starting simple. ResNet-50 will probably be more than enough for your application. Moreover, I suggest using a lib like fast.ai.