My model deals with videos, and I want to calculate how fast it can process frames as in frames per second or processing time for 1 frame.
I have made a single function to get predictions, it takes in raw frames as input, does all the preprocessing, and returns the classification. One of the preprocessing steps is sampling the frames from the video, basically, it reduces the number of frames which go into the deep learning model by 1/5. Without all the preprocessing, the model won't perform as expected.
So my question is, should I consider the preprocessing time aswell? And, most importantly, is this processing time for all frames or just for the frames the model actually sees?
Example: Input is of 50 frames, and total time taken to preprocess them and make predictions is 1 second. So, the processing time for 1 frame is 1/50seconds. OR Should it be 1/10seconds, as model only gets to process 10 frames, others simply get skipped in preprocessing.
Which way is the standard way or the right way?