I'm starting my first real data-science project, I made a reserach and want to ask if my approach is correct:
I HAVE: 600 photos of electronic components, hundreds of components in a single photograph, components shape and distance between them may vary between photographs but there is only 1 shape in a single photo. components shapes are squares, rectangles, ovals, "E"-shape and similar
I NEED: generic counter for components (no matter what is the type of elements on the photo)
PLANNED APPROACH: analyze each picture with openCV to gain predictions and then train CNN with Tensorflow and GPU (no previous experience).
is it the correct way of thinking?