I want to build a model which can count the number of coconuts in a heap. I am planning to manually collect data for this. I have found this interesting paper. Few questions I have.
I see that there is no way I can detect coconuts as a heap completely covers many coconuts inside. So I want to consider it as a regression problem.
- Which angle of the heap should I collect data? The top view (of the heap) seems to consider the height of the heap as well, but not easy to collect.
- Maybe I should start with a smaller fruit like lemon so that I can easily collect data and train and later do transfer learning on coconuts?
- A square image of 5 MP should be good enough for collecting? Or is it an overkill?
- Any place where I can get pre-trained weights to start with?
Please feel free to express your thoughts.