I have roughly 30,000 images of two categories, which are 'crops' and 'weeds.' An example of what I have can be found below:
The goal will use my training images to detect weeds among crops, given an orthomosaic GIS image of a given field. I guess you could say that I'm trying to detect certain objects in the field.
As I'm new to deep learning, how would one go about generating training labels for this task? Can I just label the entire photo as a 'weed' using some type of text file, or do I actually have to draw bounding boxes (around weeds) on each image that will be used for training? If so, is there an easier way than going through all 30,000 of my images?
I'm very new to this, so any specific details would really help a lot!