I'm pretty new to ML so I apologize for the potentially trivial question; I've been unable to find a clear answer to my question.
Let's imagine that I want to build a model that is able to detect sharks in images. I put a camera in the water and hit record. I end up with thousands of images. Some of the frames depict a single shark, some depict several sharks, others depict 1 or more sharks among other objects such as fish and maybe even a random submarine.
Now, the question is: which of the images are most suitable, which should I throw away, and why?
For instance, must each individual training image contain ONE and ONLY ONE shark (each at slightly different angles, lighting, etc.)? Is an image/frame depicting several sharks OK (I imagine that would work for image classification, but not so well for object detection)? What about images that contain sharks and other objects/fish?
If someone can explain to me (even better if you have a link to a good resource), I would really appreciate it.