I want to train a model that will identify if the image is mushroom and non-mushroom.
If the image is mushroom, I will use another existing model to categorize if its poisonous or edible.
I want to know what kind of images should I use in training non-mushroom category.
In training a mushroom vs. non-mushroom image classifier, which images should comprise the negative class?
Only you can answer this question. The answer requires some careful thinking on your part, and it depends on what types of objects that you believe your classifier will encounter once deployed in the "real world". If you are only going to present "vegetation" to your classifier, then you probably only need to curate a mushroom (positive class) and plant (negative class) dataset. On the other hand, if there are no limits to what your classifier will encounter, then your training images for the non-mushroom class must include the visible universe (minus the mushrooms, of course). Ideally, your positive and negative class images should be collected in the same manner, at least how they would be collected when implemented.
