General purpose computer vision APIs are good if you're looking for breadth of concepts across many categories. For example, if you're Shutterstock and you're t

General purpose computer vision APIs are good if you're looking for breadth of concepts across many categories. For example, if you're Shutterstock and you're trying to make images searchable with very widely used, generally accepted concepts like "flower" and "car" then a general model would be good enough for you. Custom computer vision models are good if you're looking for depth in certain categories. For example, if you're a gardening app and you want to take a pic of a flower and be able to recognize different species of flowers, then custom training is required. There are some options with computer vision API companies where they will let you do custom model training. IBM will do custom training as a service for $$$$ but if you don't want to pay like crazy, Clarifai has a free (to a certain point) offering that lets you train a custom image recognition model on your own https://developer.clarifai.com/guide/train#train https://developer.clarifai.com/guide/train#train