image-match is a simple (now Python 3!) package for finding approximate image matches from a corpus. It is similar, for instance, to pHash, but includes a database backend that easily scales to billions of images and supports sustained high rates of image insertion: up to 10,000 images/s on our cluster!
PLEASE NOTE: This algorithm is intended to find nearly duplicate images -- think copyright violation detection. It is NOT intended to find images that are conceptually similar. For more explanation, see this issue or this video.
Based on the paper An image signature for any kind of image, Wong et al. There is an existing reference implementation which may be more suited to your needs.
The folks over at Pavlov have released an excellent containerized version of image-match for easy scaling and deployment.
Once you're up and running, read these two (short) sections of the documentation to get a feel for what image-match is capable of: