Reputation: 372
Here is the effect I am trying to achieve - Imagine a user submits an image, then a python script to cycle through each JPEG/PNG for a similar image in the current working directory.
Close to how Google image search works (when you submit your image and it returns similar ones). Should I use PIL or OpenCV?
Preferably using Python3.4 by the way, but Python 2.7 is fine.
Wilson
Upvotes: 13
Views: 14587
Reputation: 1694
I created the undouble library in Python which seems a match for your issue.
It uses Hash functions to detect (near-)identical images in for example a directory. It works using a multi-step process of pre-processing the images (grayscaling, normalizing, and scaling), computing the image hash, and the grouping of images based on a threshold value.
Upvotes: 0
Reputation: 1121
I mean, why not use both? It's trivial to convert PIL images into OpenCV images and vice-versa, and both have niche functions that can make your life easier. Pair them up with sklearn and numpy, and you're cooking with gas.
Upvotes: 1