This is one of my projects using OpenAI's CLIP model to do interesting things. So the big credit goes to them!
I processed 2M images from the Unsplash dataset with CLIP and stored the feature vector representation of each photo (a 512 element vector). You can now encode a text query with CLIP in the same latent space and search the database.
I also tried doing some simple arithmetic with the feature vectors to combine the result of a search query and a photo. You can for example search for "Sydney Opera house" and give it a bight photo and you will get a photo of the Sydney Opera at night.
Wanted to give it a shot but it seems to fail when attempting to fetch the precomputed features - 504 Gateway Time-outs. Quota limits might have been reached?
Yeah, it's a 2 GB file, so it hits the quota limit on the Google Drive pretty fast. There is a problem with the mirror at transfer.army that I'll fix today.
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I also tried doing some simple arithmetic with the feature vectors to combine the result of a search query and a photo. You can for example search for "Sydney Opera house" and give it a bight photo and you will get a photo of the Sydney Opera at night.
You can directly jump to the Google Colab notebook if you want to give it a try: https://colab.research.google.com/github/haltakov/natural-la...
Wanted to give it a shot but it seems to fail when attempting to fetch the precomputed features - 504 Gateway Time-outs. Quota limits might have been reached?