Image Similarity Search | Vision Transformer + Qdrant Vector Database
This video shows Python code for image similarity search - using Qdrant as the Vector Database and a free vision transformer model : ViT Model 'facebook/dino-vits16'
This is all free. No need for a paid AI service such as OpenAI. Unlike many tutorials and videos, this uses a custom dataset, rather than the usual ready made one. I have used some Real Estate Property images from a Kaggle collection, but you could just as easily add your own and modify the metadata accordingly. I introduce the project at the start, and then the second half is a sequence of me demonstrating it. It did have some audio commentary, but it was poor quality so I removed it. Apologies!
🟩 Here is the short follow up video , showing just the code to make the search :
🔗 • Image Similarity (AI) | Qdrant
🟩 The process of finding similar images
🔗 https://huggingface.co/blog/image-sim...
chapters -
00:00 intro - Real Estate Image Similarity Search
02:32 making a dataset
03:27 metadata
10:21 import dataset
12:22 source image
14:12 run code
16:33 qdrant actix vector database (Docker)
18:48 hugging face usage tips
Useful Links:
🟩 Vision Transformer (ViT)
---------------------------------------------
🔗 https://huggingface.co/docs/transform...
🔗 https://huggingface.co/docs/datasets/...
🟩 Loading Script
-----------------------------
🔗 https://huggingface.co/docs/datasets/...
🟩 Qdrant
----------------
🔗 https://qdrant.tech/
🔗 https://qdrant.tech/documentation/con...
🔗 https://colab.research.google.com/git...
Pytorch
🔗 https://pytorch.org/get-started/locally/
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