Image Similarity Search with VGG16 and Cosine Distance in python.
This is a walkthrough python tutorial for image similarity search using VGG16 as feature extractor and cosine distance as a metric for similarity.
Cosine Similarity can be used to compare vectors:
- Cosine similarity compares how "aligned" two vectors are (like comparing directions they point)
- It measures the cosine of the angle between two vectors:
- Formula: cos(θ) = (A·B)/(||A||·||B||)
- Result ranges from -1 (opposite) to 1 (identical)
- Value of 0 indicates perpendicularity (no similarity)
- We compare query vector against all database vectors
Link to python code: https://github.com/bnsreenu/python_for_microscopists/tree/master/348-Image%20similarity%20using%20VGG16%20and%20cosine%20distance