Description: Currently, the image embeddings are added to the FAISS index using the inner product similarity (IndexFlatIP). However, for accurate cosine similarity comparison, the embeddings need to be normalized to unit vectors. This normalization ensures that the inner product will directly correspond to cosine similarity.
Outcome: The embeddings are normalized to unit vectors, ensuring they represent cosine similarity when using the FAISS index with IndexFlatIP.
Description: Currently, the image embeddings are added to the FAISS index using the inner product similarity (IndexFlatIP). However, for accurate cosine similarity comparison, the embeddings need to be normalized to unit vectors. This normalization ensures that the inner product will directly correspond to cosine similarity.
Outcome: The embeddings are normalized to unit vectors, ensuring they represent cosine similarity when using the FAISS index with IndexFlatIP.