Industries today deal with ever increasing amounts of data. Especially in retail, fashion, and other industries where the image representation of products plays an important role. In such a situation, we can often descri… See more

CLIP architecture consists of two main components: (1) a text encoder, and (2) an Image encoder. These two encoders are jointly trained to predict the correct pairings of a batch of training (image, text) examples. … See more

Now that we know the architecture of CLIP and how it works, this section will walk you through all the steps to successfully implement two real-world scenarios. First, you will understand how to perform an image sear… See more

This approach using Pinecone has several advantages: → Simplicity: the querying approach is much simpler than the first approach, where the user has the full responsibility of managing the vector index. → Speed: … See more