How CLIP Processes Images and Text
At the core of CLIP's functionality is its ability to process images and text through distinct yet complementary methods. Images are fed into a vision transformer, a type of neural network specifically designed to handle visual data. Meanwhile, text is processed using a transformer language model, which is adept at understanding and generating human language. Both the vision and language transformers produce embeddings, which are numerical representations of the image and text data. By using contrastive learning, CLIP aligns these embeddings, allowing the model to understand the relationship between visual and textual information. This process is what enables CLIP to perform tasks such as identifying images based on text descriptions, demonstrating its powerful cross-modal capabilities.