CLIP: Creating Image Classifiers Without Data

Imagine you need to classify whether people wear glasses, but you have no data or resources to train a custom model. In this tutorial, you will learn how to use a pre-trained CLIP model to create a custom classifier without any training required. This approach is known as Zero-Shot image classification, and it enables classifying images of classes that were not explicitly seen during the training of the original CLIP model. An easy-to-use Jupyter notebook with the full code is provided below for your convenience. The CLIP (Contrastive Language-Image Pre-training) model, developed by OpenAI, is a multi-modal vision and language model. It maps images and text descriptions to the same latent space, allowing it to determine whether an image and description match.