openai/CLIP

CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pairs. It can be instructed in natural language to predict the most relevant text snippet, given an image, without directly optimizing for the task, similarly to the zero-shot capabilities of GPT-2 and 3. We found CLIP matches the performance of the original ResNet50 on ImageNet "zero-shot" without using any of the original 1.28M labeled examples, overcoming several major challenges in computer vision. First, install PyTorch 1.7.1 and torchvision, as well as small additional dependencies, and then install this repo as a Python package. Returns the model and the TorchVision transform needed by the model, specified by the model name returned by clip.available_models(). The name argument can also be a path to a local checkpoint.