Models

What is OpenAI CLIP?

CLIP (Contrastive Language-Image Pre-Training) is an impressive multimodal zero-shot image classifier that achieves impressive results in a wide range of domains with no fine-tuning. It applies the recent advancements in large-scale transformers like GPT-3 to the vision arena.

About the model

Here is an overview of the

OpenAI CLIP

model:

Date of Release Jan 05, 2021
Model Type Classification
Architecture
Framework Used PyTorch
Annotation Format OpenAI CLIP Classification
Stars on GitHub 11000+

What is CLIP?

In January 2021 OpenAI released CLIP (Contrastive Language-Image Pre-Training), a zero-shot classifier that leverages knowledge of the English language to classify images without having to be trained on any specific dataset. It applies the recent advancements in large-scale transformers like GPT-3 to the vision arena.

The results are extremely impressive; we have put together a CLIP tutorial and a CLIP Colab notebook for you to experiment with the model on your own images.

CLIP's Performance

Training Efficiency: CLIP is among one of the most efficient models with an accuracy of 41% at 400 million images, outperforming other models such as the Bag of Words Prediction (27%) and the Transformer Language Model (16%) at the same number of images. This means that CLIP trains much faster than other models within the same domain.

CLIP's Training Efficiency

Generalization: CLIP has been trained with such a wide array of image styles that it is far more flexible and than other models like ImageNet. It is important to note that CLIP generalizes well with images that it was trained on, not images outside of its training domain. Pictured below are some of the different image styles:

CLIP's Generalization

Further Reading Over OpenAI CLIP

Using OpenAI CLIP: https://blog.roboflow.com/how-to-use-openai-clip/

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Model Performance

Explore this model on Roboflow

Deploy OpenAI CLIP to production

Roboflow offers a range of SDKs with which you can deploy your model to production.

OpenAI CLIP Annotation Format

OpenAI CLIP

uses the

uses the

OpenAI CLIP Classification

annotation format. If your annotation is in a different format, you can use Roboflow's annotation conversion tools to get your data into the right format.

Convert data between formats

Label data automatically with OpenAI CLIP

You can automatically label a dataset using

OpenAI CLIP

with help from Autodistill, an open source package for training computer vision models. You can label a folder of images automatically with only a few lines of code. Below, see our tutorials that demonstrate how to use

OpenAI CLIP

to train a computer vision model.

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