Try the Model

Use the widget below to experiment with MetaCLIP. You can detect COCO classes such as people, vehicles, animals, household items.

Overview

MetaCLIP is a zero-shot classification and embedding model developed by Meta AI.

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MetaCLIP License

MetaCLIP

is licensed under a

CC BY-NC 4.0

license.

Performance

Deploy a MetaCLIP API

You can use Roboflow Inference to deploy a

MetaCLIP

API on your hardware. You can deploy the model on CPU (i.e. Raspberry Pi, AI PCs) and GPU devices (i.e. NVIDIA Jetson, NVIDIA T4).

Below are instructions on how to deploy your own model API.

First, install Autodistill and Autodistill MetaCLP:


pip install autodistill autodistill-metaclip

Then, run:


from autodistill_metaclip import MetaCLIP

# define an ontology to map class names to our MetaCLIP prompt
# the ontology dictionary has the format {caption: class}
# where caption is the prompt sent to the base model, and class is the label that will
# be saved for that caption in the generated annotations
# then, load the model
base_model = MetaCLIP(
    ontology=CaptionOntology(
        {
            "person": "person",
            "a forklift": "forklift"
        }
    )
)

results = base_model.predict("./image.png")
print(results)

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Label Data Automatically with MetaCLIP

You can automatically label a dataset using MetaCLIP 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 MetaCLIP to train a computer vision model.

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