https://github.com/autodistill/autodistill-clip

CLIP module for use with Autodistill.
https://github.com/autodistill/autodistill-clip

autodistill clip image-classification

Last synced: 2 months ago
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CLIP module for use with Autodistill.

• Host: GitHub
• URL: https://github.com/autodistill/autodistill-clip
• Owner: autodistill
• License: mit
• Created: 2023-06-06T08:05:28.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-12-05T09:14:03.000Z (about 1 year ago)
• Last Synced: 2024-08-10T23:17:49.803Z (5 months ago)
• Topics: autodistill, clip, image-classification
• Language: Python
• Homepage: https://docs.autodistill.com
• Size: 14.6 KB
• Stars: 7
• Watchers: 4
• Forks: 1
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

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# Autodistill CLIP Module

This repository contains the code supporting the CLIP base model for use with [Autodistill](https://github.com/autodistill/autodistill).

[CLIP](https://github.com/openai/CLIP), developed by OpenAI, is a computer vision model trained using pairs of images and text. You can use CLIP with autodistill for image classification.

Read the full [Autodistill documentation](https://autodistill.github.io/autodistill/).

Read the [CLIP Autodistill documentation](https://autodistill.github.io/autodistill/base_models/clip/).

## Installation

To use CLIP with autodistill, you need to install the following dependency:

```bash

pip3 install autodistill-clip

```

## Quickstart

```python

from autodistill_clip import CLIP

from autodistill.detection import CaptionOntology

# define an ontology to map class names to our CLIP 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 = CLIP(

    ontology=CaptionOntology(

        {

            "person": "person",

            "a forklift": "forklift"

        }

    )

)

results = base_model.predict("./context_images/test.jpg")

print(results)

base_model.label("./context_images", extension=".jpeg")

```

## License

The code in this repository is licensed under an [MIT license](LICENSE.md).

## 🏆 Contributing

We love your input! Please see the core Autodistill [contributing guide](https://github.com/autodistill/autodistill/blob/main/CONTRIBUTING.md) to get started. Thank you 🙏 to all our contributors!