https://github.com/autodistill/autodistill-vlpart
VLPart model for use with Autodistill.
Science Score: 13.0%
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Low similarity (11.5%) to scientific vocabulary
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Repository
VLPart model for use with Autodistill.
Basic Info
- Host: GitHub
- Owner: autodistill
- License: mit
- Language: Python
- Default Branch: main
- Homepage: https://docs.autodistill.com
- Size: 24.4 KB
Statistics
- Stars: 4
- Watchers: 2
- Forks: 0
- Open Issues: 0
- Releases: 0
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Metadata Files
README.md
Autodistill VLPart Module
This repository contains the code supporting the VLPart base model for use with Autodistill.
VLPart, developed by Meta Research, is an object detection and segmentation model that works with an open vocabulary. autodistill-vlpart enables you to use VLPart to auto-label images for use in training a fine-tuned model. autodistill-vlpart supports the LVIS vocabulary.
Read the full Autodistill documentation.
Read the VLPart Autodistill documentation.
Installation
To use VLPart with autodistill, you need to install the following dependency:
bash
pip3 install autodistill-vlpart
Quickstart
```python from autodistill_vlpart import VLPart from autodistill.detection import CaptionOntology from autodistill.utils import plot
define an ontology to map class names to our VLPart 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 = VLPart( ontology=CaptionOntology( { "person": "person" } ) )
predictions = base_model.predict("./image.png")
print(predictions)
plot( image=cv2.imread("./image.png"), classes=basemodel.classnames, detections=predictions )
label the images in the context_images folder
basemodel.label("./contextimages", extension=".jpeg") ```
License
This project is licensed under an MIT license.
🏆 Contributing
We love your input! Please see the core Autodistill contributing guide to get started. Thank you 🙏 to all our contributors!
Owner
- Name: Autodistill
- Login: autodistill
- Kind: organization
- Email: autodistill@roboflow.com
- Website: https://autodistill.com
- Repositories: 1
- Profile: https://github.com/autodistill
Use bigger slower models to train smaller faster ones
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- Total versions: 2
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pypi.org: autodistill-vlpart
VLPart for use with Autodistill
- Homepage: https://github.com/autodistill/autodistill-vlpart
- Documentation: https://autodistill-vlpart.readthedocs.io/
- License: MIT License
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Latest release: 0.1.1
published over 2 years ago