https://github.com/autodistill/autodistill-blipv2

BLIPv2 model for use with Autodistill.

Science Score: 26.0%

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archival interactive transformers sequences projection generic observability autograding hacking shellcodes

Last synced: 11 months ago · JSON representation

Repository

BLIPv2 model for use with Autodistill.

Basic Info

Host: GitHub
Owner: autodistill
License: bsd-3-clause
Language: Python
Default Branch: main
Size: 11.7 KB

Statistics

Stars: 2
Watchers: 2
Forks: 0
Open Issues: 1
Releases: 0

Created about 3 years ago · Last pushed over 2 years ago

Metadata Files

Readme License

README.md

Autodistill BLIPv2 Module

This repository contains the code supporting the BLIPv2 base model for use with Autodistill.

BLIPv2, developed by Salesforce, is a computer vision model that supports visual question answering and zero-shot classification. Autodistill supports classifying images using BLIPv2.

Read the full Autodistill documentation.

Read the BLIPv2 Autodistill documentation.

Installation

To use BLIPv2 with autodistill, you need to install the following dependency:

bash pip3 install autodistill-blipv2

Quickstart

```python from autodistill_blip import BLIPv2

define an ontology to map class names to our BLIPv2 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

basemodel = BLIPv2( ontology=CaptionOntology( { "person": "person", "a forklift": "forklift" } ) ) basemodel.label("./context_images", extension=".jpeg") ```

License

This project is licensed under a 3-Clause BSD 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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Dependencies

setup.py pypi

autodistill *
numpy *
supervision *
torch *
transformers ==4.30.0