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.
To use BLIPv2 with autodistill, you need to install the following dependency:
pip3 install autodistill-blipv2
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
base_model = BLIPv2(
ontology=CaptionOntology(
{
"person": "person",
"a forklift": "forklift"
}
)
)
base_model.label("./context_images", extension=".jpeg")
This project is licensed under a 3-Clause BSD license.
We love your input! Please see the core Autodistill contributing guide to get started. Thank you 🙏 to all our contributors!