autodistill-detr 0.1.0

DETR module for use with Autodistill

Autodistill DETR Module

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

DETR is a transformer-based computer vision model you can use for object detection. Autodistill supports use of the DETR Resnet 50 model developed by Meta Research.

Read the full Autodistill documentation.

Read the DETR Autodistill documentation.

Installation

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

pip3 install autodistill-detr

Quickstart

from autodistill_detr import DETR

# define an ontology to map class names to our DETR 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 = DETR(
    ontology=CaptionOntology(
        {
            "person": "person",
            "a forklift": "forklift"
        }
    )
)
base_model.label("./context_images", extension=".jpg")

License

The code in this repository is licensed under an .

🏆 Contributing

We love your input! Please see the core Autodistill contributing guide to get started. Thank you 🙏 to all our contributors!