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https://github.com/autodistill/autodistill-grounding-dino

Grounding DINO module for use with Autodistill.

https://github.com/autodistill/autodistill-grounding-dino

Science Score: 13.0%

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    CITATION.cff file
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    Scientific vocabulary similarity
    Low similarity (11.1%) to scientific vocabulary

Keywords

autodistill autodistill-grounding-dino grounding-dino
Last synced: 11 months ago · JSON representation

Repository

Grounding DINO module for use with Autodistill.

Basic Info
  • Host: GitHub
  • Owner: autodistill
  • License: apache-2.0
  • Language: Python
  • Default Branch: main
  • Homepage: https://docs.autodistill.com
  • Size: 23.4 KB
Statistics
  • Stars: 22
  • Watchers: 4
  • Forks: 15
  • Open Issues: 8
  • Releases: 0
Topics
autodistill autodistill-grounding-dino grounding-dino
Created about 3 years ago · Last pushed about 2 years ago
Metadata Files
Readme License

README.md

Autodistill Grounding DINO Module

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

Grounding DINO is a zero-shot object detection model developed by IDEA Research. You can distill knowledge from Grounding DINO into a smaller model using Autodistill.

Read the Grounding DINO Autodistill documentation.

[!TIP] You can use Autodistill Grounding DINO on your own hardware, or use the Roboflow hosted version of Autodistill to label images in the cloud.

Installation

To use the Grounding DINO base model, you will need to install the following dependency:

bash pip3 install autodistill autodistill-yolov8 autodistill-grounding-dino

Quickstart

```python from autodistillgroundingdino import GroundingDINO from autodistill.detection import CaptionOntology from autodistill_yolov8 import YOLOv8

define an ontology to map class names to our GroundingDINO 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 = GroundingDINO(ontology=CaptionOntology({"shipping container": "container"}))

label all images in a folder called context_images

basemodel.label("./contextimages", extension=".jpeg") ```

License

The code in this repository is licensed under an Apache 2.0 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

Use bigger slower models to train smaller faster ones

GitHub Events

Total
  • Watch event: 4
  • Issue comment event: 2
  • Pull request event: 1
Last Year
  • Watch event: 4
  • Issue comment event: 2
  • Pull request event: 1

Committers

Last synced: over 1 year ago

All Time
  • Total Commits: 14
  • Total Committers: 4
  • Avg Commits per committer: 3.5
  • Development Distribution Score (DDS): 0.286
Past Year
  • Commits: 4
  • Committers: 3
  • Avg Commits per committer: 1.333
  • Development Distribution Score (DDS): 0.5
Top Committers
Name Email Commits
James Gallagher j****g@j****g 10
SolomonLake l****h@g****m 2
Dolzhenko Vladislav d****2@g****m 1
Alain Pilon a****n@g****m 1
Committer Domains (Top 20 + Academic)
jamesg.blog: 1

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 9
  • Total pull requests: 6
  • Average time to close issues: 21 days
  • Average time to close pull requests: 17 days
  • Total issue authors: 8
  • Total pull request authors: 5
  • Average comments per issue: 2.89
  • Average comments per pull request: 1.33
  • Merged pull requests: 4
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 2
  • Pull requests: 2
  • Average time to close issues: N/A
  • Average time to close pull requests: about 3 hours
  • Issue authors: 2
  • Pull request authors: 2
  • Average comments per issue: 1.5
  • Average comments per pull request: 1.5
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • Mars-204 (2)
  • NIRAVDEV (1)
  • gkadntmd (1)
  • SDonkelaarGDD (1)
  • sctrueew (1)
  • Dimacat-exe (1)
  • NapasinKuna (1)
  • yance-dev (1)
Pull Request Authors
  • SolomonLake (4)
  • P-stha12 (2)
  • djwessel (2)
  • Vdol22 (2)
  • AlainPilon (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 1,467 last-month
  • Total dependent packages: 1
  • Total dependent repositories: 3
  • Total versions: 7
  • Total maintainers: 2
pypi.org: autodistill-grounding-dino

GroundingDINO module for use with Autodistill

  • Versions: 7
  • Dependent Packages: 1
  • Dependent Repositories: 3
  • Downloads: 1,467 Last month
  • Docker Downloads: 0
Rankings
Docker downloads count: 4.6%
Downloads: 5.9%
Dependent repos count: 9.0%
Dependent packages count: 10.1%
Average: 12.3%
Forks count: 19.2%
Stargazers count: 25.1%
Maintainers (2)
yeldarb robolake
Last synced: 11 months ago

Dependencies

.github/workflows/publish.yml actions
  • actions/checkout v3 composite
  • actions/setup-python v2 composite
.github/workflows/test.yml actions
  • actions/checkout v3 composite
  • actions/setup-python v2 composite
.github/workflows/welcome.yml actions
  • actions/first-interaction v1.1.1 composite
setup.py pypi
  • autodistill *
  • numpy >=1.20.0
  • opencv-python >=4.6.0
  • rf_groundingdino *
  • rf_segment_anything *
  • supervision *
  • torch *