Data

Tools

Indexes

Applications

Experiments

Open Source Science

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

ViT module for use with autodistill.

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

Science Score: 13.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ○
    .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (10.5%) to scientific vocabulary

Keywords

autodistill computer-vision vision-transformer vit
Last synced: 6 months ago · JSON representation

Repository

ViT 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: 11.7 KB
Statistics
  • Stars: 5
  • Watchers: 2
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Topics
autodistill computer-vision vision-transformer vit
Created over 2 years ago · Last pushed over 2 years ago
Metadata Files
Readme License

README.md

Autodistill ViT Module

This repository contains the code supporting the ViT target model for use with Autodistill.

ViT is a classification model pre-trained on ImageNet-21k, developed by Google. You can train ViT classification models using Autodistill.

Read the full Autodistill documentation.

Read the ViT Autodistill documentation.

Installation

To use the ViT target model, you will need to install the following dependency:

bash pip3 install autodistill-vit

Quickstart

```python from autodistill_vit import ViT

target_model = ViT()

train a model from a classification folder structure

targetmodel.train("./contextimages_labeled/", epochs=200)

run inference on the new model

pred = targetmodel.predict("./contextimages_labeled/train/images/dog-7.jpg", conf=0.01) ```

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
Last Year

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 0
  • Total pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 0
  • Total pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
Pull Request Authors
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 33 last-month
  • Total dependent packages: 1
  • Total dependent repositories: 0
  • Total versions: 2
  • Total maintainers: 1
pypi.org: autodistill-vit

ViT module for use with Autodistill

  • Versions: 2
  • Dependent Packages: 1
  • Dependent Repositories: 0
  • Downloads: 33 Last month
Rankings
Dependent packages count: 7.2%
Downloads: 17.6%
Average: 25.8%
Forks count: 30.3%
Stargazers count: 32.3%
Dependent repos count: 41.3%
Maintainers (1)
yeldarb
Last synced: 6 months ago

Dependencies

.github/workflows/publish-to-pypi.yml actions
  • actions/checkout v3 composite
  • actions/setup-python v4 composite
  • pypa/gh-action-pypi-publish release/v1 composite
.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
  • Pillow *
  • autodistill *
  • numpy *
  • supervision ==0.9.0
  • torch *
  • transformers *