Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Add section for community project #768

Merged
merged 1 commit into from
Dec 8, 2022
Merged

Add section for community project #768

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
9 changes: 9 additions & 0 deletions README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -299,6 +299,15 @@ For more information, refer to the [Logging Documentation](https://openvinotoolk

Note: Set your API Key for [Comet.ml](https://www.comet.com/signup?utm_source=anomalib&utm_medium=referral) via `comet_ml.init()` in interactive python or simply run `export COMET_API_KEY=<Your API Key>`

# Community Projects

## 1. Web-based Pipeline for Training and Inference

This project showcases an end-to-end training and inference pipeline build on top of Anomalib. It provides a web-based UI for uploading MVTec style datasets and training them on the available Anomalib models. It also has sections for calling inference on individual images as well as listing all the images with their predictions in the database.

You can view the project on [Github](https://github.com/vnk8071/anomaly-detection-in-industry-manufacturing/tree/master/anomalib_contribute)
For more details see the [Discussion forum](https://github.com/openvinotoolkit/anomalib/discussions/733)

# Datasets

`anomalib` supports MVTec AD [(CC BY-NC-SA 4.0)](https://creativecommons.org/licenses/by-nc-sa/4.0/) and BeanTech [(CC-BY-SA)](https://creativecommons.org/licenses/by-sa/4.0/legalcode) for benchmarking and `folder` for custom dataset training/inference.
Expand Down