🚀 Your Turn!

The success of DeepEM Playground depends on its community. We invite Deep Learning (DL) experts to contribute their work and help advance the field of electron microscopy (EM).

Please make sure that you've read the provided info about our proposed workflow before getting started. You can also seek further inspiration from previousely implemented use cases.

📥 Get Started

Start immediately using the Lightning AI Studio template - no additional setup required. Click on the button above to dublicate the template in your own teamspace and get started right away.

If you prefer local development, we provide a GitHub template that includes the deepEM library, ensuring a standardized workflow and a consistent API across all Jupyter notebooks.

📖 Documentation

The deepEM library documentation is available here.

🐳 Quick Setup

For local development, we provide multiple setup options:

• Dockerfile and Docker image
• Conda-based environment.yml
• requirements.txt

📩 Submit Your Work

Submission Checklist

• ✅ Implementation
• Implementation of your own use case using the provided deepem library within either our GitHub template or Lightning AI Studios directly
• Adaptation of markdown descriptions within the .ipynbs to allow EM researchers to follow your use case as easily as possible
• ✅ Easy Setup
• Pip Provide a requirements.txt specifying tested Python, CUDA, and cuDNN versions, along with other needed dependencies. To generate the requirements.txt you can run pip freeze > requirements.txt
• Conda Provide an environment.yml for easy setup using Conda. To export the current active environment, you can run conda env export --no-builds > environment.yml
• Docker Provide a Docker image and a corresponding Dockerfile with all dependencies installed
• Either provide clear documentation on how to start this Docker image locally and run the Jupyter notebook
• Or directly add your code to the Docker and provide an access point with the Jupyter notebook
• ✅ Submission
• Lightning AI Studio Provide a link to your published Lightning AI Studio
• Github Provide a link to your code on GitHub with an easy-to-understand README.md.

Once your contribution is ready, publish it on Lightning AI Studios and notify the authors via mail. Provide them with the link to your Lighting AI Studio as well as github repository and possible additional info you wish to share or which can simplify the review process. We will review your submission and get back to you. If everything is set, we will link your use case to on the playgrounds website.