ipeevski/research-poster-animeganv2-App

⚡️ Anime Converter (AnimeGANV2 research poster)

This app is a research poster demo of AnimeGANv2 paper. It showcasese the paper, blog, noteboo,k and model demo where you can upload an image and convert it into Anime. To create a research poster for your work use the Lightning Research Template app.

Important Links:

• Paper
• Github official
• Github PyTorch Implementation
• Blog
• Colab Notebook

Getting started

To create a Research Poster you can install this app via the Lightning CLI or use the template from GitHub and manually install the app as mentioned below.

Installation

With Lightning CLI

lightning install app lightning/anime-converter

Once you have installed the app, you can goto the research-poster-animeganv2 folder and run lightning run app app.py --cloud from terminal. This will launch the template app in your default browser with tabs containing research paper, blog, Training logs, and Model Demo.

You should see something like this in your browser:

You can modify the content of this app and customize it to your research. At the root of this template, you will find app.py that contains the ResearchApp class. This class provides arguments like a link to a paper, a blog, and whether to launch a Gradio demo. You can read more about what each of the arguments does in the docstrings.

Highlights

• Provide the link for paper, blog, or training logger like WandB as an argument, and ResearchApp will create a tab for each.
• Make a poster for your research by editing the markdown file in the resources folder.
• Add interactive model demo with Gradio app, update the gradio component present in the [research_app ( ./research_app/components/model_demo.py) folder.
• View a Jupyter Notebook or launch a fully-fledged notebook instance (Sharing a Jupyter Notebook instance can expose the cloud instance to security vulnerability.)
• Reorder the tab layout using the tab_order argument.

Example

# update app.py at the root of the repo
import lightning as L

paper = "https://arxiv.org/pdf/2103.00020.pdf"
blog = "https://openai.com/blog/clip/"
github = "https://github.com/mlfoundations/open_clip"
wandb = "https://wandb.ai/aniketmaurya/herbarium-2022/runs/2dvwrme5"

app = L.LightningApp(
    ResearchApp(
        poster_dir="resources",
        paper=paper,
        blog=blog,
        training_log_url=wandb,
        github=github,
        notebook_path="resources/Interacting_with_CLIP.ipynb",
        launch_gradio=True,
    )
)