Pixera provides to create 'pixed' images for Pixel-Art. Pixera has two implementations for now. The first one is, Python Notebook in the examples directory can be used by developers who want to design their own trained model. You can also look at the GAN Example that I created. You can access full code of this project for free. Also don't forget to try Demo on pixera.
The second one offers pixel art conversion for your images, including pictures and sketches.
The pixera provides to change image type as you can see below. In this GAN Example, images in the dataset are arranged by passing through the pixera algorithm. Thus, pixel characters were created using the GAN algorithm. The trained models are available on the Huggingface.
| Directory | Contents |
|---|---|
data/ |
Scripts for the dataset. |
models/ |
Includes utilizer scripts. |
options/ |
Necessary options for the model. |
util/ |
Directory which includes method(s). |
git clone https://github.com/AlicanAKCA/pixera pip install -r requirements.txt python app.pyIt will have shown you an interface on your local host. Also, you can access full code and live Demo on Hugging Face Repo and pixera.app.
After running the app.py, will have shown you a link which provides to reach the interface.
http://127.0.0.1:7860/Hi there!
I am a Junior AI Developer with a passion for creating innovative solutions using cutting-edge technologies. I have experience in developing GAN models and I am currently working on a project called pixera, which aims to generate pixel art using deep learning techniques. I am excited about the potential of AI and its impact on society, and I am constantly exploring new ways to push the boundaries of what is possible. If you find my work valuable and would like to support me, you can buy me a coffee on BuyMeACoffee.
Thank you for your support!
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Copyright (C) Alican Akca. (Pixera Algorithm)
Suitable for commercial use.