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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Deploy and scale serverless machine learning app - in 4 steps.
| Date | Stars |
|---|---|
| 2026-07-24 | 406 |
| 2026-07-25 | 406 |
| 2026-07-28 | 406 |
| 2026-07-30 | 406 |
| 2026-07-31 | 406 |
| 2026-08-06 | 405 |
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# Build and Deploy Cartoonify: a Serverless Machine Learning App <a href="https://www.buymeacoffee.com/ahmedbesbes" target="_blank"><img src="https://www.buymeacoffee.com/assets/img/custom_images/orange_img.png" alt="Buy Me A Coffee" style="height: 41px !important;width: 174px !important;box-shadow: 0px 3px 2px 0px rgba(190, 190, 190, 0.5) !important;-webkit-box-shadow: 0px 3px 2px 0px rgba(190, 190, 190, 0.5) !important;" ></a> This repo contains all the code needed to run, build and deploy Cartoonify: a toy app I made from scratch to turn your pictures into cartoons. <p align="center"> <img src="./images/demo_cartoonify.gif" width="40%"> </p> **Here's what motivated me in starting this project:** - Give GANs a try. I've been fascinated by these models lately. Trying the CartoonGAN model to turn your face into a cartoon seemed like real fun - Learn about deploying an application on a serverless architecture using different services of AWS (Lambda, API Gateway, S3, etc.) - Practice my React skills. I was so damn bored of Plotly, Dash and Streamlit. I wanted, for once, to build something custom and less mainstream - Use Netlify to deploy this React app. I saw demos of how easy this process was and I wanted to try it to convince myself If you're interested in this project, here's a short introduction 🎥 [](https://youtu.be/U3UjaRVRtWQ) # 0. Some prerequisites to build and deploy Cartoonify 🛠 If you want to run and deploy Cartoonify, here are some prerequisites first: - An AWS account (don't worry, deploying this app will cost you almost **nothing**) - A free account on Netlify - Docker installed on your machine - node and npm (preferably the latest versions) installed on your machine - torch and torchvision to test CartoonGAN locally (optional) All set? you're now ready to go. ### Testing cartoonGAN on Google colab check out `cartoongan/notebooks/standalone_cartoonify.ipynb` or online on [Colab](https://colab.research.google.com/drive/1Lq8mACJKP8TBxY-TJcsdyo_qul-OVdYc#scrollTo=ug2o6M2IqyAu) Please follow these four steps: # 1. Test CartoonGAN locally Some parts of the CartoonGan code as well as the pretrained models are borrowed from this [repo](https://github.com/Yijunmaverick/CartoonGAN-Test-Pytorch-Torch). A shout out to them for the great work! This is more of an exploratory step where you get to play with the pretrained models and try them (**so inference only**) on some sample images. If you're interested in the training procedure, have a look at the CartoonGAN [paper](https://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_CartoonGAN_Generative_Adversarial_CVPR_2018_paper.pdf) - Download the four pretrained models first. These weights will be loaded inside the Generator model defined in **`cartoongan/network/Transformer.py`** ```bash cd cartoongan bash download_pth.sh ``` - To test one of the four models, head over the notebook **`cartoongan/notebooks/CartoonGAN.ipynb`** and change the input image path to your test image. This notebook calls **`cartoongan/test_from_code.py`** script to make the transformation. ```bash cd cartoongan/notebooks jupyter notebook ```  _You can watch this section on Youtube to learn more about GANs and the CartoonGAN model_ <p align="center"> [](https://youtu.be/R86zP6Hf4Hk) </p> # 2. Deploy CartoonGAN on a serverless API using AWS Lambda The goal of this section is to deploy the CartoonGAN model on a serverless architecture so that it can be requested through an API endpoint ... from the internet :computer: ## Why does a serverless architecture matter? In a serverless architecture using Lambda functions, for example
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:89ca7a4a12050cea, topic:serverless
matched fp:89ca7a4a12050cea, topic:pytorch
matched fp:89ca7a4a12050cea, topic:computer-vision
matched fp:89ca7a4a12050cea, topic:gan