Hello there 👋, This is a showcase of a project I’ve been working on for the past weeks. It’s a simple cross-platform desktop application that allows you to tag images using a machine learning model that I’ve trained. It is written in C# using Avalonia UI, and it uses the FastAI library for the machine learning part, the model is then converted to ONNX. The application is available for Windows, Linux and MacOS....
Hello there 👋, In this post, I will show you how to convert a FastAI model to ONNX and CoreML. Convert a FastAI model to Pytorch Before we can convert the model to ONNX format or CoreML, we need to convert it to Pytorch first. This is a simple process. Assuming that the model is trained, we need to call torch.save to export the model: from fastai.vision.all import * # learn is your FastAI Learner torch....
Hello everyone! 👋 This is a follow-up post to the previous one, long story short I started taking the course from fast.ai to learn more about Deep Learning. I’ve built a simple Image Tagging model using the Resnet architecture (don’t worry about the paper I did not read it, GitHub Copilot suggested it while writing this blog post). FastAI is a high-level Python library that allows you to train complex ML models really fast and efficiently....
Hello everyone 👋, I’ve been playing with FastAI and deep learning for a week or so and I’ve decided to combine my passion for software with my passion for photography. I’m working on an app or maybe a library that allows you to generate tags for a photo. For an amateur photographer like me it’s quite useful as I don’t always have inspiration to write tags for my photos and sometimes the tags I write are inconsistent....
Hello everyone 👋, In this quick post I’ll show you how to deploy a FastAI model using FastAPI. It’s a follow-up to my previous post from here and it is partially based on this FastAI lecture: Exporting the Model Before we create the API, we need to export the model as a pickle file. Add learn.export("<path>/cat_or_dog.pkl") with the full absolute export path at the end of the script: # ... learn = vision_learner(dls, resnet34, metrics=error_rate) learn....
Hello everyone 👋, This is my first blog post about AI, it’s a quick post on how to enable GPU support for the FastAI library. I have avoided getting into AI for some time now, I thought that it would involve lots of complicated math, and I was not sure that it would be worth the effort, I did not get very good grates in my college math classes 😅....