4 ms·
Cool website! Can you go through how you set up the whole thing?
by lovestodonothin 8y ago
Cool website! Can you go through how you set up the whole thing?
- anotheryou 8y agoI'm pretty sure it's based on the fast.ai course. Their current set-up tutorial is outdated and doesn't work though. In the forums there is a pinned thread about a docker build that works nicely on https://render.com/ https://render.com/ fork repo, replace ML model, change html content, link to render, done https://course.fast.ai/deployment_render.html https://course.fast.ai/deployment_render.html
- gcarvalho 8y agoThank you. I actually didn’t base it on fast.ai. It went on like so: - I scraped from google images using queries like “ripe bananas”, “green bananas”, etc - Filtered out garbage images and labeled the remaining with the help of someone - Trained the model (very straight forward with Keras). The code in the notebook is something like 30 lines I think. - Using tf.js was what took me the longest. Using tensorflowjs_converter.save_model outputs an incompatible or corrupted file. Saving it first with keras and then using the tensorflowjs_converter CLI tool is what worked. The web-ui code is also available in the repo. - Lastly. It is served from GitHub pages (not a problem since everything is static and runs client side), with a custom freenom domain (on a convenient .ml tld) and through cloudflare’s DNS which gives me SSL on a custom domain, caching and some very basic analytics. Everything free tier. It only cost me time (around 5h I think). Did I miss anything you wanted to know?