torchvision by Ciro Santilli 40 Updated 2025-07-16
Contains several computer vision models, e.g. ResNet, all of them including pre-trained versions on some dataset, which is quite sweet.
TensorFlow quantum by Ciro Santilli 40 Updated 2025-07-16
Version of TensorFlow with a Cirq backend that can run in either quantum computers or classical computer simulations, with the goal of potentially speeding up deep learning applications on a quantum computer some day.
Ciro Santilli is very happy to meet people with related interests, he really loves his like-minded online friends. Even if you don't have something a specific goal in mind for the contact, please just say hi.
To contact Ciro publicly about any general subject that is not covered in a more specific GitHub repository, including saying hi or suggestions about his website either:
Publicly viewable contact is preferred if possible to more effectively share Ciro's wisdom with the world.
But if you feel more comfortable with private contact, no problem, either:
For other less good methods that will also likely work, use direct messages of the following profiles from under Section "Accounts controlled by Ciro Santilli":Ciro's Twitter DMs are also open, but note that Ciro receives endless Chinese language SPAM there which Twitter is doing nothing to combat, so it's not as reliable.
If you are a privacy freak or are going to tell Ciro state secrets Ciro has this GNU Privacy Guard public key: pubkey.gpg, but it's not something that he has ever really used.
Disqus comments were removed from his website in 2019-05-04, a manual dump is available here, removal rationale at: why Ciro Santilli removed Disqus comments from his website in 2019-05-04.
SVG 1.2 by Ciro Santilli 40 Updated 2025-07-16
Dropped in favor of SVG 2.
yolov5-pip by Ciro Santilli 40 Updated 2025-07-16
OK, now we're talking, two liner and you get a window showing bounding box object detection from your webcam feed!
python -m pip install -U yolov5==7.0.9
yolov5 detect --source 0
The accuracy is crap for anything but people. But still. Well done. Tested on Ubuntu 22.10, P51.
MNIST database by Ciro Santilli 40 Updated 2025-07-16
70,000 28x28 grayscale (1 byte per pixel) images of hand-written digits 0-9, i.e. 10 categories. 60k are considered training data, 10k are considered for test data.
Playing with it is the de-facto computer vision hello world.
It was on this dataset that Yann LeCun made great progress with the LeNet model. Running LeNet on MNIST has to be the most classic computer vision thing ever. See e.g. activatedgeek/LeNet-5 for a minimal and modern PyTorch educational implementation.
But it is important to note that as of the 2010's, the benchmark had become too easy for many applications. It is perhaps fair to say that the next big dataset revolution of the same importance was with ImageNet.
The dataset could be downloaded from yann.lecun.com/exdb/mnist/ but as of March 2025 it was down and seems to have broken from time to time randomly, so Wayback Machine to the rescue:
wget \
 https://web.archive.org/web/20120828222752/http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz \
 https://web.archive.org/web/20120828182504/http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz \
 https://web.archive.org/web/20240323235739/http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz \
 https://web.archive.org/web/20240328174015/http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz
but doing so is kind of pointless as both files use some crazy single-file custom binary format to store all images and labels. OMG!
Fashion MNIST by Ciro Santilli 40 Updated 2025-07-16
Same style as MNIST: 28x28 grayscale images, but with clothes rather than hand written digits.
It was designed to be much harder than MNIST, and more representative of modern applications, while still retaining the low resolution of MNIST for simplicity of training.
https://web.archive.org/web/20250511105702im_/https://github.com/zalandoresearch/fashion-mnist/raw/master/doc/img/fashion-mnist-sprite.png
If you are a pussy and work a soul crushing job, this is one way to lie to yourself that your life is still worth living: do one cool thing every day.
Find a time in which your mind hasn't yet been destroyed by useless work, usually in the morning before work, and do one thing you actually like in life.
Work a little less well for you boss, and a little better for yourself. Ross Ulbricht:
I hated working for someone else and trading my time for money with no investment in myself
Selling drugs online is not advisable however.
Even better, try to reach an official agreement with your employer to work 20% less than the standard work week. For example, you could work one day less every week, and do whatever you want on that day. It is not possible to push your passion to weekends, because your brain is too tired. "You keep all non-company-related IP you develop on that time" is a key clause obviously.
On a related note, good employers must allow employees to do whichever the fuck "crazy projects", "needed refactorings or other efficiency gains" and "learn things deeply" at least 20% of their time if employees want that: en.wikipedia.org/wiki/20%25_Project. Employees must choose if they want to do it one day a week or two hours per day. One day per month initiatives are bullshit. Another related name: genius hour.
Video 1.
I did it for me, Skyler
. Source. Pursuing a dream part time can make you feel afraid and tired. But at least, you will feel alive.
Maybe you will be fired, but long term, having tried, or even succeeded your dream, or a one of its side effects, will be infinitely more satisfying.
The same goes for school, and maybe even more so because your parents can still support you there. Some Gods who actually followed this advice and didn't end up living under a bridge:
Gandhi TODO source:
You can chain me, you can torture me, you can even destroy this body, but you will never imprison my mind
CIFAR-10 by Ciro Santilli 40 Updated 2025-07-16
60,000 tiny 32x32 color images in 10 different classes: airplanes, cars, birds, cats, deer, dogs, frogs, horses, ships, and trucks.
TODO release date.
This dataset can be thought of as an intermediate between the simplicity of MNIST, and a more full blown ImageNet.
https://web.archive.org/web/20250517192041im_/https://www.cs.toronto.edu/~kriz/cifar-10-sample/airplane1.png
https://web.archive.org/web/20250517192041im_/https://www.cs.toronto.edu/~kriz/cifar-10-sample/automobile1.png
https://web.archive.org/web/20250517192041im_/https://www.cs.toronto.edu/~kriz/cifar-10-sample/bird1.png
https://web.archive.org/web/20250517192041im_/https://www.cs.toronto.edu/~kriz/cifar-10-sample/cat1.png

Pinned article: Introduction to the OurBigBook Project

Welcome to the OurBigBook Project! Our goal is to create the perfect publishing platform for STEM subjects, and get university-level students to write the best free STEM tutorials ever.
Everyone is welcome to create an account and play with the site: ourbigbook.com/go/register. We belive that students themselves can write amazing tutorials, but teachers are welcome too. You can write about anything you want, it doesn't have to be STEM or even educational. Silly test content is very welcome and you won't be penalized in any way. Just keep it legal!
We have two killer features:
  1. topics: topics group articles by different users with the same title, e.g. here is the topic for the "Fundamental Theorem of Calculus" ourbigbook.com/go/topic/fundamental-theorem-of-calculus
    Articles of different users are sorted by upvote within each article page. This feature is a bit like:
    • a Wikipedia where each user can have their own version of each article
    • a Q&A website like Stack Overflow, where multiple people can give their views on a given topic, and the best ones are sorted by upvote. Except you don't need to wait for someone to ask first, and any topic goes, no matter how narrow or broad
    This feature makes it possible for readers to find better explanations of any topic created by other writers. And it allows writers to create an explanation in a place that readers might actually find it.
    Figure 1.
    Screenshot of the "Derivative" topic page
    . View it live at: ourbigbook.com/go/topic/derivative
  2. local editing: you can store all your personal knowledge base content locally in a plaintext markup format that can be edited locally and published either:
    This way you can be sure that even if OurBigBook.com were to go down one day (which we have no plans to do as it is quite cheap to host!), your content will still be perfectly readable as a static site.
    Figure 2.
    You can publish local OurBigBook lightweight markup files to either https://OurBigBook.com or as a static website
    .
    Figure 3.
    Visual Studio Code extension installation
    .
    Figure 4.
    Visual Studio Code extension tree navigation
    .
    Figure 5.
    Web editor
    . You can also edit articles on the Web editor without installing anything locally.
    Video 3.
    Edit locally and publish demo
    . Source. This shows editing OurBigBook Markup and publishing it using the Visual Studio Code extension.
    Video 4.
    OurBigBook Visual Studio Code extension editing and navigation demo
    . Source.
  3. https://raw.githubusercontent.com/ourbigbook/ourbigbook-media/master/feature/x/hilbert-space-arrow.png
  4. Infinitely deep tables of contents:
    Figure 6.
    Dynamic article tree with infinitely deep table of contents
    .
    Descendant pages can also show up as toplevel e.g.: ourbigbook.com/cirosantilli/chordate-subclade
All our software is open source and hosted at: github.com/ourbigbook/ourbigbook
Further documentation can be found at: docs.ourbigbook.com
Feel free to reach our to us for any help or suggestions: docs.ourbigbook.com/#contact