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sudo apt install pybind11-dev

git clone https://github.com/mlcommons/inference
cd inference
git checkout v2.1

virtualenv -p python3 .venv
. .venv/bin/activate
pip install numpy==1.24.2 pycocotools==2.0.6 onnxruntime==1.14.1 opencv-python==4.7.0.72 torch==1.13.1

cd loadgen
CFLAGS="-std=c++14" python setup.py develop
cd -

cd vision/classification_and_detection
python setup.py develop
wget -q https://zenodo.org/record/3157894/files/mobilenet_v1_1.0_224.onnx
export MODEL_DIR="$(pwd)"
export EXTRA_OPS='--time 10 --max-latency 0.2'

tools/make_fake_imagenet.sh
DATA_DIR="$(pwd)/fake_imagenet" ./run_local.sh onnxruntime mobilenet cpu --accuracy

Last line of output on P51, which appears to contain the benchmark results

TestScenario.SingleStream qps=58.85, mean=0.0138, time=0.136, acc=62.500%, queries=8, tiles=50.0:0.0129,80.0:0.0137,90.0:0.0155,95.0:0.0171,99.0:0.0184,99.9:0.0187

where presumably qps means queries per second, and is the main results we are interested in, the more the better.

Running:

tools/make_fake_imagenet.sh

produces a tiny ImageNet subset with 8 images under fake_imagenet/.

fake_imagenet/val_map.txt contains:

val/800px-Porsche_991_silver_IAA.jpg 817
val/512px-Cacatua_moluccensis_-Cincinnati_Zoo-8a.jpg 89
val/800px-Sardinian_Warbler.jpg 13
val/800px-7weeks_old.JPG 207
val/800px-20180630_Tesla_Model_S_70D_2015_midnight_blue_left_front.jpg 817
val/800px-Welsh_Springer_Spaniel.jpg 156
val/800px-Jammlich_crop.jpg 233
val/782px-Pumiforme.JPG 285

where the numbers are the category indices from ImageNet1k. At gist.github.com/yrevar/942d3a0ac09ec9e5eb3a see e.g.:

817: 'sports car, sport car',
89: 'sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita',

and so on, so they are coherent with the image names. By quickly looking at the script we see that it just downloads from Wikimedia and manually creates the file.

TODO prepare and test on the actual ImageNet validation set, README says:

Prepare the imagenet dataset to come.

Since that one is undocumented, let's try the COCO dataset instead, which uses COCO 2017 and is also a bit smaller. Note that his is not part of MLperf anymore since v2.1, only ImageNet and open images are used. But still:

wget https://zenodo.org/record/4735652/files/ssd_mobilenet_v1_coco_2018_01_28.onnx
DATA_DIR_BASE=/mnt/data/coco
export DATA_DIR="${DATADIR_BASE}/val2017-300"
mkdir -p "$DATA_DIR_BASE"
cd "$DATA_DIR_BASE"
wget http://images.cocodataset.org/zips/val2017.zip
wget http://images.cocodataset.org/annotations/annotations_trainval2017.zip
unzip val2017.zip
unzip annotations_trainval2017.zip
mv annotations val2017
cd -
cd "$(git-toplevel)"
python tools/upscale_coco/upscale_coco.py --inputs "$DATA_DIR_BASE" --outputs "$DATA_DIR" --size 300 300 --format png
cd -

Now:

./run_local.sh onnxruntime mobilenet cpu --accuracy

fails immediately with:

No such file or directory: '/path/to/coco/val2017-300/val_map.txt

The more plausible looking:

./run_local.sh onnxruntime mobilenet cpu --accuracy --dataset coco-300

first takes a while to preprocess something most likely, which it does only one, and then fails:

Traceback (most recent call last):
  File "/home/ciro/git/inference/vision/classification_and_detection/python/main.py", line 596, in <module>
    main()
  File "/home/ciro/git/inference/vision/classification_and_detection/python/main.py", line 468, in main
    ds = wanted_dataset(data_path=args.dataset_path,
  File "/home/ciro/git/inference/vision/classification_and_detection/python/coco.py", line 115, in __init__
    self.label_list = np.array(self.label_list)
ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 2 dimensions. The detected shape was (5000, 2) + inhomogeneous part.

TODO!

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FFmpeg video synthesis by

Ciro Santilli 37 Updated 2025-07-16

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Video with a solid color:

2 second white video:

ffplay -autoexit -f lavfi -i 'color=white:640x480:d=3,format=rgb24,trim=end=2'

Also add some audio:

ffmpeg -lavfi "color=white:640x480:d=3,format=rgb24,trim=end=2[v];sine=f=1000:d=2[a]" -map '[a]' -map '[v]' out.mkv

TODO how to ffplay the video + audio directly? -map does not seem to work unfortunately.

2 second white followed by 2 second black video:

ffplay -autoexit -f lavfi -i 'color=white:640x480:d=3,format=rgb24,trim=end=2[a];color=black:640x480:d=3,format=rgb24,trim=end=2[b];[a][b]concat=n=2:v=1:a=0'

bibliography:
- superuser.com/questions/1153930/how-to-generate-a-pure-white-background-video-with-ffmpeg

Display count in seconds on the video:

black text on white background. Start from 0 and count up to 2:

ffplay -autoexit -f lavfi -i "
color=white:480x480:d=3,
format=rgb24,
drawtext=
  fontcolor=black:
  fontsize=600:
  text='%{eif\:t\:d}':
  x=(w-text_w)/2:
  y=(h-text_h)/2
"

count 0 to 2 with one different sine wave per count:

ffmpeg -lavfi "
color=white:480x480:d=3,
format=rgb24,
drawtext=
fontcolor=black:
fontsize=600:
text='%{eif\:t\:d}':
x=(w-text_w)/2:
y=(h-text_h)/2[v];
sine=f=500:d=1[a1];
sine=f=1000:d=1[a2];
sine=f=2000:d=1[a3];
[a1][a2][a3]concat=n=3:v=0:a=1[a];
" -map '[v]' -map '[a]' count.mkv

bibliography:

Bibliography:

ffmpeg.org//ffmpeg-filters.html#Video-Sources main section of the documentation listing various video generators
stackoverflow.com/questions/11640458/how-can-i-generate-a-video-file-directly-from-an-ffmpeg-filter-with-no-actual-in generically asking how to generate the video without an input video

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Activity tracker website by

Ciro Santilli 37 Updated 2025-07-16

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Stockfish CLI by

Ciro Santilli 37 Updated 2025-10-14

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www.maketecheasier.com/use-stockfish-cli-master-chess is a good source.

Most of what follows is part of the Universal Chess Interface. Tested on Ubuntu 22.10, Stockfish 14.1.

After starting stockfish on the command line, d (presumably display) contains:

 +---+---+---+---+---+---+---+---+
 | r | n | b | q | k | b | n | r | 8
 +---+---+---+---+---+---+---+---+
 | p | p | p | p | p | p | p | p | 7
 +---+---+---+---+---+---+---+---+
 |   |   |   |   |   |   |   |   | 6
 +---+---+---+---+---+---+---+---+
 |   |   |   |   |   |   |   |   | 5
 +---+---+---+---+---+---+---+---+
 |   |   |   |   |   |   |   |   | 4
 +---+---+---+---+---+---+---+---+
 |   |   |   |   |   |   |   |   | 3
 +---+---+---+---+---+---+---+---+
 | P | P | P | P | P | P | P | P | 2
 +---+---+---+---+---+---+---+---+
 | R | N | B | Q | K | B | N | R | 1
 +---+---+---+---+---+---+---+---+
   a   b   c   d   e   f   g   h

Fen: rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR w KQkq - 0 1
Key: 8F8F01D4562F59FB

Sweet ASCII art. where:

Fen: FEN notation
Key: TODO

Move white king's pawn from e2 to e4:

position startpos moves e2e4

Then display again:

gives:

 +---+---+---+---+---+---+---+---+
 | r | n | b | q | k | b | n | r | 8
 +---+---+---+---+---+---+---+---+
 | p | p | p | p | p | p | p | p | 7
 +---+---+---+---+---+---+---+---+
 |   |   |   |   |   |   |   |   | 6
 +---+---+---+---+---+---+---+---+
 |   |   |   |   |   |   |   |   | 5
 +---+---+---+---+---+---+---+---+
 |   |   |   |   | P |   |   |   | 4
 +---+---+---+---+---+---+---+---+
 |   |   |   |   |   |   |   |   | 3
 +---+---+---+---+---+---+---+---+
 | P | P | P | P |   | P | P | P | 2
 +---+---+---+---+---+---+---+---+
 | R | N | B | Q | K | B | N | R | 1
 +---+---+---+---+---+---+---+---+
   a   b   c   d   e   f   g   h

Fen: rnbqkbnr/pppppppp/8/8/4P3/8/PPPP1PPP/RNBQKBNR b KQkq - 0 1
Key: B46022469E3DD31B

so we see that the pawn moved.

Now let's make Stockfish think for one second what is the next best move for black:

go movetime 1000

gives as the last line:

bestmove c7c5 ponder g1f3

TODO:

what is ponder? Something to do with thinking on the opponent's turn: permanent brain.
understand the previous lines

To make the move it as suggested for black, we have to either repeat the entire sequence of movements:

position startpos moves e2e4 c7c5

d:

 +---+---+---+---+---+---+---+---+
 | r | n | b | q | k | b | n | r | 8
 +---+---+---+---+---+---+---+---+
 | p | p |   | p | p | p | p | p | 7
 +---+---+---+---+---+---+---+---+
 |   |   |   |   |   |   |   |   | 6
 +---+---+---+---+---+---+---+---+
 |   |   | p |   |   |   |   |   | 5
 +---+---+---+---+---+---+---+---+
 |   |   |   |   | P |   |   |   | 4
 +---+---+---+---+---+---+---+---+
 |   |   |   |   |   |   |   |   | 3
 +---+---+---+---+---+---+---+---+
 | P | P | P | P |   | P | P | P | 2
 +---+---+---+---+---+---+---+---+
 | R | N | B | Q | K | B | N | R | 1
 +---+---+---+---+---+---+---+---+
   a   b   c   d   e   f   g   h

Fen: rnbqkbnr/pp1ppppp/8/2p5/4P3/8/PPPP1PPP/RNBQKBNR w KQkq - 0 2
Key: 4CA78BCE9C2980B0

or alternatively we could also use the previous FEN notation as a starting point;

position fen rnbqkbnr/pppppppp/8/8/4P3/8/PPPP1PPP/RNBQKBNR b KQkq - 0 1 moves c7c5

Note how the Universal Chess Interface interface is very simple: we just load a state and then decide what to do next for that one state. The engine holds only one and exactly one state at a time, and you can't even modify it differentially without loading new one from scratch.

Let's move white again with our brain with either:

position startpos moves e2e4 c7c5 d2d3
position fen rnbqkbnr/pp1ppppp/8/2p5/4P3/8/PPPP1PPP/RNBQKBNR w KQkq - 0 2 moves d2d3

Set a specific position from fen:

position fen rnbqkbnr/pppppppp/8/8/4P3/8/PPPP1PPP/RNBQKBNR b KQkq - 0 1

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FeathersJS by

Ciro Santilli 37 Updated 2025-07-16

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Looks interesting.

It seems to abstract the part about the client messaging the backend, which focuses on being able to easily plug in a number of Front-end web framework to manage client state.

Has the "main web API is the same as the REST API" focus, which is fundamental 2020-nowadays.

Uses Socket.IO, which allows the client Javascript to register callbacks when data is updated to achieve Socket.IO, e.g. their default chat app does:

client.service('messages').on('created', addMessage);

so that message appear immediately as they are sent.

Their standard template from feathers generate app on @feathersjs/cli@4.5.0 includes:

several authentication methods, including OAuth
testing
backend database with one of several object-relational mapping! However, they don't abstract across them. E.g., the default Chat example uses NeDB, but a real app will likely use Sequelize, and a port is needed

which looks promising! They don't have a default template for a Front-end web framework however unfortunately: docs.feathersjs.com/guides/frameworks.html#the-feathers-chat lists a few chat app versions, which is their hello world:

Front-end web framework: not built-in on generator, but there are some sample repos pointed from the documentation, and they did work out-of-box:
- feathers-chat-react

But it is in itself a completely boring app with a single splash page, and no database interaction, so not a good showcase. The actual showcase app is feathersjs/feathers-chat.

And there is no official example of the chat app that is immediately deployable to Heroku: FeathersJS Heroku deployment, all setups require thinking.

Global source entry point: determine on package.json as usual, defaults to src/index.js.

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HyperPhysics by

Ciro Santilli 37 Updated 2025-07-16

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hyperphysics.phy-astr.gsu.edu/hbase/hframe.html

Created by Dr. Rod Nave from Georgia State University, where he worked from 1968 after his post-doc in North Wales on molecular spectroscopy.

While there is value to that website, it always feels like it falls a bit too short as too "encyclopedic" and too little "tutorial-like". Most notably, it has very little on the history of physics/experiments.

Ciro Santilli likes this Rod, he really practices some good braindumping, just look at how he documented his life in the pre-social media Internet dark ages: hyperphysics.phy-astr.gsu.edu/Nave-html/nave.html

The website evolved from a HyperCard stack, as suggested by the website name, mentioned at: hyperphysics.phy-astr.gsu.edu/hbase/index.html.

Shame he was too old for CC BY-SA, see "Please respect the Copyright" at hyperphysics.phy-astr.gsu.edu/hbase/index.html.

exhibits.library.gsu.edu/kell/exhibits/show/nave-kell-hall/capturing-a-career has some good photo selection focused on showing the department, and has an interview.

Kell hall is a building of GSU that was demolished in 2019: atlanta.curbed.com/2020/1/31/21115980/gsu-georgia-state-atlanta-kell-hall-demolition-park-library-north

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Krusader by

Ciro Santilli 37 Updated 2025-07-16

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The most powerful GUI file manager ever?? Infinite configurability??

Ciro Santilli wasted some time on it before he gave up on file managers altogether and started using only the CLI with a few aliases.

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Keyhole Inc. by

Ciro Santilli 37 Updated 2025-07-16

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Adobe Flash by

Ciro Santilli 37 Updated 2025-07-16

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Bundle assets into a single file in Phaser by

Ciro Santilli 37 Updated 2025-07-16

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Quantum field theory bibliography by

Ciro Santilli 37 Updated 2025-07-16

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Ciro Santilli's favorites so far:

Physics from Symmetry by Jakob Schwichtenberg (2015)

Bibliography of the biliograpy:

Recommendations by friend P. C.:

The Global Approach to Quantum Field Theory
Lecture Notes | Geometry and Quantum Field Theory | Mathematics ocw.mit.edu/courses/mathematics/18-238-geometry-and-quantum-field-theory-fall-2002/lecture-notes/
Towards the mathematics of quantum field theory (Frederic Paugam)
Path Integrals in Quantum Mechanics (J. Zinn–Justin)
(B.Hall) Quantum Theory for Mathematicians (B.Hall)
Quantum Field Theory and the Standard Model (Schwartz)
The Algebra of Grand Unified Theories (John C. Baez)
quantum Field Theory for The Gifted Amateur by Tom Lancaster (2015)

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 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!

Video 1.

Intro to OurBigBook

. Source.

We have two killer features:

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
Video 2.
OurBigBook Web topics demo
. Source.
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:
- to OurBigBook.com to get awesome multi-user features like topics and likes
- as HTML files to a static website, which you can host yourself for free on many external providers like GitHub Pages, and remain in full control
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.
Internal cross file references done right:
Infinitely deep tables of contents:
Figure 6.
Dynamic article tree with infinitely deep table of contents
.
Live URL: ourbigbook.com/cirosantilli/chordate
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

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