Sunday, November 06, 2022 Deep Learning in the Film Industry + a few comments about Op...

Tuesday, September 13, 2022

iniVation - DAVIS 346 Neuromorphic Event camera.

A high-precision camera sensor manufactured by Swiss company iniVation, which develops neuromorphic vision systems.

Employs a patented technology that works like the human retina, significantly reducing power consumption, data rate and computational requirements compared to conventional camera sensors, while providing a dynamic range of 120dB and latency of 1ms. Has less and higher performance.

It is expected to be used in the following fields:

surveillance and ambient sensing / high-speed robots / FA applications (factory automation) / microscopy / motion analysis (humans and animals) / fluid dynamics / sleep research, chronobiology / Fluorescence Imaging / Particle Tracking

Product Specifications:

  • 346 x 260 resolution

  • Simultaneous frame and event output

  • H 40 x W 60 x D 25 mm

  • 100 g without lens

  • CE certified

  • Color or mono

Device comes with:

  • Micro-USB 3.0 cable

  • CS-mount lens

  • 1/4" mount

The camera does not output frames of intensity images. However, similar intensity images can be reconstructed from the event output by their DV software. 

There is support for multi-camera time synchronization via daisy chain connection and external event injection.

iniVation website:

CED: Color Event Camera Dataset
CED is the first Color Event Camera Dataset, featuring 50 minutes of footage with both color frames and color events from the Color-DAVIS346. Event cameras have several advantages over conventional cameras: high dynamic range, low latency and immunity to motion blur. We include sequences that showcase these attractive properties, such as high-speed, low-light etc. All the data are released as binary (rosbag) files.

Wednesday, September 07, 2022

Saturday, April 16, 2022

Scalable WebRTC peer-to-peer broadcasting

WebRTC Scalable Broadcast

Scalable WebRTC peer-to-peer broadcasting demo.

npm downloads

This module simply initializes and configures it in a way that single broadcast can be relayed over unlimited users without any bandwidth/CPU usage issues. Everything happens peer-to-peer!

RTCMultiConnection v3 and Scalable Broadcast

RTCMultiConnection v3 now naively supports scalable-broadcast:

Scalable Audio/Video BroadcastDemoSource
Scalable Screen BroadcastDemoSource
Scalable Video BroadcastDemoSource
Scalable File SharingDemoSource


Note: These (below) are old demos. Above (RTCMultiConnection-v3) demos are preferred (and up-to-dated).

  1. index.html - share video or screen or audio over unlimited users using p2p methods.
  2. share-files.html - share files with unlimited users using p2p methods!

Browsers Support:

FirefoxStable / Aurora / Nightly
Google ChromeStable / Canary / Beta / Dev

Browsers Comparison

host means the browser that is used to forward remote-stream.

ChromeAudio+VideoChrome,FirefoxRemote audio tracks are skipped.
ChromeAudioNoneChrome can NOT forward remote-audio
ChromeVideoChrome,FirefoxNo issues
ChromeScreenChrome,FirefoxNo issues
FirefoxAudio+VideoChrome,FirefoxNo issues
FirefoxAudio+ScreenChrome,FirefoxNo issues
FirefoxAudioChrome,FirefoxNo issues
FirefoxVideoChrome,FirefoxNo issues
FirefoxScreenChrome,FirefoxNo issues
  1. First column shows browser name
  2. Second column shows type of remote-stream forwarded
  3. Third column shows browsers that can receive the remote forwarded stream
  4. Fourth column shows sender's i.e. host's issues

Chrome-to-Firefox interoperability also works!

Android devices are NOT tested yet. Opera is also NOT tested yet (though Opera uses same chromium code-base).

Currently you can't share audio in Chrome out of this big. In case of audio+video stream, chrome will skip remote-audio tracks forwarding. However chrome will keep receiving remote-audio from Firefox!


Firefox additionally allows remote-stream-forwarding for:

  1. Streams captured from <canvas>
  2. Streams captured from <video>
  3. Streams captured or generated by AudioContext i.e. WebAudio API

Is stream keeps quality?

Obviously "nope". It will have minor side-effects (e.g. latency in milliseconds/etc.).

If you'll be testing across tabs on the same system, then you'll obviously notice quality lost; however it will NOT happen if you test across different systems.

WebRTC Scalable Broadcast

In the image, you can see that each NEW-peer is getting stream from most-recent peer instead of getting stream directly from the moderator.

npm install webrtc-scalable-broadcast

Now, goto node_modules>webrtc-scalable-broadcast:

cd node_modules
cd webrtc-scalable-broadcast

# and run the server.js file
node server.js


cd ./node_modules/webrtc-scalable-broadcast/
node ./server.js

Or install using WGet:

mkdir webrtc-scalable-broadcast && cd webrtc-scalable-broadcast
tar -zxvf webrtc-scalable-broadcast.tar.gz
ls -a
node server.js

Or directly download the TAR/archive on windows:

And now open: http://localhost:8888 or

If server.js fails to run:

# if fails,
lsof -n -i4TCP:8888 | grep LISTEN
kill process-ID

# and try again
node server.js

How it works?

Above image showing terminal logs explains it better.

For more details, to understand how this broadcasting technique works:

WebRTC Scalable Broadcast

Assuming peers 1-to-10:

First Peer:

Peer1 is the only peer that invokes getUserMedia. Rest of the peers will simply forward/relay remote stream.

peer1 captures user-media
peer1 starts the room

Second Peer:

peer2 joins the room
peer2 gets remote stream from peer1
peer2 opens a "parallel" broadcasting peer named as "peer2-broadcaster"

Third Peer:

peer3 joins the room
peer3 gets remote stream from peer2
peer3 opens a "parallel" broadcasting peer named as "peer3-broadcaster"

Fourth Peer:

peer4 joins the room
peer4 gets remote stream from peer3
peer4 opens a "parallel" broadcasting peer named as "peer4-broadcaster"

Fifth Peer:

peer5 joins the room
peer5 gets remote stream from peer4
peer5 opens a "parallel" broadcasting peer named as "peer5-broadcaster"

and 10th peer:

peer10 joins the room
peer10 gets remote stream from peer9
peer10 opens a "parallel" broadcasting peer named as "peer10-broadcaster"


  1. Peer9 gets remote stream from peer8
  2. Peer15 gets remote stream from peer14
  3. Peer50 gets remote stream from peer49

and so on.


Scalable WebRTC Broadcasting Demo is released under MIT licence . Copyright (c) Muaz Khan.

Friday, March 11, 2022

Scanning laser microscope

3D printed, scanning laser confocal microscope so I could collect 3D surface topology and profilometry data! The microscope stage is based on an OpenFlexure "Delta" stage, and the confocal optics are constructed with a 3D printed body, some lenses, a 405nm laser, pinhole and photodiode. The microscope is controlled by a Raspberry Pi (which controls an arduino to move the steppers). It's not beautiful, it takes forever to scan, and the images are of dubious quality... but it works! OpenFlexure: 0:00 Intro 1:56 Confocal vs Widefield Microscopy 3:25 OpenFlexure Motion Platform 4:01 Confocal optical breakdown 8:00 Delta motion stage 8:43 Photodiode amplifier 9:14 Confocal Pinhole demonstration 10:31 Camera vs Photodiode 11:31 Data processing considerations 14:05 Images and results! 18:22 Optimizations 21:37 Discord! Come hang out with us!

Thursday, March 10, 2022

ASCII Video (Coding Challenge 166)

Let's make ASCII art in p5.js together! In this video, I demonstrate a variety of techniques for translating the pixels of an image into text and finish with rendering video as text ASCII characters in a DOM. p5.js Web Editor Sketches: 🕹️ ASCII video: 🕹️ ASCII image canvas: 🕹️ ASCII image dom: 🕹️ ASCII text: 🕹️ ASCII weather api: đŸŽĨ Previous video: đŸŽĨ All videos: Links discussed in this video: 🔗 ASCII play by ertdfgcvb: 🔗 HTML Entity: 🔗 HTML div: 🔗 p5.js loadPixels(): 🔗 p5.js brightness(): 🔗 CodingTrainChooChoo on Twitch: Other videos mentioned in this video: đŸŽĨ The Pixel Array: đŸŽĨ Basics of CSS: đŸŽĨ p5.js Web Editor - Uploading Media Files: Timestamps: 0:00 Welcome! Choo choo! 0:28 Introducing Today’s Topic 1:39 Pixel to ASCII 4:52 Pixelating an image 7:03 Pixel Array Explanation 8:40 Back to the code 10:18 Adding Text 11:04 Mapping Brightness to Characters 13:26 Switching from canvas to DOM 18:10 Real-time ASCII video 20:10 Some refinemens 21:29 See you next time! 🚂 Website: