This document summarizes the components used to create an LED wall display interface using Telegram. The LED wall is composed of 128 pixels arranged in an 8x16 configuration. The architecture includes a Telegram bot to receive messages and images, a Redis database to store the model and media, a Flask API to interface with the components, and Celery to manage asynchronous tasks like image conversion. Images are stored in Amazon S3 and the LED wall is controlled by a Raspberry Pi connected to an LED driver HAT. The system allows users to send messages and photos to the Telegram bot which are then processed and displayed on the LED wall.

1. It is amazing what you
can do with 128 pixels
Xavier Orduña
Python Meetup BCN
26th November
(Using Telegram as an Interface for an LED wall)

2. Back to the Origin
(2.560 x 1.600 pixels)(84 x 47 pixels) (160 x 144 pixels)

3. The Challenge

4. The Screen
A lot of wiring!!
128 px
128px
80 cm
80cm
About 1000 EUR in electronics!

5. Architecture
Telegram Bot
Redis DB (Model)
Amazon S3 (Images)
Flask API
Celery (tasks)
HDMI + LED Controller
GPIO Header

6. Telegram Bot
• API: https://core.telegram.org/bots/api
• Python Library:
https://github.com/leandrotoledo/python-
telegram-bot
• New bot token: @BotFather
• Bot name: walledbot

7. Telegram Bot
(here goes the logic with the messages)

8. Telegram Bot
(gets a photo or text and posts it to our API)

9. Telegram Bot
(Send a message to the user)
(Send a keyboard to the user)

10. Model in Redis
• The most easy and FUN database
• You can represent complex models (
http://redis.io/topics/twitter-clone)
• Key, value storage with steroids (sets,
lists, hashes)
• All operations are atomic
• You can use Redis Desktop Manager
(linux, mac, windows)

11. Model in Redis
• walls_list list
of
wall
id’s
• wall_ids
counter
with
last
wall
id
• posts_ids
counter
with
last
post
id
• walls:
list
with
wall
ids
• walls:WALL_ID
hash
with
wall
data
• posts:POST_ID
hash
with
post
data
• walls_posts:WALL_ID
list
with
posts
id’s

12. Model in Redis

13. API (Flask)
• Its easy and well documented
• Almost everything included (jinja2,
sessions, cookies, request, …)
• Very similar to bottle
• Can be deployed using uWSGI or run
standalone
• API and Web app all in one!

14. API (Flask)

15. API (Flask)

16. API (Flask)

17. Celery Task Mngt
• Task manager easy to use!
• It can use Redis as a Backend and Broker
• But also MongoDB or RabbitMQ

18. Celery Task Mngt

19. Convert to image
Fonts from: www.dafont.com

20. Convert to image
a3er
a
couple
of
hours
trying
to
resize
an
image,
I
decied
to
use
a
script
found
in
somewhere:
h;ps://gist.github.com/sigilioso/2957026

21. Amazon S3
• Easy place to store images
• Organized in buckets
• Best library is “boto”
• You should create new keys for your
application
• The AWS backend is sometimes confusing

22. Amazon S3

23. LED Matrix
Available at: http://www.adafruit.com/products/1484 (40 USD)

24. LED Wall
Tutorial here: https://learn.adafruit.com/adafruit-diy-led-video-wall/overview
It is fun to build it, but you can find it already mounted and ready to go!

25. RaspberryPI
• Last version: Raspberry PI 2 Model B
• Less than 40 USD
• 1 Gb RAM
• To speedup development share the home
folder using samba
• If you plan to play with it, get a keyboard
and a screen.

26. RaspberryPI
LED
GPIO
HAT
available
at
Adafruit,
it
can
manage
up
to
4
32x32
LED
Matrix

27. RaspberryPI
Chinese LED wall controller.
Input is DVI and it maps W x H pixels to LED wall (300 USD)

28. RaspberryPI

29. Framebuffer
• PyGame enables us to access the
framebuffer directly
• We can show images or sprites
• Programs to modify framebuffer must run
with sudo

30. Framebuffer

31. The Result

32. Thank you!
code:
xavier.orduna@gmail.com