Quick post today. And a memory backup one. I just spend 30 minutes trying to install a desktop UI in a clean lite RaspberryPi install. And I missed and missed again the command.
The right command is
sudo apt install raspberrypi-ui-mods
And that’s it. Now is here, so I can search me and find the solution.
Context: I use the [Raspbian Buster Lite] distro for the Raspberry Pi. In 10 minutes I got the SSH enabled so I can perform most of my operations remotely from my computer.
After an amazing weekend, where I split my time supporting 2 different hackathons, today big news is the announcement of the new Raspberry Pi 4.
Raspberry Pi 4 is here! A tiny, dual-display desktop computer, with three RAM variants to choose from, and all the hackability you know and love. On sale now from the familiar price of $35: https://t.co/d9iwVidexm#RaspberryPi4pic.twitter.com/4fll4gx1Ax
64-bit Quad-Core ARM Cortex-A72 processor, with a core clock speed of 1.5GHz
1GB, 2GB or 4GB of RAM
2 4K HDMI displays
USB 3
Bluetooth 5
starting price at $35
and much more !
I won’t get deep in details, I prefer to share some really good reviews, later i this post. Now is time to wait until the 4GB model is available in Canada and I’ll do some update on my Custom Vision docker and Machine Learning performance posts with the new device!
Programación, bases de datos, .Net, JavaScript, Azure, Windows, Linux y más. En Net University te brindamos entrenamiento de alta calidad con profesionales experimentados, al mejor costo / beneficio que puedas encontrar.
Actualmente hay 3
cursos disponibles y estamos terminando varios más, incluido uno de Machine
Learning para .Net developers, ¡que saldrá a la luz a final de Junio!
I’ve write a couple of time about project Malmo and Minecraft, so if you like Minecraft and Artificial Intelligence, MineRL will make your day. Let’s start with some basis:
MineRL is a large-scale dataset on Minecraft of seven different tasks, which highlight a variety of research challenges including open-world multi-agent interactions, long-term planning, vision, control, navigation, and explicit and implicit subtask hierarchies.
There are 2 main ways to be involved with MineRL, entering the AI (DL) competition, or playing Minecraft (to create more source data to train and test models!)
In the play more, MineRL want to solve Minecraft using state-of-the-art Machine Learning! To do so, MineRL is creating one of the largest datasets of recorded human player data. The dataset includes a set of tasks which highlights many of the hardest problems in modern-day Reinforcement Learning: sparse rewards and hierarchical policies.
There is plenty of information and details on the main website, and as soon as I finish some of my current work and personal projects, I’ll for sure spend more time here!
Además de cuidar detalles como la funcionalidad o la apariencia visual de nuestra aplicación, nuestra aplicación debe funcionar correctamente bajo todas las condiciones en todos los dispositivos para la que sea lanzada.
Un punto importante a revisar siempre suele ser, el tiempo de arranque de la aplicación.
¿Conoces conceptos como AOT?, ¿fast renderers?. En este artículo vamos a repasar algunos conceptos que podemos aplicar para tener un impacto positivo en los tiempos de arranque de la aplicación.
XAMLC
Si defines la interfaz de usuario de la aplicación Xamarin.Forms con XAML tienes la opción de utilizar XamlCompilationOptions.
Cuenta con dos valores:
Compile.
Acelera la carga de elementos visuales.
Reduce el tamaño del paquete.
La compilación (AOT) es más larga.
Skip.
Valor por defecto para mantener retocompatibilidad con versiones antiguas de Xamarin.Forms.
The Insider Dev Tour is for developers
interested in building Microsoft 365 experiences (Windows, Graph,
Office, Teams) today, using the latest dev technologies, as well as for
those who want a peek into the future. If you can read code, this is for
you, regardless if you are a beginner, an expert, a student, or a
hobbyist developer.
The morning keynote
session will give you a demo and code-focused overview of the new
developer technology emerging from Redmond. It’s the best of Microsoft
Build for Microsoft 365 developers. We’ll cover Windows, Graph, Office,
AI, and more so that you are up-to-date and able to make informed
decisions when choosing from the latest technology for your next
project.
This is a 100 percent developer-focused event.
The
tour is an opportunity to connect directly with leads and engineers
from Redmond, as well as regional industry leaders and the community of
Microsoft MVPs and RDs. We’re excited to meet you in person!
#InsiderDevTour
El uso de imágenes en aplicaciones móviles es habitual. Es un elemento clave a la hora de conseguir buenos resultados visuales. Sin embargo, también suelen ser uno de los puntos clave que impactan en el rendimiento de la aplicación. Problemas como:
Alto consumo de memoria.
Bloqueo de la UI (carga de imágenes en el hilo de UI, etc).
Etc.
En este artículo, vamos a realizar comparaciones en el rendimiento del control Image de Xamarin.Forms entre diferentes versiones, así como una comparativa con FFImageLoading y GlideX.
Para realizar las comaparativas vamos a necesitar un ejemplo y algo de código para obtener información. Nuestro ejemplo va a ser una versión modificada del gran ejemplo realizado por Jonathan Peppers en Glidex.
So, the trip to Italy is done, and I have the best memories ever. I’ve spend some time with the Global Avanade Innovation Network, and it was amazing to see again my friends from all around the globe.
I was supposed to continue my series of posts on Face Recognition and Python. Remember, I was down from 5 FPS to 30 FPS with some minor tweaks. But I have in my notes a different post to write.
It all started when my friend Juanjo (@kastwey) kindly asked to everyone in twitter to describe the images we use in each tweet. Juanjo is blind, and he is an amazing developer. Every time I talk to him, he reminds me how we can do some little extra efforts and make his life more easier.
NO tiene sentido que siga insistiendo en que la gente describa las imágenes en Twitter. Al final, queramos o no, creo que el pensamiento de: "es para cuatro gatos y no merece la pena el esfuerzo", aunque sea de forma inconsciente, es el que se impone. Quizá me equivoque, claro.
Sometime ago, I was used to share my code samples as images in my blog, and JuanJo shared how difficult was to him to read this code. My code is not very good, but you never know …
So, if you want to help people in Twitter who may not be able to see the graphics content you share, please follow the next steps. This is for Twitter for Android, I’m sure that the iOS app will be similar.
Open Settings in the Twitter App
Twitter Android Settings
Select [Accessibility]
Twitter Android Settings Accessibility options
Check [Compose image descriptions]
That’s it!
Now, every time you write a new tweet you will be prompted to add an image description for every photo / picture.
And after yesterday’s post I realize that the code is working, but there is room for performance improvement. So, I went back to my 1st sample, the one for face detection and I added some code to get some times for Frames per Second (FPS).
In my initial code, the app was working processing almost 6 FPS. Then I started to read the code and think on improvements and I manage to get an amazing +30FPS.
So, before moving forward, I want to remark this StackOverflow post that quickly pointed me in the easiest way to do a StopWatch in Python.
My original code, was this one:
And then, I realize that I may use some of the OpenCV functions to increase the face detection process. I really don’t need to process a full HD image (1920 x 1080), I may resize the frame to a quarter size and work with this. That’s how, based on some of the samples, I got the following code:
The line 12 perform the initial resize and then I recalculate back the positions before drawing the face frame. This process works almost 6 times faster than the original one.
I’ll continue improving the code and samples, and sharing my learning path !
Quick post today. I’ll pickup yesterday demo, showing the facial features and adding Face Recognition on top of that. In other words, we’ll move from this
To this
With a couple of extra lines for face recognition
There is some room for performance improvement, so I’ll focus on this in next posts.
Rendimiento con…
El ejemplo 
