johnny-five
examples
johnny-five | examples | |
---|---|---|
21 | 143 | |
13,201 | 7,754 | |
- | 0.7% | |
1.3 | 5.3 | |
6 months ago | about 1 month ago | |
JavaScript | Jupyter Notebook | |
GNU General Public License v3.0 or later | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
johnny-five
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Qwik & Arduino with Johnny Five
Some times ago I have played with johnny-five, a JavaScript Robotics & IoT platform. In short words, we can communicate with our Arduino or Raspberry by using JavaScript with a very friendly syntax.
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Dockerize Javascript IOT Applications
The library Johnny-Five is a Javascript library that allows you to control Arduino and other microcontrollers using Javascript. It is very easy to use and it has a lot of examples that you can use to learn how to use it.
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Is there a differnece if I program the Arduino using NodeJS instead of it language c/c++
+Here is the platform used to program the board http://johnny-five.io/
- Arduino to PC Serial Protocol Library
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From Wi-Fi to Li-Fi, sending data via light using Arduino and JavaScript
I decided to use the Johnny-Five JavaScript framework for this. After installing it , I started by declaring a few variables and instantiating the transmitter board.
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Guide please🙏i will really mean a lot.
IOT is the internet of things. That loosely means - interconnected devices that aren't your standard "computer." You can totally do that with JS and a little computer like an Arduino. You can use https://johnny-five.io/ or something... but I'm talking about - a year from now -
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help - Cannot figure out why I keep getting SyntaxError: Unexpected token {
here it the project's github: https://github.com/rwaldron/johnny-five
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JS Library for controlling devices with cameras
Johnny Five seems like a neat project for that bit. What I'm trying to find is a library for using the camera bit. Sorry if my original question wasn't specific enough. I'll try to clarify here.
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Anybody build / programmed LEDs using Node?
Start here: http://johnny-five.io/
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Firmata on ESP32 (WROOM)
I am trying to put Firmata on ESP32 and connect it to the johnny-five lib (or any other JS client). I managed to put official Firmata and other forks related to ESP32, but it doesn't work (build+upload succeed), but I'm getting "ready" from the device.
examples
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My Favorite DevTools to Build AI/ML Applications!
TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more intuitive coding of complex AI models. Both frameworks support a wide range of AI models, from simple linear regression to complex deep neural networks.
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Open Source Ascendant: The Transformation of Software Development in 2024
AI's Open Embrace Artificial intelligence (AI) and machine learning (ML) are increasingly leveraging open-source frameworks like TensorFlow [https://www.tensorflow.org/] and PyTorch [https://pytorch.org/]. This democratization of AI tools is driving innovation and lowering entry barriers across industries.
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Best AI Tools for Students Learning Development and Engineering
Which label applies to a tool sometimes depends on what you do with it. For example, PyTorch or TensorFlow can be called a library, a toolkit, or a machine-learning framework.
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Releasing The Force Of Machine Learning: A Novice’s Guide 😃
TensorFlow: An open-source machine learning framework for high-performance numerical computations, especially well-suited for deep learning.
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MLOps in practice: building and deploying a machine learning app
The tool used to build the model per se was TensorFlow, a very powerful and end-to-end open source platform for machine learning with a rich ecosystem of tools. And in order to to create the needed script using TensorFlow Jupyter Notebook was used, which is a web-based interactive computing platform.
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🔥14 Excellent Open-source Projects for Developers😎
10. TensorFlow - Make Machine Learning Work for You 🤖
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GPU Survival Toolkit for the AI age: The bare minimum every developer must know
AI models, particularly those built on deep learning frameworks like TensorFlow, exhibit a high degree of parallelism. Neural network training involves numerous matrix operations, and GPUs, with their expansive core count, excel in parallelizing these operations. TensorFlow, along with other popular deep learning frameworks, optimizes to leverage GPU power for accelerating model training and inference.
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🔥🚀 Top 10 Open-Source Must-Have Tools for Crafting Your Own Chatbot 🤖💬
#2 TensorFlow
- Are there people out there who still like Sam atlman - AI IS AT DANGER
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Tensorflow help
I am on a new ftc team trying to get vision to work. I used the ftc machine learning tool chain but I have yet to get a good result with at best a 10% accuracy rate. I have changed everything possible in the tool chain with little luck. To fix this, I have tried making my own .tflite model using the google colab from https://www.tensorflow.org/. When ever I try to run the same code with my own .tflite model, it gives me the error "User code threw an uncaught exception: IllegalStateException - Error getting native address of native library: task_vision_jni". It gives me the same error with official tensor flow tflite test models, and when I put them on a raspberry pi, both worked just fine. Does anyone have a fix to this error or even just tips for the machine learning toolchain?
What are some alternatives?
cylon.js - JavaScript framework for robotics, drones, and the Internet of Things (IoT)
cppflow - Run TensorFlow models in C++ without installation and without Bazel
serialport - Access serial ports with JavaScript. Linux, OSX and Windows. Welcome your robotic JavaScript overlords. Better yet, program them!
mlpack - mlpack: a fast, header-only C++ machine learning library
onoff - GPIO access and interrupt detection with Node.js
awesome-teachable-machine - Useful resources for creating projects with Teachable Machine models + curated list of already built Awesome Apps!
node-rpio - Raspberry Pi GPIO library for node.js
face-api.js - JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js
spi-device - SPI serial bus access with Node.js
Selenium WebDriver - A browser automation framework and ecosystem.
pigpio - Fast GPIO, PWM, servo control, state change notification and interrupt handling with Node.js on the Raspberry Pi
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing