📟 Creating a Text-to-speech engine with Google Tesseract and Arm NN on Raspberry Pi
A text-to-speech (TTS) engine is the crucial element of systems looking to create a natural interaction between humans and machines based on embedded devices. An embedded device can, for example, help visually impaired people read signs, letters, and documents. More specifically, a device can use optical character recognition to let a user know what it sees in an image.
In this article, you will learn how to do so with TensorFlow, OpenCV, Festival, and a Raspberry Pi. I will use the TensorFlow machine learning platform along with a pre-trained Keras-OCR model to perform OCR. OpenCV will be used to capture images from the web camera. Finally, the Festival speech synthesis system will serve as the TTS module. Everything will then be combined to build the Python app for Raspberry Pi.
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#projects #raspberry #machine_learning #artificial_intelligence #python
A text-to-speech (TTS) engine is the crucial element of systems looking to create a natural interaction between humans and machines based on embedded devices. An embedded device can, for example, help visually impaired people read signs, letters, and documents. More specifically, a device can use optical character recognition to let a user know what it sees in an image.
In this article, you will learn how to do so with TensorFlow, OpenCV, Festival, and a Raspberry Pi. I will use the TensorFlow machine learning platform along with a pre-trained Keras-OCR model to perform OCR. OpenCV will be used to capture images from the web camera. Finally, the Festival speech synthesis system will serve as the TTS module. Everything will then be combined to build the Python app for Raspberry Pi.
More information...
#projects #raspberry #machine_learning #artificial_intelligence #python
🎛 Dog Mood Detector with Google Cloud and Raspberry Pi
In this article we’re going to explore the idea of a dog mood detector. We’ll build a device that listens to the ambient sound around it and, if a dog is present, attempts to determine which type of sound the dog is making: a friendly bark, a scared whimper, or an aggressive growl.
Based on the preferences of the user, the device vibrates when it thinks they should check on their dog. This could be used, perhaps, to help owners keep tabs on their dog when they're out of earshot. To prototype this device, we’ll use a Raspberry Pi, which is my go-to platform for implementing Machine Learning on edge devices.
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#projects #raspberry #machine_learning #IoT #python
In this article we’re going to explore the idea of a dog mood detector. We’ll build a device that listens to the ambient sound around it and, if a dog is present, attempts to determine which type of sound the dog is making: a friendly bark, a scared whimper, or an aggressive growl.
Based on the preferences of the user, the device vibrates when it thinks they should check on their dog. This could be used, perhaps, to help owners keep tabs on their dog when they're out of earshot. To prototype this device, we’ll use a Raspberry Pi, which is my go-to platform for implementing Machine Learning on edge devices.
More information...
#projects #raspberry #machine_learning #IoT #python
📟 Automatic Trash Classification with Raspberry Pi and Arm NN Machine Learning
AI is now moving to edge devices. Arm is leading this revolution by providing accelerated hardware IPs and middle-layer solutions.
In practice, this means you can train your models using the most popular ML frameworks. You can then load models and optimize them on your edge device to perform fast inference, eliminating network and privacy problems.
To demonstrate ML with edge computing resources, we'll use Arm NN APIs to classify images of trash from a webcam attached to a Raspberry Pi. The Raspberry Pi will display classification results.
More information...
#projects #raspberry #artificial_intelligence #machine_learning
AI is now moving to edge devices. Arm is leading this revolution by providing accelerated hardware IPs and middle-layer solutions.
In practice, this means you can train your models using the most popular ML frameworks. You can then load models and optimize them on your edge device to perform fast inference, eliminating network and privacy problems.
To demonstrate ML with edge computing resources, we'll use Arm NN APIs to classify images of trash from a webcam attached to a Raspberry Pi. The Raspberry Pi will display classification results.
More information...
#projects #raspberry #artificial_intelligence #machine_learning
🎚 OSHChip (OpenSourceHardwareChip)
The most striking thing you see is that it is the size of a 16 pin DIP, and unlike other processor boards, it is designed from the start to be compatible with the white breadboards that are commonly used by electronic hobbyists, robotics projects, and oh so many hackaday projects.
Unlike other processor boards that are far larger, OSHChip can be plugged into the middle two rows of a bread board, and it doesn’t cover the connected holes that you will be connecting to.
Specifications:
▫️ ARM
▫️ 2.4 GHz Bluetooth Low Energy radio
▫️ Broad range of built-in Peripheral functions
▫️ 256 KBytes of Flash memory for program and data
▫️ 32 KBytes of SRAM
▫️ Support for in-system debugging including breakpoints
More information...
#boards #cortex
The most striking thing you see is that it is the size of a 16 pin DIP, and unlike other processor boards, it is designed from the start to be compatible with the white breadboards that are commonly used by electronic hobbyists, robotics projects, and oh so many hackaday projects.
Unlike other processor boards that are far larger, OSHChip can be plugged into the middle two rows of a bread board, and it doesn’t cover the connected holes that you will be connecting to.
Specifications:
▫️ ARM
Cortex-M0 32 bit (16 MHz)▫️ 2.4 GHz Bluetooth Low Energy radio
▫️ Broad range of built-in Peripheral functions
▫️ 256 KBytes of Flash memory for program and data
▫️ 32 KBytes of SRAM
▫️ Support for in-system debugging including breakpoints
More information...
#boards #cortex
🎛 Insanely Small Development Board: T402 Atto
It’s an extremely simple circuit and hardly something that hasn’t been done before, but the value here is in the tricky soldering to make it rather than its novelty.
The ATtiny402 and three passive SMD components are fitted on the smallest possible sliver of prototyping board to contain them, and the female headers and set of programming pins contribute far more to the volume of the device than the board itself. He also tried a side-on design with two smaller slivers of board before settling on the more conventional layout.
The demonstration of the system in action seen in the video: the break is a magnetic flux detector, dwarfed by the 40-pin DIP Z80 it is sitting on.
More information...
#boards #arduino #experiments
It’s an extremely simple circuit and hardly something that hasn’t been done before, but the value here is in the tricky soldering to make it rather than its novelty.
The ATtiny402 and three passive SMD components are fitted on the smallest possible sliver of prototyping board to contain them, and the female headers and set of programming pins contribute far more to the volume of the device than the board itself. He also tried a side-on design with two smaller slivers of board before settling on the more conventional layout.
The demonstration of the system in action seen in the video: the break is a magnetic flux detector, dwarfed by the 40-pin DIP Z80 it is sitting on.
More information...
#boards #arduino #experiments
🎬 How to use the two Cores of the Pi Pico?
The new Pi Pico has two cores. How can we use both? And: If you want to play with the Pico, this video can save you a lot of time because we will discover the main differences between programming an Arduino and a Pi Pico. After this video, you will know more than 99% of all Pi Pico users. And you know how to avoid some quirks.
https://youtu.be/9vvobRfFOwk
#video #raspberry #pico
The new Pi Pico has two cores. How can we use both? And: If you want to play with the Pico, this video can save you a lot of time because we will discover the main differences between programming an Arduino and a Pi Pico. After this video, you will know more than 99% of all Pi Pico users. And you know how to avoid some quirks.
https://youtu.be/9vvobRfFOwk
#video #raspberry #pico
YouTube
#372 How to use the two Cores of the Pi Pico? And how fast are Interrupts?
The new Pi Pico has two cores. How can we use both? And: If you want to play with the Pico, this video can save you a lot of time because we will discover the main differences between programming an Arduino and a Pi Pico. After this video, you will know more…
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🎥 ESP32-CAM Video Streaming Web Server
In this project we’re going to build an IP surveillance camera with the ESP32-CAM board. The ESP32 camera is going to host a video streaming web server that you can access with any device in your network.
You can integrate this video streaming web server with popular home automation platforms like Home Assistant or Node-RED. In this tutorial, we’ll show you how to integrate it with Home Assistant and Node-RED.
More information...
#projects #camera #esp32 #web
In this project we’re going to build an IP surveillance camera with the ESP32-CAM board. The ESP32 camera is going to host a video streaming web server that you can access with any device in your network.
You can integrate this video streaming web server with popular home automation platforms like Home Assistant or Node-RED. In this tutorial, we’ll show you how to integrate it with Home Assistant and Node-RED.
More information...
#projects #camera #esp32 #web
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