Dominic  Feeney

Dominic Feeney

1624432032

A tutorial showing how to set up TensorFlow's Object Detection API on the Raspberry Pi

TensorFlow-Object-Detection-on-the-Raspberry-Pi

Update 10/13/19: Setting up the TensorFlow Object Detection API on the Pi is much easier now! Two major updates: 1) TensorFlow can be installed simply using “pip3 install tensorflow”. 2) The protobuf compiler (protoc) can be installed using "sudo apt-get protobuf-compiler. I have updated Step 3 and Step 4 to reflect these changes.

Bonus: I made a Pet Detector program (Pet_detector.py) that sends me a text when it detects when my cat wants to be let outside! It runs on the Raspberry Pi and uses the TensorFlow Object Detection API. You can use the code as an example for your own object detection applications. More info is available at the bottom of this readme.

Introduction

This guide provides step-by-step instructions for how to set up TensorFlow’s Object Detection API on the Raspberry Pi. By following the steps in this guide, you will be able to use your Raspberry Pi to perform object detection on live video feeds from a Picamera or USB webcam. Combine this guide with my tutorial on how to train your own neural network to identify specific objects, and you use your Pi for unique detection applications such as:

Here’s a YouTube video I made that walks through this guide!

The guide walks through the following steps:

  1. Update the Raspberry Pi
  2. Install TensorFlow
  3. Install OpenCV
  4. Compile and install Protobuf
  5. Set up TensorFlow directory structure and the PYTHONPATH variable
  6. Detect objects!
  7. Bonus: Pet detector!

The repository also includes the Object_detection_picamera.py script, which is a Python script that loads an object detection model in TensorFlow and uses it to detect objects in a Picamera video feed. The guide was written for TensorFlow v1.8.0 on a Raspberry Pi Model 3B running Raspbian Stretch v9. It will likely work for newer versions of TensorFlow.

#tensorflow #raspberrypi #hardware #api #set up tensorflow's object detection api #a tutorial showing how to set up tensorflow's object detection api on the raspberry pi

What is GEEK

Buddha Community

A tutorial showing how to set up TensorFlow's Object Detection API on the Raspberry Pi
Dominic  Feeney

Dominic Feeney

1624432032

A tutorial showing how to set up TensorFlow's Object Detection API on the Raspberry Pi

TensorFlow-Object-Detection-on-the-Raspberry-Pi

Update 10/13/19: Setting up the TensorFlow Object Detection API on the Pi is much easier now! Two major updates: 1) TensorFlow can be installed simply using “pip3 install tensorflow”. 2) The protobuf compiler (protoc) can be installed using "sudo apt-get protobuf-compiler. I have updated Step 3 and Step 4 to reflect these changes.

Bonus: I made a Pet Detector program (Pet_detector.py) that sends me a text when it detects when my cat wants to be let outside! It runs on the Raspberry Pi and uses the TensorFlow Object Detection API. You can use the code as an example for your own object detection applications. More info is available at the bottom of this readme.

Introduction

This guide provides step-by-step instructions for how to set up TensorFlow’s Object Detection API on the Raspberry Pi. By following the steps in this guide, you will be able to use your Raspberry Pi to perform object detection on live video feeds from a Picamera or USB webcam. Combine this guide with my tutorial on how to train your own neural network to identify specific objects, and you use your Pi for unique detection applications such as:

Here’s a YouTube video I made that walks through this guide!

The guide walks through the following steps:

  1. Update the Raspberry Pi
  2. Install TensorFlow
  3. Install OpenCV
  4. Compile and install Protobuf
  5. Set up TensorFlow directory structure and the PYTHONPATH variable
  6. Detect objects!
  7. Bonus: Pet detector!

The repository also includes the Object_detection_picamera.py script, which is a Python script that loads an object detection model in TensorFlow and uses it to detect objects in a Picamera video feed. The guide was written for TensorFlow v1.8.0 on a Raspberry Pi Model 3B running Raspbian Stretch v9. It will likely work for newer versions of TensorFlow.

#tensorflow #raspberrypi #hardware #api #set up tensorflow's object detection api #a tutorial showing how to set up tensorflow's object detection api on the raspberry pi

Arvel  Parker

Arvel Parker

1591611780

How to Find Ulimit For user on Linux

How can I find the correct ulimit values for a user account or process on Linux systems?

For proper operation, we must ensure that the correct ulimit values set after installing various software. The Linux system provides means of restricting the number of resources that can be used. Limits set for each Linux user account. However, system limits are applied separately to each process that is running for that user too. For example, if certain thresholds are too low, the system might not be able to server web pages using Nginx/Apache or PHP/Python app. System resource limits viewed or set with the NA command. Let us see how to use the ulimit that provides control over the resources available to the shell and processes.

#[object object] #[object object] #[object object] #[object object] #[object object] #[object object] #[object object] #[object object] #[object object] #[object object]

MEAN Stack Tutorial MongoDB ExpressJS AngularJS NodeJS

We are going to build a full stack Todo App using the MEAN (MongoDB, ExpressJS, AngularJS and NodeJS). This is the last part of three-post series tutorial.

MEAN Stack tutorial series:

AngularJS tutorial for beginners (Part I)
Creating RESTful APIs with NodeJS and MongoDB Tutorial (Part II)
MEAN Stack Tutorial: MongoDB, ExpressJS, AngularJS and NodeJS (Part III) 👈 you are here
Before completing the app, let’s cover some background about the this stack. If you rather jump to the hands-on part click here to get started.

#[object object] #[object object] #[object object] #[object object] #[object object] #[object object] #[object object] #[object object]

TensorFlow Lite Object Detection using Raspberry Pi and Pi Camera

I have not created the Object Detection model, I have just merely cloned Google’s Tensor Flow Lite model and followed their Raspberry Pi Tutorial which they talked about in the Readme! You don’t need to use this article if you understand everything from the Readme. I merely talk about what I did!

Prerequisites:

  • I have used a Raspberry Pi 3 Model B and PI Camera Board (3D printed a case for camera board). **I had this connected before starting and did not include this in the 90 minutes **(plenty of YouTube videos showing how to do this depending on what Pi model you have. I used a video like this a while ago!)

  • I have used my Apple Macbook which is Linux at heart and so is the Raspberry Pi. By using Apple you don’t need to install any applications to interact with the Raspberry Pi, but on Windows you do (I will explain where to go in the article if you use windows)

#raspberry-pi #object-detection #raspberry-pi-camera #tensorflow-lite #tensorflow #tensorflow lite object detection using raspberry pi and pi camera

Creating RESTful APIs with NodeJS and MongoDB Tutorial

Welcome to this tutorial about RESTful API using Node.js (Express.js) and MongoDB (mongoose)! We are going to learn how to install and use each component individually and then proceed to create a RESTful API.

MEAN Stack tutorial series:

AngularJS tutorial for beginners (Part I)
Creating RESTful APIs with NodeJS and MongoDB Tutorial (Part II) 👈 you are here
MEAN Stack Tutorial: MongoDB, ExpressJS, AngularJS and NodeJS (Part III)

#[object object] #[object object] #[object object] #[object object] #[object object] #[object object] #[object object]