2017 Hot Saling Restaurant 15 Inch POS System Windows POS Terminal

2017 Hot Saling Restaurant 15 Inch POS System Windows POS Terminal
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Note:

Bundle 1: 2G DDR3+32G eMMC Base

Bundle 2: 4G DDR3+64G eMMC Base

Bundle 3: 2G DDR3+32G eMMC+Case

Bundle 4: 4G DDR3+64G eMMC+Case

Bundle 5: 2G DDR3+32G eMMC Base+Win10 Product Key(Home)

Bundle 6: 4G DDR3+64G eMMC Base+Enterprise License

 

Optional Accessory:

 
 
LattePanda 
 
 
Development Board

 

2GB/4GB DDR3+ 32GB/64GB eMMC

 

 

 

Overview

 

LattePanda is the first development board that can run a full version of Windows 10! It is turbocharged with an Intel Quad Core processor and has excellent connectivity, with three USB ports and integrated WiFi and Bluetooth 4.0. It also includes an Arduino co-processor that enables you to master the physical world by controlling interactive devices using thousands of plug and play peripherals.

 
 
Applications2

Full Windows 10 OS

•       LattePanda is different from the Raspberry Pi and other development boards as it supports a complete Windows 10 system. With abundant software resources and a mature Windows ecosystem at your disposal, LattePanda gives your ideas more accessibility and power!

Harness the power of LattePanda to create and innovate!

01

 

•       Fast And Powerful

  LattePanda brings single board computers to a whole new level of power and performance. Turbocharged with an Intel Quad Core 1.8GHz processor, 2-4GB RAM and 32-64GB onboard flash memory, LattePanda can easily carry out image recognition, real-time CNC control and more!

      02

  •  Ready to Go Arduino

   LattePanda is not only a low cost regular Windows computer - it also includes an Arduino co-processor, which means it can be used to control and sense the physical world when you add sensors and actuators. Whether you are a Windows developer, an IoT developer, an interactive designer, robotics whizz, or a maker, LattePanda can aid your creative process with physical computing projects!

5
 
 
User Manual 
 
User Manual03

 

GPIO Demo

 

 

 
  • DigitalWrite
 

In this example, we will blink the LED which is connected with digital pin (D0 - D13)

 

API Required :

public Arduino();

public void pinMode(int pin, byte mode);

public void digitalWrite(int pin, byte value);

Hardware Required:

 

LattePanda x 1

led x 1 (or you can use the LED attached to pin 13 on the Arduino board itself)

Circuit:

LED inserted directly into pin 9

 

01

 

 

Code:

 

Create a new project in Visual Studio, Refer to Create a project

Main function code :

02

 

Test:

 

Click Debug button to execute, the LED will start blinking.

digitalRead

This example detects the Button state through digital pin (D0-D13). API required:

 

public Arduino();

public void pinMode(int pin, byte mode);

public int digitalRead(int pin);

Hardware Required:

 

LattePanda x 1

Button x 1

Resistor (Resistance value greater than 1KΩ) x 1

Circuit:

 

 

Connect button to pin 9 as following figure shows

 
 
03
 

 

Code:

 

Create a new project in Visual Studio, refer to Create a project

Main function code

 
 
04
 
  • PWM

This example assigns a pulse width modulation (PWM) value to an output pin (D3, D5, D6, D9, D10, D11) to dim or brighten an LED API Required:

 

public Arduino();

public void pinMode(int pin, byte mode);

public void analogWrite(int pin, int state);

Hardware Required:

 

LattePanda x 1

LED x 1

Circuit:

 

LED connected directly into pin 9 as following figure shows

 
 
110

 

 

Code:

 

Create a new project in Visual Studio, refer to Create a project

Main function code

 
 
 
05
 
 

Test:

 

Click Debug to execute, you will find the LED brightness vary form dim to bright and then back again.

AnalogRead

This example detect the value of analog pin (A0-A5) where a potentiometer is connected, and then print the value API Required:

 

public Arduino();

public int analogRead(int pin);

public event AnalogPinUpdated analogPinUpdated;

Hardware Required:

 

LattePanda x 1

Potentiometer x 1

Circuit:

 

Connect the potentiometer to pin 0 as following figure shows:

 
 
06
 

 

Code :

 

Create a new project in Visual Studio, refer to Create a project

Main function Code:

 
 
07
 

 

Test:

 

Click Debug to execute, the state of potentiometer will print when you rotate it.

Servo

In this example, we will sweep the servo motor back and forth across 180 degrees. API Required:

 

public Arduino();

public void pinMode(int pin, byte mode);

public void servoWrite(int pin, int angle);

Hardware Required:

 

LattePanda x 1

Servo Motor x 1

Circuit:

 

Servo inserted directly into pin D9:

 
 
08
 
 

Code :

 

Create a new project in Visual Studio, Refer to Create a project

Main function code:

 
 
09
 
 

Test:

 

Click debug to execute, you will find the motor sweeping forth and back continuously.

I2C

This example will show you how to use I2C to get the data form 3-axis accelerometer ADXL345 API Required:

 

public Arduino();

public void wireBegin(Int16 delay); 3.public void wireRequest(byte slaveAddress,Int16 slaveRegister, Int16[] data,byte mode);

public event DidI2CDataReveive didI2CDataReveive;

Hardware Required:

 

LattePanda x 1

ADXL345 x 1

Circuit:

 

The following is a figure describing which pins on the LattePanda should be connected to the pins on the accelerometer.

 
 
10

 

 

Code :

 

Create a new project in Visual Studio, Refer to Create a project

Main function code:

 
 
11
 

 

Test:

 

Click Debug to execute, the 3-axis acceleration data will be printing continuous.

 
 
 

Face Detection Using openVC

 

Introduction

In this article, you will learn an easy way to detect your face and eyes by using OpenCV.

OpenCV (Open Source Computer Vision) is released under a BSD license and hence it’s free for both academic and commercial use. It has C++, C, Python and Java interfaces and supports Windows, Linux, Mac OS, iOS and Android. OpenCV was designed for computational efficiency and with a strong focus on real-time applications. Written in optimized C/C++, the library can take advantage of multi-core processing.

 

Adopted all around the world, OpenCV has more than 47 thousand people of user community and estimated number of downloads exceeding 9 million. Usage ranges from interactive art, to mines detection, online maps and advanced robotics.

 

Steps:

Step 1:Install Visual Studio 2017 and OpenCV

1.Install Visual Studio 2017 on your computer

Head over to https://www.visualstudio.com/products/visual-studio-professional-with-msdn-vs and download Visual Studio Professional 2015. Unzip the downloaded file and double-click the \'vs_professional.exe\', then the installation process will begin.

 

2.Install OpenCV

1) Head over to the site: http://www.opencv.org and download the latest version of OpenCV (shown in the following figure). Choose the version according to your operating system.

In this tutorial we are going to install OpenCV 3.1 using Visual Studio 2015 professional on a 64-bit system running Windows 10.

 

01

 

2) Extract the downloaded OpenCV file Double click the downloaded OpenCV file, and then extract it

 

02

 

Step 2: Set the Environment Variables

1.To do this step, open the Control Panel and then System. Click the Advanced System Settings, last Environment Variables in turns as show in the following figure.
 

033

 

2.Edit the PATH environment variables and Add a new environment variable, then give it the value of F:\\opencv\\build\\x64\\vc14\\bin. Note that change the value depends on the path where you have extracted your OpenCV in step 2.

 

04

 

Step 3: Create a new project in Visual Studio 2017

1.In Visual Studio 2017, create a new project to follow the steps in turns as the following figure shows
 
 
05
 
 
2.Select Win32 Console Application in Visual C++, then name your project and select a directory to store it
 
06
 
 
3.Choose the empty project and click finish
 
07
 
 
4.Add a new cpp file
 
08
09
 
 
Step 4: Configure OpenCV in Visual Studio 2017
 
1.Open the Property Manager and double click Debug|Win64
 
10
 
 

2.Select "Include Directories", and give it the following values:

F:\\opencv\\build\\include

F:\\opencv\\build\\include\\opencv

F:\\opencv\\build\\include\\opencv2

Remember that change the value depending on the path you have extracted your OpenCV files to in step 2.

11
 
 

3.Add Library Directories, give the value of F:\\opencv\\build\\x64\\vc14\\lib. Remember that changing the values depends on the path where you have extracted your OpenCV in step 2

 

12

 

4.Add additional dependences

Copy the following item and paste it in additional Dependences blankopencv_world310d.lib

13
 
 

Step 5: Paste the following code to the .cpp file your added in step 4.

 

020
021
022

 

Step 6: Debug your Project

Set two options as following figure shows:

 

14

 

Press F5 to execute the face detection project, your PC camera will turn on and your face and eyes will be highlighted like so:

 

15

 

 

resource

User Mannal And Resource:  http://docs.lattepanda.com/

GPIO Demo:http://docs.lattepanda.com/content/hardware/examples/

Face Detection Using OpenVC:http://docs.lattepanda.com/content/projects/HowToDetectFaceEyes/

Github: https://github.com/LattePandaTeam/

Blog:   https: //www.lattepanda.com/blog  

 

 

 

Pack list

 

Bundle 1 & Bundle 2

1x LattePanda Demo Board 2G/4G+32G/64G Base(Depend on your order)

1x Poower Adapter

1x Micro USB Cable

1x Cooling Fan

1x Antenna 

Panda shipping list update

 

 

zhixian

Bundle 3 & Bundle 4

1x LattePanda Demo Board 2G/4G+32G/64G (Depend on your order)

1x Poower Adapter

1x Micro USB Cable

​1x Arylic Case 

1x Cooling Fan

1x Antenna 

 

Panda 1 update 500x shipping list

 

 

 

zhixian

Bundle 5 & Bundle 6

 

1x LattePanda Demo Board 2G/4G+32G/64G (Depend on your order)
1x Windows10 Product Key
1x Poower Adapter
1x Micro USB Cable
1x Arylic Case
1x Cooling Fan
1x Antenna

Panda shipping list update

 

 

 

 

zhixian

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Expert Support: firefly@ smartfire.cn   Skype: smartfire_cn

Product Customization: firefly@ smartfire.cn