Raspberry Pi OpenCV Smart Vision Gimbal
OpenCV AI Artificial Intelligence Python Programming Machine Vision

Product Introduction
The Little R Raspberry Pi OpenCV Machine Vision Development Kit is based on the Raspberry Pi 4B development board and is equipped with a USB high-definition camera and a 2-DOF gimbal.
The product uses OpenCV to implement visual functions such as color recognition, face recognition, QR code recognition, and gesture recognition. Each functional example provides a detailed explanation of the principles and Python source code.
OpenCV / Python Programming / Machine Vision / Vision Development Environment

Two-DOF Vision Gimbal
The Little R Raspberry Pi OpenCV Machine Vision Development Kit features two anti-blocking servo motors
that can control the camera up, down, left, and right, providing a wider visual coverage!

AI Vision Features and Applications
The product integrates many interesting machine vision recognition functions, such as:
facial recognition, color recognition, QR code recognition, AR virtual reality, gesture recognition, etc.;
each vision function comes with Python source code, allowing for in-depth secondary development.

Face Recognition Quickly identifies faces within the field of view, and drives the gimbal to follow the face in all directions. | Edge Detection Effective images can be output in real time using various detection algorithms. |

Aruco Augmented Reality Supports dynamic detection and tracking of QR code AR tags, acquiring the tag's pose and coordinates. | Gesture Recognition Real-time gesture detection can be achieved using OpenCV. |

Color Recognition After recognizing a specified color via the gimbal camera, drives the gimbal to follow the corresponding color in all directions. | QR Code Recognition The gimbal can be driven to rotate to a specified position by recognizing QR codes containing specific content. |

* It offers 38 detailed lessons, including explanations of principles, experimental operations, and source code analysis.
Course List
1. Basic Courses
| Introduction to Raspberry Pi OpenCV | Introduction to software & hardware components |
| Robot Development Kit | Kit box parameters |
| SD Card System Backup & Restore | |
| Working Principle of Pan-Tilt Camera | |
2. Raspberry Pi OpenCV Machine Vision Development Kit Course
| Development Tools Preparation | Software setup , Hardware setup |
| Basic Operations | Remote connection , Code framework , Modify code , Run code |
| Machine Vision Overview | What is machine vision , What is OpenCV , OpenCV installation , Simple OpenCV application examples |
| Face Recognition | Principle of face recognition , Experience color recognition effects , Key code analysis for color recognition , Complete color recognition function code |
| Edge Detection | Principle of gesture recognition , Experience gesture recognition effects , Key code analysis for gesture recognition , Complete gesture recognition function code |
| Aruco Augmented Reality | Principle of Aruco AR , Experience Aruco AR effects , Key code analysis for Aruco AR , Complete Aruco AR function code |
| QR Code Recognition | Principle of QR code recognition , Experience QR code recognition effects , Key code analysis for QR code recognitin , Complete QR code recognition function code |
| Color Recognition | Principle of color recognition , Experience color recognition effects , Key code analysis for color recognition ,Complete color recognition function code |
| Gesture Recognition | Principle of gesture recognition , Experience gesture recognition effects , Key code analysis for gesture recognition , Complete gesture recognition function code |
Product Parameters

| 1. High-definition camera | 2. Two-DOF gimbal |
| 3. Built-in Raspberry Pi 4B motherboar | 4. Raspberry Pi visual expansion box |
Raspberry Pi OpenCV Machine Vision Development Kit
| Product Model | XR-CV-PRI |
| Main Controller | Raspberry Pi 4B development board |
| Pan-Tilt Parameters | 2 degrees of freedom (2-DOF) pan-tilt |
| Camera Resolution | 480P |
| Power Supply | 9V power adapter |
| Interfaces | UART / SPI / I2C / PWM / GPIO |
| Operating System | Linux Ubuntu 18.04 |
| Servo Model | XR-SG180 |
| Connectivity | WiFi (802.11 b/g/n) / RJ45 Ethernet |
| Machine Vision Framework | OpenCV 4 |
| Programming Language | Python |
| Product Dimensions | 420 × 104 × 155 mm |
| Net Weight | 0.228 kg |
Product List
Standard Version

| Visual Gimbal Product Body | Charger | Warranty Card |
Advanced Version

| Visual Gimbal Product Body | Charger | Warranty Card | Keyboard and Mouse Set |
Professional Version

| Visual Gimbal Unit | Charger |

| Warranty Card | Keyboard and Mouse Set | 7-inch Touchscreen Display |










