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OV7725 MU Vision Sensor 640x480 UART/I2C

DFRobot

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SKU:
147-SEN0314
MPN:
SEN0314
OV7725 MU Vision Sensor is a compact image recognition sensor with a built-in deep learning engine, 640x480 resolution, 90-degree FOV, and UART/I2C output for intelligent robotics applications. View full description
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Technical Specifications

Brand:
DFRobot

Warranty Information

All the products supplied by Evelta are genuine and original. We offer 14 days replacement warranty in case of manufacturing defects. For more details, please visit our cancellation and returns page.

Description

An image recognition sensor equipped with a built-in deep learning engine. Despite its compact size, this sensor harnesses the power of a 30W wide-angle lens and a multitude of vision algorithms, enabling your robots to become more intelligent and autonomous. With the MU vision sensor at your disposal, you can construct a smart robot capable of adapting to unpredictable environmental events with suitable behaviors.

Leverage the MU vision sensor to effortlessly identify and locate a wide range of objects, including colors, balls, humans, and cards. The detected results can be conveniently output through UART and I2C interfaces. Remarkably, this sensor possesses the ability to process information locally, eliminating the need for a network connection. Additionally, parameter configuration and firmware updates for the module can be easily achieved via the onboard USB serial port. The sensor supports various communication modes, such as UART, I2C, and WIFI, ensuring compatibility with Arduino, Mixly, and micro:bit embedded platforms. Hence, regardless of your chosen development platform, you are wholeheartedly invited to explore the immense capabilities of this sensor.

The compact MU vision sensor unlocks a myriad of intelligent applications. Imagine a smart printing and scanning car robot or a basketball shooting robot—these are just glimpses of what you can achieve. Moreover, its applications extend far and wide, encompassing smart toys, AI teaching tools, maker products, and more.

Project: Arduino Face Tracking Robot

 

Project: How To Make DIY Arduino Traffic Sign Recognition Robot

Other Parts: Tracked Robot Chassis, Arduino Uno, Motor Driver Shield, 18650 Li-ion Battery - (From PowerBank )

 

Specification

  • Processor: dual-core, 240MHz
  • Camera: Omnivision ov7725
  • Camera Resolution: 640x480
  • Field of View: 90Deg (Diagonal line)
  • 2 LED lights
  • Dimension: 3.2x3.2x1.2cm/1.26x1.26x0.47”
  • Data Output: UART/I2C
  • Power Supply: 5V
  • Detected Objects: people silhouette (above the waist)
Package Contents
MU Vision Sensor x1

Resources

FAQs:

Q: What are the key features of the OV7725 MU Vision Sensor?

  • Built-in deep learning algorithm acceleration engine
  • 640 x 480 pixel resolution
  • 90° field of view (FOV)
  • Supports UART and I2C interfaces

Q: What are the applications of the OV7725 MU Vision Sensor?

  • Ideal for intelligent robotics and AI vision applications
  • Object recognition and tracking
  • Face detection and recognition
  • Gesture recognition
  • Obstacle avoidance

Q: Does the OV7725 MU Vision Sensor require any additional software or libraries?

A: The sensor comes with built-in algorithms, so no additional software libraries are required.
However, you may need to write code to interface with the sensor and process the output data depending on your specific application.

Q: What is the power consumption of the OV7725 MU Vision Sensor?

A: The power consumption is not explicitly mentioned in the product description.
It's recommended to refer to the datasheet or contact the manufacturer for detailed information.

Q: What is the difference between UART and I2C interfaces?

  • UART (Universal Asynchronous Receiver-Transmitter) is a simple serial communication protocol.
  • I2C (Inter-Integrated Circuit) is a more complex two-wire serial communication protocol that allows multiple devices to communicate on the same bus.
  • You can choose the interface based on your project requirements and the capabilities of your microcontroller.