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Free | OpenMV4 Cam H7, a machine vision microcontroller board based on the STM32H7 processor

Latest update time:2024-06-18
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Seeed's OpenMV4 Cam H7 is a small, low-power microcontroller board that includes an Arduino, a Raspberry Pi-compatible machine vision sensor, and an OV7725 camera. It is powerful and flexible and suitable for a variety of complex machine vision applications.


How to apply for free

From now until June 30, >> click here to apply for free , sign up for the 2024 DigiKey "Sense Everything, Enjoy Life" Creative Competition , submit your proposal or idea, and you will have a chance to own it! DIY can also win cash prizes of 10,000 yuan, 5,000 yuan, 2,000 yuan , etc.

Tips: When filling out the form, select 102991322 (OpenMV4 Cam H7 product number) and select 1 other creative matching material.


OpenMV4 Cam H7 Features

■ STM32H743VI Arm® Cortex®-M7 processor running at 480 MHz, with 1 MB RAM and 2 MB Flash, and all I/O pins output 3.3 V and are 5 V tolerant.

• Full-speed USB (12 Mbs) interface to user's computer

• microSD card slot with 100 Mbs read/write speeds

• SP bus operating at up to 100 Mbs allows users to easily transfer system image data to LCD expansion board, Wi-Fi expansion board or other microcontrollers

• I²C-bus, CAN-bus and asynchronous serial bus (Tx/Rx) for connection with other microcontrollers and sensors

• 1 12-bit ADC and 1 12-bit DAC

• 3 I/O pins for servo control

• Interrupts and PWM on all I/O pins (there are ten I/O pins on the board)

• 1 RGB LED and two high power 850 nm infrared LEDs


■ The detachable camera module system allows OpenMV Cam H7 to connect to different sensors:

• The OpenMV Cam H7 is equipped with an OV7725 image sensor, which can capture 640x480 8-bit grayscale images or 640x480 16-bit RGB565 images at 60 FPS when the resolution is higher than 320x240, and up to 120 FPS when the resolution is lower than 320x240. Most simple algorithms will run above 60 FPS. The image sensor has a 2.8 mm lens with a standard M12 lens mount.


■ LiPo battery connector is compatible with 3.7 V LiPo batteries

application

Frame Difference Processing, Color Tracking, Marker Tracking, Face Detection, Eye Tracking, People Detection, Optical Flow, QR Code Detection/Decoding, Data Matrix Detection/Decoding, Linear Barcode Decoding, AprilTag Tracking, Line Detection, Circle Detection, Rectangle Detection, Template Matching, Image Capture, Video Recording, TensorFlow Lite for Microcontroller Support

Pin Diagram



Technical Information

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