BinKey

OpenMV Cam H7 R2

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Important Note

This entire repo was AI created - including all of the data within. The intent was to A) help me with my personal electronics inventory; and B) see how I could use AI to make that process a bit easier. DO NOT TRUST!

OpenMV Cam H7 R2

High-performance machine vision camera module with Python programming support for computer vision and AI applications.

OpenMV Cam H7 R2

OpenMV Cam H7 R2 - High-performance machine vision camera with STM32H7 processor

Overview

The OpenMV Cam H7 R2 is a small, low power microcontroller board that allows easy implementation of machine vision applications in the real world. It runs high-level Python scripts using MicroPython, making it much easier to work with complex machine vision algorithms compared to traditional C/C++ programming.

Key Features

Processor

  • STM32H743VI ARM Cortex-M7 running at 480 MHz
  • 1MB SRAM and 2MB Flash memory
  • Double Precision FPU for advanced calculations
  • Core Mark Score: 2400 (comparable to Raspberry Pi 2: 2340)

Memory Layout

  • 1MB Total RAM:
    • 256KB for .DATA/.BSS/Heap/Stack
    • 512KB Frame Buffer/Stack
    • 256KB DMA Buffers
  • 2MB Total Flash:
    • 128KB Bootloader
    • 128KB Embedded Flash Drive
    • 1792KB Firmware

Camera System

  • MT9M114 Image Sensor (included)
  • 640x480 resolution at up to 80 FPS (lower resolutions)
  • 40 FPS for resolutions above 320x240
  • 2.1mm lens on standard M12 mount (replaceable)
  • Removable camera module system with 8-bit parallel interface

Supported Image Formats

  • Grayscale: 640x480 and under
  • RGB565: 320x240 and under
  • JPEG: 640x480 and under (both Grayscale and RGB565)
  • BAYER/YUV422 support

I/O Interfaces

OpenMV Cam H7 R2 Pinout

OpenMV Cam H7 R2 Pinout Diagram - All pins are 5V tolerant with 3.3V output

Communication

  • Full Speed USB (12 Mbps) - appears as Virtual COM Port and USB Flash Drive
  • μSD Card Socket - 100 Mbps read/write capability
  • SPI Bus - up to 80 Mbps for image streaming
  • I2C Bus - up to 1 Mb/s
  • CAN Bus - up to 1 Mb/s
  • Asynchronous Serial (TX/RX) - up to 7.5 Mb/s

Analog/Digital I/O

  • 12-bit ADC and 12-bit DAC
  • 10 I/O pins total (all 5V tolerant, 3.3V output)
  • 3 servo control pins
  • Interrupts and PWM on all I/O pins
  • RGB LED and two high-power 850nm IR LEDs

Power Specifications

Power Consumption

  • Idle (no μSD): 110mA @ 3.3V
  • Idle (with μSD): 110mA @ 3.3V
  • Active (no μSD): 160mA @ 3.3V
  • Active (with μSD): 170mA @ 3.3V

Power Input

  • VIN Range: 3.6V to 5V
  • 3.3V Rail: Do not draw more than 250mA
  • Pin Current: Up to 25mA per pin, 120mA total across all pins
  • LiPo Battery Connector for 3.7V batteries

Physical Specifications

Dimensions

  • Length: 45mm
  • Width: 36mm
  • Height: 30mm
  • Weight: 16g

Operating Conditions

  • Operating Temperature: -20°C to 70°C
  • Storage Temperature: -40°C to 125°C

Lens Specifications

  • Max Image Circle Diameter: 6.7mm
  • Focal Length: 2.8mm
  • Aperture: F2.0
  • HFOV: 70.8°, VFOV: 55.6°
  • Mount: M12×0.5 (standard, replaceable)
  • IR Cut Filter: 650nm (removable)
  • Format: 1/3”

Programming and Software

Development Environment

  • MicroPython operating system
  • OpenMV IDE for development
  • High-level Python scripting instead of C/C++
  • Open source software, firmware, and hardware

Machine Vision Capabilities

  • Object detection and tracking
  • Color detection and filtering
  • Line following algorithms
  • Face detection
  • QR code and barcode reading
  • Template matching
  • Feature detection

Applications

Primary Use Cases

  • Robotics: Vision-guided robots, line followers
  • Industrial: Quality control, part inspection
  • Security: Motion detection, object recognition
  • Education: Computer vision learning projects
  • IoT: Smart cameras, monitoring systems
  • Automotive: Driver assistance prototypes

Expandability

  • Compatible with various lens types via M12 mount
  • Global Shutter Camera Module available separately
  • FLIR Lepton Adapter Module for thermal imaging
  • Various shields available (LCD, WiFi, etc.)

Technical Notes

Performance

  • Most algorithms run at 40-80 FPS on QVGA (320x240) resolution
  • Optimized for real-time machine vision processing
  • Hardware acceleration for common vision tasks

Connectivity Options

  • Direct connection to Arduino via special cable
  • USB connection to Raspberry Pi
  • Multiple interface options (SPI, I2C, UART, USB)
  • Simple communication protocols

Storage Information

  • Location: Cabinet 3, Bin 27
  • Quantity: 1 unit
  • Condition: New, unused
  • Packaging: Original retail packaging with cables
  • Documentation: Includes quick start guide and online resources

Graph View

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