The OpenMV Cam is a small, low power, microcontroller board featuring an STM32H743II Arm® Cortex® M7 processor running at 480MHz, which allows you to easily implement applications using machine vision in the real world. It is equipped with 32MB of SDRAM, 1MB of RAM and 2MB of flash. You program the OpenMV Cam in high-level Python scripts (courtesy of the MicroPython Operating System) instead of C/C++. This makes it easier to deal with the complex outputs of machine vision algorithms and working with high-level data structures. But you still have total control over your OpenMV Cam and its I/O pins in Python. You can easily trigger taking pictures and videos on external events or execute machine vision algorithms to figure out how to control your I/O pins.

All this programming can be done on the OpenMV IDE which makes it easy to program your OpenMV Cam. OpenMV IDE features a modern Python multi-file text editor, a slick serial terminal, and a frame buffer to visualize what your OpenMV Cam sees in real-time.

Features:

STM32H743II processor to realize machine vision applications
Compact size for easy deployment in robotics projects
Low power consumption for prolonged use
Micropython support with easy-to-use OpenMV IDE for quick and convenient project integration
High resolution OV5640 image sensor (2592x1944/ 5MP) for better image processing
Removable camera module system to realize advanced applications
Support for various shields to further expand your projects
Full speed USB (12Mbs) interface with your computer - Your OpenMV Cam will appear as a Virtual COM Port and a USB Flash Drive when plugged in.
A μSD Card socket capable of 100Mbs reads/writes which allows your OpenMV Cam to record video and easy pull machine vision assets off of the μSD card.
An SPI bus that can run up to 100Mbs allowing you to easily stream image data off the system to either the LCD Shield, the Wi-Fi Shield, or another microcontroller.
An I2C Bus, CAN Bus, and an Asynchronous Serial Bus (TX/RX) for interfacing with other microcontrollers and sensors.
Two I/O pins with support for servo control in robotics projects
Interrupts and PWM on all I/O pins with 10 I/O pins on the board for project expandability
An RGB LED for status indication and two high power 850nm IR LEDs

Specifications:

Processor :
- ARM® 32-bit Cortex®-M7 CPU
- w/ Double Precision FPU
- 480 MHz (1027 DMIPS)
- Core-Mark Score: 2400
RAM Layout :
- 32 MB of external 32-bit SDRAM clocked at 100 MHz for 400 MB/s of bandwidth.
- 256KB DMA Buffers
- 32MB Frame Buffer/Stack
- 256KB .DATA/.BSS/Heap/Stack
Flash Layout :

128KB Bootloader
16MB Embedded Flash Drive
1792KB Firmware
32 MB (16 MB usable right now) of external quadspi flash clocked at 100 MHz in 4-bit DDR mode for 100 MB/s of bandwidth.

Supported Image Formats :
- Grayscale
- RGB565
- JPEG (and BAYER)
Maximum Supported Resolutions :
- Grayscale: 640x480 and under
- RGB565: 320x240 and under
- Grayscale JPEG: 640x480 and under
- RGB565 JPEG: 640x480 and under
Lens Info :
- Focal Length: 2.8mm
- Aperture: F2.0
- Format: 1/3"
- HFOV = 70.8°, VFOV = 55.6°
- Mount: M12*0.5
- IR Cut Filter: 650nm (removable)
Peripherals :
- 12-bit ADC and a 12-bit DAC
- 2 x I/O pins with support for servo control
- Interrupts and PWM on all I/O pins (10 I/O pins on the board)
- An RGB LED and two high power 850nm IR LEDs

Electrical Info :
- All pins are 5V tolerant with 3.3V output.
- All pins can sink or source up to 25mA.
- P6 is not 5V tolerant in ADC or DAC mode.
- Up to 120mA may be sinked or sourced in total between all pins.
- VIN may be between 3.6V and 5V.
- Do not draw more than 250mA from your OpenMV Cam's 3.3V rail.
Power Consumption :
- Idle - No μSD Card: 140mA @ 3.3V
- Idle - μSD Card: 140mA @ 3.3V
- Active - No μSD Card: 230mA @ 3.3V
- Active - μSD Card: 240mA @ 3.3V
Storage Temperature : -40°C to 125°C
Operating Temperature : -20°C to 70°C
Weight : 17g
Dimensions (L*W*H) : 45 x 36 x 29mm

Applications:

The OpenMV Cam can be used for the following things currently (more in the future):

Frame Differencing
- You can use Frame Differencing on your OpenMV Cam to detect motion in a scene by looking at what's changed. Frame Differencing allows you to use your OpenMV Cam for security applications. Check out the video of the feature here.
Color Tracking
- You can use your OpenMV Cam to detect up to 16 colors at a time in an image (realistically you'd never want to find more than 4) and each color can have any number of distinct blobs. Your OpenMV Cam will then tell you the position, size, centroid, and orientation of each blob. Using color tracking your OpenMV Cam can be programmed to do things like tracking the sun, line-following, target tracking, and much, much, more. Video demo here.
Marker Tracking
- You can use your OpenMV Cam to detect groups of colors instead of independent colors. This allows you to create color makers (2 or more color tags) which can be put on objects allowing your OpenMV Cam to understand what the tagged objects are. Video demo here.
Face Detection
- You can detect Faces with your OpenMV Cam (or any generic object). Your OpenMV Cam can process Haar Cascades to do generic object detection and comes with a built-in Frontal Face Cascade and Eye Haar Cascade to detect faces and eyes. Video demo here.
Eye Tracking
- You can use Eye Tracking with your OpenMV Cam to detect someone's gaze. You can then, for example, use that to control a robot. Eye Tracking detects where the pupil is looking versus detecting if there's an eye in the image.
Person Detection
- You can detect if there's a person in the field of view using our built-in person detector TensorFlow Lite model. Video demo here.
Optical Flow
- You can use Optical Flow to detect translation of what your OpenMV Cam is looking at. For example, you can use Optical Flow on a quad-copter to determine how stable it is in the air. See the video of the feature here.
QR Code Detection/Decoding
- You can use the OpenMV Cam to read QR Codes in its field of view. With QR Code Detection/Decoding you can make smart robots that can read labels in the environment. You can see our video on this feature here.
Data Matrix Detection/Decoding
- The OpenMV Cam H7 can also detect and decode data matrix 2D barcodes too. You can see our video on this feature here.
Linear Barcode Decoding
- The OpenMV Cam H7 can also decode 1D linear bar codes. In particular, it can decode EAN2, EAN5, EAN8, UPCE, ISBN10, UPCA, EAN13, ISBN13, I25, DATABAR, DARABAR_EXP, CODABAR, CODE39, CODE93, and CODE128 barcodes. You can see our video on this feature here.
AprilTag Tracking
- Even better than QR Codes above, the OpenMV Cam H7 can also track AprilTags at 160x120 at up to about 12 FPS. AprilTags are rotation, scale, shear, and lighting invariant state-of-the-art fiducial markers. We have a video on this feature here.
Line Detection
- Infinite line detection can be done speedily on your OpenMV Cam at near max FPS. And, you can also find non-infinite length line segments too. You can see our video of this feature here. Additionally, we support running linear regressions on the image for use in line following applications like this DIY Robocar.
Circle Detection
- You can use the OpenMV Cam H7 to easily detect circles in the image. See for yourself in this video.
Rectangle Detection
- The OpenMV Cam H7 can also detect rectangles using our AprilTag library's quad detector code. Check out the video here.
Template Matching
- You can use template matching with your OpenMV Cam to detect when a translated pre-saved image is in view. For example, template matching can be used to find fiducials on a PCB or read known digits on a display.
Image Capture
- You can use the OpenMV Cam to capture up to 640x480 Grayscale/RGB565 BMP/JPG/PPM/PGM images. You directly control how images are captured in your Python script. Best of all, you can preform machine vision functions and/or draw on frames before saving them.
Video Recording
- You can use the OpenMV Cam to record up to 640x480 Grayscale/RGB565 MJPEG video or GIF images (or RAW video). You directly control how each frame of video is recorded in your Python script and have total control on how video recording starts and finishes. And, like capturing images, you can preform machine vision functions and/or draw on video frames before saving them.
TensorFlow Lite for Microcontrollers Support: TensorFlow Lite support lets you run custom image classification and segmentation models onboard your OpenMV Cam. With TensorFlow Lite support you can easily classify complex regions of interest in view and control I/O pins based on what you see.

Documents:

Package Includes:

1 x OpenMV Cam H7 Plus
2 x 8-Pin Female Headers
1 x Micro-USB Cable
1 x Hole Plate
1 x Proto PCB Board
1 x Right Angle Fixing Plate
4 x Supporting Screws
4 x Nuts
4 x Gaskets

Processor Specifications
Memory	RAM Layout : 256KB.DATA/.BSS/Heap/Stack 512KB Frame Buffer/Stack RAM Layout : 32 MB of external 32-bit SDRAM clocked at 100 MHz for 400 MB/s of bandwidth. 256KB DMA Buffers 32MB Frame Buffer/Stack 256KB .DATA/.BSS/Heap/Stack Flash Layout : 128KB Bootloader 16MB Embedded Flash Drive 1792KB Firmware 32 MB (16 MB usable right now) of external quadspi flash clocked at 100 MHz in 4-bit DDR mode for 100 MB/s of bandwidth.
Processor	ARM® 32-bit Cortex®-M7 CPU w/ Double Precision FPU 480 MHz (1027 DMIPS) Core-Mark Score: 2400
Sensor Specifications
Sensor size	1/3"
Resolution	Maximum Supported Resolutions : Grayscale: 640x480 and under RGB565: 320x240 and under Grayscale JPEG: 640x480 and under RGB565 JPEG: 640x480 and under
Lens Specifications
Focal Length	Focal Length: 2.8mm
Field of View	HFOV = 70.8°, VFOV = 55.6°
Lens Mount	M12*0.5