OpenMV Cam M7 - Machine Vision with Python and Arduino
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OpenMV Cam M7 - Machine Vision with Python and Arduino

( OpenMV )

The OpenMV Cam is a small, low power, microcontroller board which allows you to easily implement applications using machine vision in the real-world. 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 video on external events or execute machine vision algorithms to figure out how to control your I/O pins.

The OpenMV Cam features:

  • The STM32F765VI ARM Cortex M7 processor running at 216 MHz with 512KB of RAM and 2 MB of flash. All I/O pins output 3.3V and are 5V tolerant. The processor has the following I/O interfaces:
    • A full speed USB (12Mbs) interface to 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.
    • A SPI bus that can run up to 54Mbs allowing you to easily stream image data off the system to either the LCD Shield, the WiFi Shield, or another microcontroller.
    • An I2C Bus, CAN Bus, and an Asynchronous Serial Bus (TX/RX) for interfacing with other microcontrollers and sensors.
    • A 12-bit ADC and a 12-bit DAC.
    • Three I/O pins for servo control.
    • Interrupts and PWM on all I/O pins (there are 10 I/O pins on the board).
    • And, an RGB LED and two high power 850nm IR LEDs.
  • The OV7725 image sensor is capable of taking 640x480 8-bit Grayscale images or 320x240 16-bit RGB565 images at 30 FPS. Your OpenMV Cam comes with a 2.8mm lens on a standard M12 lens mount. If you want to use more specialized lenses with your OpenMV Cam you can easily buy and attach them yourself.



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.
  • Color Tracking
    • You can use your OpenMV Cam to detect up to 32 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.
  • 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.
  • 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.
  • QR Code Detection/Decoding
    • You can use the OpenMV Cam to read QR Codes in it's field of view. With QR Code Detection/Decoding you can make smart robots which can read labels in the environment. You can see our video on this feature here.
  • Data Matrix Detection/Decoding
    • The OpenMV Cam M7 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 M7 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 M7 can also track AprilTags at 160x120 at up to about 12 FPS. AprilTags are rotation, scale, shear, and lighting invariant state-of-the-art fidicual markers. We have a video on this feature here.
  • Edge/Line Detection
    • You can preform edge detection via either the Canny Edge Detector algorithm or simple high-pass filtering followed by thresholding. After you have a binary image you can then use the Hough Detector to find all the lines in the image. With edge/line detection you can use your OpenMV Cam to easily detect the orientation of objects.
  • 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 M7 to easily detect circles in the image. See for yourself in this video.
  • Rectangle Detection
    • The OpenMV Cam M7 can also detect rectangles using our AprilTag library's quad detector code. Checkout 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 320x240 RGB565 (or 640x480 Grayscale) 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 320x240 RGB565 (or 640x480 Grayscale) MJPEG video or GIF images. 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.

Finally, all the above features can be mixed and matched in your own custom application along with I/O pin control to talk to the real world.


Processor ARM® 32-bit Cortex®-M7 CPU
w/ Double Precision FPU
216 MHz (462 DMIPS)
Core Mark Score: 1082
(compare w/ Raspberry Pi Zero: 2060)
RAM Layout 128KB .DATA/.BSS/Heap/Stack
384KB Frame Buffer/Stack
(512KB Total)
Flash Layout 32KB Bootloader
96KB Embedded Flash Drive
1920KB Firmware
(2MB Total)
Supported Image Formats Grayscale
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"
Angle (Field-of-View): 115°
Mount: M12*0.5
IR Cut Filter: 650nm (removable)
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.
Weight 16g
Length 45mm
Width 36mm
Height 30mm

Power Consumption

Idle - No μSD Card 110mA @ 3.3V
Idle - μSD Card 110mA @ 3.3V
Active - No μSD Card 190mA @ 3.3V
Active - μSD Card 200mA @ 3.3V

Temperature Range

Storage -40°C to 125°C
Operating -20°C to 70°C



A lot of new functionality about to come out in the next firmware update for OpenMV. Here's the list:

ZBar Integration - We've got the ZBar 1D barcode library working on the OpenMV Cam M7. It can decode bar codes oriented in any direction in 640x480 grayscale image at about 3 FPS and decode vertically aligned bar codes in a 640x40 grayscale image at about 20 FPS. So, if you don't mind a slow frame rate it can basically find and decode barcodes in an image generally. Or, you can turn the camera into a linear barcode scanner (640x40 res) for a higher FPS.

ZBar supports for the following types of 1D bar codes:

* EAN2
* EAN5
* EAN8
* ISBN10
* EAN13
* I25
* CODE39
* CODE93
* CODE128

... so, basically every 1D bar code you'll run into. :)

Best of all, finding barcodes is super easy to do. Just call the "find_barcodes()" method on an image and you'll get a list of all 1D barcodes. The method works just like "find_qrcodes()".

Normally, I'd do a demo with ZBar support... but, there's really not that much to look at when you set the resolution to 640x40. Just a lot of black and white lines that look the same.

Note that this feature only works on the OpenMV Cam M7 because we've exhausted the flash space for major new features on the OpenMV Cam M4.

Wireless Frame Buffer Support - As demoed previously with the "Open Terminal" functionality in OpenMV IDE we've now added methods to the firmware for transmitting images to OpenMV IDE over any serial link. The new "compress_for_ide()" and "compressed_for_ide()" methods on images allow you to jpeg compress an image in place or create a jpeg compressed copy. Every 6-bits of the jpeg compressed images are then encoded to a byte valued between 128-191 for transmission to OpenMV IDE.

By encoding the image binary data in this way we're able to transmit images over any serial link without risk of corrupting normal printable text data. This allows you to connect to an OpenMV Cam sending image data in the middle of transmission without issues.

So... wirelessly programming and debugging your OpenMV Cam using REPL now works! However, you'll want to use fast wireless links for sending image data (above 1 mega baud).

WiFi Access Point Mode - With firmware v2.3.0 you'll now be able to setup your WiFi shield to run in Access Point mode so it acts like a WiFi router.

640x480 RGB565 Images/Video - Grayscale 640x480 image/video recording works on your OpenMV Cam M7. However, RGB565 640x480 image/video recording doesn't work because we don't have the RAM.

That said, we've figured out a way around this problem for just image and video recording by storing Bayer images in RAM instead of RGB565 images. This cuts the required space in half. Using a Bayer image does incur an overhead of linear interpolation per pixel access so we don't plan to build this feature out for image processing functions. But, we'll make it so you can take 640x480 RGB565 images and 640x480 color MJPEG video/gifs. Note that we don't expect the frame rate to be impressive for video but it will be great for taking snapshots.

CMUcam5 Pixy Emulation - We've received quite a few requests from folks looking to replace their CMUcam5 Pixy with the OpenMV Cam so that they can use AprilTags in their application versus color tracking without having to change their Arduino code. So... we've now got example scripts for this:

AprilTags using Pixy Protocol over I2C
AprilTags using Pixy Protocol over SPI
AprilTags using Pixy Protocol over UART
Color Tracking using Pixy Protocol over I2C
Color Tracking using Pixy Protocol over SPI
Color Tracking using Pixy Protocol over UART

These examples scripts also really show you how to use the OpenMV Cam's I/O with computer vision support. Being able to control the filtering of results on your OpenMV Cam before transmitting them is very powerful.

MAVLink Support - The same folks asking for Pixy Emulation also wanted MAVLink support for integration with ArduCopter and the Pixhawk. So, we added an example script for sending out AprilTag detection data for automatic landing support and optical flow data for use in GPS denied environments:


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