Pixy CMUcam5

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The Pixy CMUcam5 is a remarkably fast image sensor that is able to be taught to find objects of various shapes, sizes, and colors. With the capability of tracking hundreds of objects simultaneously, the Pixy can be used in robotics, home automation, color coding, and more all the while only providing you with the information that you actually want. Pixy really is a fast and easy-to-use vision system equipped with a dedicated NXP LPC4330 processor making it capable of handling large loads of data from its image sensor and processing it quickly while outputting what it detects 50 times per second.

Pixy processes images from the image sensor and only sends the useful information to your microcontroller, doing so at 50 frames per second. This means each Pixy CMUcam5 processes an entire 640x400 image frame every 1/50th of a second (20 milliseconds). The information is available through one of several interfaces: UART serial, SPI, I2C, USB, or digital/analog output. So your Arduino, Raspberry Pi, BeagleBone, or other microcontroller can easily talk with Pixy and still have plenty of CPU available for other tasks you need them to do.

Pixy uses a color-based filtering algorithm to detect objects. Color-based filtering methods are popular because they are fast, efficient, and relatively robust. Pixy calculates hue and saturation of each RGB pixel from the image sensor and uses these as the primary filtering parameters. The hue of an object remains largely unchanged with changes in lighting and exposure. Changes in lighting and exposure can have a frustrating effect on color filtering algorithms, causing them to break. Pixy’s filtering algorithm is robust when it comes to lighting and exposure changes.

  • 1x Pixy CMUcam5
  • 1x Pixy IO to Arduino ISP Cable
  • Processor: NXP LPC4330, 204 MHz, dual core
  • Image sensor: Omnivision OV9715, ¼", 1280x800
  • Lens field-of-view: 75 degrees horizontal, 47 degrees vertical
  • Lens type: standard M12 (several different types available)
  • Power consumption: 140 mA typical
  • Power input: USB input (5V) or unregulated input (6V to 10V)
  • RAM: 264K bytes
  • Flash: 1M bytes
  • Available data outputs: UART serial, SPI, I2C, USB, digital, analog
  • Dimensions: 2.1" x 2.0" x 1.4
  • Weight: 27 grams

Pixy CMUcam5 Product Help and Resources

Core Skill: Programming

If a board needs code or communicates somehow, you're going to need to know how to program or interface with it. The programming skill is all about communication and code.

2 Programming

Skill Level: Rookie - You will need a better fundamental understand of what code is, and how it works. You will be using beginner-level software and development tools like Arduino. You will be dealing directly with code, but numerous examples and libraries are available. Sensors or shields will communicate with serial or TTL.
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Core Skill: Electrical Prototyping

If it requires power, you need to know how much, what all the pins do, and how to hook it up. You may need to reference datasheets, schematics, and know the ins and outs of electronics.

2 Electrical Prototyping

Skill Level: Rookie - You may be required to know a bit more about the component, such as orientation, or how to hook it up, in addition to power requirements. You will need to understand polarized components.
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Customer Comments

  • Do you think it could detect a squirrel through a window on a tree 1.5 meters away? Is detection effected greatly by light conditions? What is the easiest / cheapest way to put this on a pan/tilt, servo controlled mount? I’m thinking of making a squirrel counter.

    • technically, it’s possible, but you’ll be writing a lot of code. I know it’s been done using a PC with opencv and python, but the pixy isn’t opencv so you’d be porting that code over in the best case, and porting a combination of python+c into ARM C++ is going to be quite a challenge if you’ve never done it.

    • Your best bet on a squirrel counter is to use a cheap PIR detector and an arduino.

      • I don’t think it would be sensitive enough, especially as the sun and the shadows it casts would be in frame.

    • Yes, if you can get the squirrels to wear QR codes !? :-)

      • What about detecting the squirrels directly? I’m not trying to distinguish between different squirrels.

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