Machine learning is revolutionizing software development, but until now, it was only in the hands of a few experts. At Adafruit, we believe that everyone should have access to this amazing technology. That's why we've partnered with Lobe to bring you an easy-to-use machine learning kit. With this kit, you can turn your machine learning ideas into reality! This kit comes with all the necessary Pi accessories at a 20% discount compared to buying the parts individually. All you need to add is a Raspberry Pi 4 with 2GB of RAM or more. The kit includes: Adafruit BrainCraft HAT for Raspberry Pi 4 machine learning, Raspberry Pi Camera Board v2 with 8 Megapixels, Adafruit Raspberry Pi Camera Board Case with 1/4' Tripod Mount, Official Raspberry Pi Power Supply 5.1V 3A with USB C (1.5 meters long), Flex Cable for Raspberry Pi Camera or Display (300mm / 12'), and an 8GB SD/MicroSD Memory Card. Note that the Raspberry Pi 4 computer is not included, but we do offer a version of this kit with a Pi 4. To create machine learning models, we'll use Lobe, a free and user-friendly app. Just show Lobe some examples of what you want it to learn, and it will train a custom model for you. You can then use this model directly on the Raspberry Pi or within Lobe itself. No soldering is required. Simply plug the parts together, and you can start your machine learning journey within an hour! The BrainCraft HAT is designed to let you 'craft brains' for machine learning on the edge using microcontrollers and microcomputers. It has a 240×240 TFT IPS display for inference output, slots for camera connector cables for imaging projects, a 5-way joystick, a button for UI input, left and right microphones, stereo headphone out, stereo 1W speaker out, three RGB DotStar LEDs, two 3-pin STEMMA connectors on PWM pins for driving NeoPixels or servos, and a Grove/STEMMA/Qwiic I2C port. A controllable mini fan on the bottom keeps your Pi cool during intense AI calculations. There's also an On/Off switch to completely disable the audio codec, ensuring privacy. Features include a 1.54' IPS TFT display with 240x240 resolution for text or video, stereo speaker ports for various audio playback, stereo headphone out, stereo microphone input for smart home assistants, two 3-pin JST STEMMA connectors for additional devices, a STEMMA QT plug-and-play I2C port compatible with many boards, a 5-Way Joystick + Button for user control, and three RGB DotStar LEDs for colorful feedback. The STEMMA QT port allows you to attach heat image sensors like the Panasonic Grid-EYE or MLX90640, which can be used as person detectors even in the dark. You can also attach an external accelerometer for gesture or vibration sensing in industrial projects. Check out the Lobe GitHub repo: https://github.com/lobe/lobe-adafruit-kit.
Using this machine learning kit is a breeze. First, gather all the parts in the kit. Remember, you'll need to add a Raspberry Pi 4 with 2GB of RAM or more. Plug the parts together as described in the kit - no soldering required. You can start your machine learning journey within an hour. To create machine learning models, open the Lobe app. Show Lobe some examples of what you want it to learn, and it will train a custom model for you. You can use this model on the Raspberry Pi or within Lobe itself. When using the BrainCraft HAT, be aware that the controllable mini fan on the bottom can help keep your Pi cool during intense AI calculations. You can turn it on when needed. Also, use the On/Off switch to disable the audio codec when you want to ensure privacy. For maintenance, keep the parts clean and dry. Avoid exposing them to extreme temperatures or humidity. If you want to expand your projects, use the STEMMA QT port to attach additional sensors like heat image sensors or an external accelerometer. Have fun exploring the world of machine learning with this kit!
