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A kit consisting of an M.2 HAT+ module and a Hailo-8L accelerator with a performance of 13 TOPS enables the rapid development of advanced real-time AI applications on the Raspberry Pi 5. This setup allows neural networks for object detection and segmentation to run on the Hailo-8L coprocessor, leaving the Raspberry Pi 5 CPU available for other tasks. The foundation has also prepared rpicam-apps libraries that significantly facilitate the creation of AI projects. Raspberry Pi SC1438

The Raspberry Pi AI Kit is an advanced solution for integrating artificial intelligence with the Raspberry Pi 5, created in collaboration with Hailo. The kit includes the Raspberry Pi M.2 HAT+ and the Hailo AI accelerator module, enabling efficient real-time neural network processing with minimal latency and low power consumption. The AI module achieves an impressive performance of 13 tera operations per second (TOPS) thanks to the Hailo-8L accelerator. Communication with the computer is via a PCIe 3.0 x1 interface, ensuring fast and efficient communication. Once installed on the Raspberry Pi 5, the module allows for the rapid development of complex computer vision applications. With full integration into the Raspberry Pi OS operating system, the AI module is automatically detected and ready to use, allowing users to immediately start working with AI.
Software is a key component of the Raspberry Pi AI Kit. With rpicam-apps, users can easily integrate neural network inference with the image processing pipeline. The pre-installed Hailo Tappas libraries enable the creation of advanced AI applications in just a few hundred lines of C++ code. The software installation process is simple and intuitive, with full instructions available in the beginner's guide.
Manufacturer BTC Korporacja sp. z o. o. Lwowska 5 05-120 Legionowo Poland sprzedaz@kamami.pl 22 767 36 20
Responsible person BTC Korporacja sp. z o. o. Lwowska 5 05-120 Legionowo Poland sprzedaz@kamami.pl 22 767 36 20
Minicomputer version 5 with 16GB RAM equipped with two microHDMI ports, 2 USB 3.0 ports and 2 USB 2.0 ports and a USB-C power connector. The processor is a 4-core Broadcom BCM2712 clocked at 2.4GHz. The board also has dual-band WiFi, Bluetooth 5.0 with BLE support, PCI Express 2.0 interface and a real-time clock. This model offers exceptional performance thanks to 16GB RAM, which makes it perfect for advanced applications
A set of 15 Velleman precision screwdrivers (flat, cross, torx). The length is 120mm
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No product available!
HK HKPilot Mega 2.7 Flight Controller USB/GYRO/ACC/MAG/BARO (56052)
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HK AfroFlight Naze32 Acro AbuseMark FunFly Controller (55819)
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No product available!
HK Thunder QQ Super - Multi-Rotor Flight Controller (65595)
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The contactless temperature meter operates in the temperature range from - 18ºC to +400 ºC. The measurement is triggered by a trigger, and the built-in laser pointer makes it easy to aim at the object. A clear display is used to read measured data. UNI-T UT300C
No product available!
Color sensor module (TCS3200) with LED backlight
No product available!
Digital magnetic field sensor module, electronic compass, +/- 5 degrees, UART, I2C, RoHS
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One-touch touch sensor module, illuminated with blue diodes, with AT42QT1010, ERAmatic
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One-touch sensor module, illuminated with green LEDs, with AT42QT1010, ERAmatic
No product available!
One-touch touch sensor module, illuminated with white diodes (warm color), with AT42QT1010, ERAmatic
No product available!
Evaluation Board for Freescale Xtrinsic Sensors - Sensors, Altitude & Pressure Measurement, Magnetic Field & Physical Position Detection
For use with Freescale FRDM-KL25z and Raspbery Pi Host Platforms
No product available!
Pin header goldpin black 1x3 pins. Straight connector for through-hole assembly. 2.54mm pitch
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No product available!
Joshua J. Drake, Zach Lanier, Collin Mulliner, Pau Oliva Fora, Stephen A. Ridley, Georg Wicherski
No product available!
A kit consisting of an M.2 HAT+ module and a Hailo-8L accelerator with a performance of 13 TOPS enables the rapid development of advanced real-time AI applications on the Raspberry Pi 5. This setup allows neural networks for object detection and segmentation to run on the Hailo-8L coprocessor, leaving the Raspberry Pi 5 CPU available for other tasks. The foundation has also prepared rpicam-apps libraries that significantly facilitate the creation of AI projects. Raspberry Pi SC1438