Tutorials Link
Hailo-8 AI HAT+ for Raspberry Pi 5
This AI acceleration module designed for Raspberry Pi 5. Hailo-8/8L has a computing power of up to 26TOPS or 13TOPS. These processors can provide Raspberry Pi 5 with excellent edge AI computing capabilities, greatly improving the execution speed of complex applications such as image recognition, object detection, and natural language processing. The module fully supports mainstream deep learning frameworks such as TensorFlow, TensorFlow Lite, ONNX, Keras, and Pytorch, allowing users to easily develop models to meet the needs of various AI projects.
Features
1) Providing 13/26TOPS computing power, it provides Raspberry Pi 5 with better AI acceleration performance.
2) The M.2 interface design ensures high-speed data transmission with Raspberry Pi 5.
3) Compatible with mainstream deep learning frameworks such as TensorFlow, TensorFlow Lite, ONNX, Keras, and Pytorch, it is convenient for users to directly deploy AI models in a familiar environment.
4) The structure is compact, takes up little space, and does not affect other functional expansions of Raspberry Pi 5.
Hailo-8/8L AI HAT+ for Raspberry Pi 5
Vendor: Yahboom
SKU: 6000301722
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Tutorials Link
Hailo-8 AI HAT+ for Raspberry Pi 5
This AI acceleration module designed for Raspberry Pi 5. Hailo-8/8L has a computing power of up to 26TOPS or 13TOPS. These processors can provide Raspberry Pi 5 with excellent edge AI computing capabilities, greatly improving the execution speed of complex applications such as image recognition, object detection, and natural language processing. The module fully supports mainstream deep learning frameworks such as TensorFlow, TensorFlow Lite, ONNX, Keras, and Pytorch, allowing users to easily develop models to meet the needs of various AI projects.
Features
1) Providing 13/26TOPS computing power, it provides Raspberry Pi 5 with better AI acceleration performance.
2) The M.2 interface design ensures high-speed data transmission with Raspberry Pi 5.
3) Compatible with mainstream deep learning frameworks such as TensorFlow, TensorFlow Lite, ONNX, Keras, and Pytorch, it is convenient for users to directly deploy AI models in a familiar environment.
4) The structure is compact, takes up little space, and does not affect other functional expansions of Raspberry Pi 5.
Questions & Answers
Have a Question?
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is it possible to use it with rosmaster m1?
Yes, it can be used with the rosmaster M1 and there is space for installation.















