Yahboom K230 Vision Module Standard Edition CanMV Face Recognition Camera Sensor

Yahboom K230 Vision Module Standard Edition CanMV Face Recognition Camera Sensor 1. The K230 visual recognition module is equipped with a 1080P60FPS high-definition camera, is compact and exquisite, and can be easily integrated into various AI visual application scenarios. It is an ideal choice for electronic competitions. 2. The K230 is programmed and developed using MicroPython language. Users can easily handle multiple visual applications such as color recognition, object counting, QR code recognition, face recognition, character recognition, and self-training without mastering AI model algorithms, greatly lowering the threshold for AI learning. 3. The module integrates a WiFi chip and supports IoT connections. It can be connected to a cloud platform to access large language models, enabling intelligent dialogue and voice question-answering functions. 4. Windows-based upper computer software is provided, supporting RTSP real-time video stream monitoring, and integrating videoimage processing tools, data generators, text tools, and other contents. 5. Audio processing support: The K230 integrates a microphone and supports audio recording, enabling keyword wake-up and voice-to-text functions. Combined with large language models, it can conduct language dialogues and provide an intelligent interactive experience. 6. Expandable speaker: It supports external speakers and, in combination with large language models, can achieve voice dialogue. It can also be linked with AI image processing functions to broadcast visual recognition results in real time. 7. Supports multiple development platforms: It can be connected to PC computers, MSPMO, STM32, ESP32, PICO, Raspberry Pi, Jetson, RDK, and other mainstream controllers for development. 8. CanMV development environment: The K230 visual recognition module uses CanMV IDE as the development environment. It is simple and convenient to operate, with the IDE providing function input parameter and related content prompts. The code does not require compilation and can be modified and