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GithubSingTown's intelligent camera solution based on OpenMV enables real-time recognition of human gestures and motion changes. Utilising AI image recognition and machine vision technologies, the system can accurately identify various gestures such as waving, making a fist, forming a heart shape, and giving a thumbs-up. It also supports custom training models and is widely applied in scenarios including human-computer interaction, intelligent control, teaching demonstrations, and contactless operations.

In the field of intelligent interaction and automatic control, gesture recognition is becoming a crucial method for human-machine communication. SingTown Technology leverages the OpenMV platform to develop an efficient smart camera system capable of real-time recognition and interpretation of users' hand movements and posture changes.
The system employs computer vision algorithms to perform background separation, key point localisation, and morphological analysis on the captured images, thereby identifying various types of gesture actions.
After training with AI models, the system can not only recognise standard gestures such as waving, clenching fists, extending palms, and "OK" signs, but also expand custom commands based on user needs. For example, in smart homes, waving can be used to control lights or curtains; in display devices, it can be used to switch pages, play, or pause; in education and medical fields, it is suitable for contactless interaction and command control.
The OpenMV intelligent camera boasts a compact design, low power consumption, and rapid response. It supports on-device computing, allowing for real-time recognition without reliance on external servers, thereby enabling edge deployment. The system can also automatically adjust parameters according to ambient light conditions, ensuring stable operation both indoors and outdoors, during the day or at night.
SingTown deeply integrates edge AI, image recognition, and machine vision technologies, enabling smart cameras not only to "see" human actions but also to "understand" their intentions, providing a new embedded vision solution for intelligent control, human-computer interaction, and automation applications.

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