Description
The Huskylens is a user-friendly AI Camera and Vision Sensor. It is packed with a variety of features, including face recognition, object tracking, object recognition, line tracking, color recognition, and tag (QR code) recognition, making it an incredibly versatile product from DFrobot.
By utilizing the UART/I2C port, the HuskyLens can seamlessly connect with popular main control boards like Arduino, micro:bit, Raspberry Pi, and LattePanda. This allows you to embark on highly imaginative projects without having to grapple with complex algorithms.
The HuskyLens is an incredibly user-friendly AI Camera. You can easily modify various algorithms by pressing the function button. Once you click the learning button, the HuskyLens initiates the learning process, allowing it to recognize new objects.
Furthermore, the HuskyLens comes equipped with a 2.0 inch IPS screen, enabling you to adjust parameters without having to connect to a PC.
The HuskyLens AI Camera is built to be intelligent, thanks to its advanced machine learning technology. This technology allows the HuskyLens to effortlessly recognize faces and objects. Furthermore, by long-pressing the learning button, the HuskyLens can constantly learn new things from various angles and ranges, resulting in increased accuracy with every new learning experience.
DFRobot's HuskyLens is equipped with the latest specialized AI chip, the Kendryte K210. This chip boasts a remarkable performance, running neural network algorithms at speeds 1,000 times faster than the STM32H743. The HuskyLens can capture even fast-moving objects, thanks to this impressive technology.
By incorporating the HuskyLens into your projects, you can explore a host of new ways to interact with your environment or yourself. These applications include interactive gesture control, autonomous robots, smart access control, and interactive toys, among many others. With the HuskyLens, the possibilities for innovative projects are endless.
The HuskyLens is capable of tracking objects and can be programmed to learn specific gestures. It can recognize and track the patterns of hand movements and provide their exact positions. With this data, you can create incredible interactive projects with remarkable ease.
The HuskyLens vision sensor has the ability to detect and track lines. While line following is not a new concept and there are plenty of methods and algorithms available, most of them require extensive parameter tuning. However, the HuskyLens offers a new and simplified way to approach line following. By simply clicking a button, it can initiate the learning and tracking of new lines.
The HuskyLens machines can serve as the visual "eyes" for your robots, enabling them to recognize you, interpret your hand gestures, and assist you with various tasks, such as organizing items.
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HuskyLens Mainboard x1
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M3 Screws x6
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M3 Nuts x6
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Small Mounting Bracket x1
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Heightening Bracket x1
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Gravity 4-Pin Sensor Cable x1
FAQs:
Q: What are the main features of the HuskyLens AI Camera?
A: The HuskyLens AI Camera has features like face recognition, object tracking, object recognition, line tracking, color recognition, and tag (QR code) recognition.
Q: Can the HuskyLens connect with popular main control boards?
A: Yes, the HuskyLens can seamlessly connect with popular main control boards like Arduino, micro:bit, Raspberry Pi, and LattePanda through the UART/I2C port.
Q: How can I modify algorithms with the HuskyLens?
A: You can easily modify various algorithms by pressing the function button on the HuskyLens.
Q: Does the HuskyLens have a learning capability?
A: Yes, the HuskyLens can initiate the learning process to recognize new objects. By long-pressing the learning button, it can constantly learn new things from various angles and ranges, increasing its accuracy over time.
Q: What is the performance of the HuskyLens AI Camera's specialized AI chip?
A: The HuskyLens AI Camera is equipped with the Kendryte K210 AI chip, which runs neural network algorithms 1,000 times faster than the STM32H743, allowing it to capture fast-moving objects.
