Cookie 设置
点击 "接受所有 Cookie"，即表示您同意在您的设备上存储 Cookie，以增强网站导航、分析网站使用情况并协助我们的营销工作。更多信息
Explore how Ultralytics and Seeed Studio partnered to launch the reCamera at YOLO Vision 2024, integrating YOLO models for innovative Vision AI applications.
We’re excited to kick off the year by partnering with Seeed Studio which sees the launch of a new computer vision innovation, the reCamera. It is an open-source AI camera designed for real-time computer vision tasks. With native support for Ultralytics YOLO models, the reCamera is compact, and customizable, making it easier than ever for developers and creators to bring their Vision AI projects to life.
The reCamera was first introduced to the AI community at YOLO Vision 2024 (YV24), Ultralytics’ annual hybrid event showcasing cutting-edge innovations and providing a platform for collaboration in Vision AI.
At the event, we were thrilled to have Elaine Wu, Seeed Studio’s Team Lead for AI Robotics, deliver an insightful keynote about the exciting potential of the reCamera. She described it as a device created with care and consideration, saying, “We have thought of every possibility for you.”
In this article, we’ll revisit Elaine Wu’s keynote at YOLO Vision 2024, focusing on the innovative reCamera - a remarkable result of the collaboration between Seeed Studio and Ultralytics - and its unique features and real-world applications.
Elaine started her talk by introducing Seeed Studio, a company that has specialized in Internet of Things (IoT) and AI hardware since 2008. She explained that Seeed Studio provides developers with tools for everything from small-scale prototypes to high-performance systems like the NVIDIA Jetson, helping them bring their ideas to life.
Over the years, Seeed Studio has supported more than 200,000 developers in creating solutions that seamlessly integrate AI and IoT. Elaine also shared how Seeed collaborates with silicon providers, software companies, and the developer community at large to create customizable solutions.
After introducing Seeed Studio, Elaine Wu unveiled Seeed Studio's latest breakthrough, the reCamera, launched in collaboration with Ultralytics. Officially announced at YV24, the reCamera is a flexible, modular, and affordable AI-powered camera with native YOLO support. Ultralytics’ license grants Seeed Studio the rights to integrate Ultralytics YOLO models into reCamera, ensuring compliant and seamless on-device AI functionality for end users. It’s designed to meet the growing need for real-time computer vision tools in a wide range of applications.
Elaine showcased the reCamera as more than just a device - it’s a platform that developers, makers, and businesses can customize and build upon. By making it open-source, Seeed Studio encourages the AI community to create solutions tailored to their needs, whether for IoT, robotics, or industrial applications.
“We define it as a flexible Vision AI platform for anyone to design their own camera,” Elaine noted, showcasing that the reCamera’s modular design and affordability make Vision AI accessible to everyone, opening the door for innovation across industries.
So, what does it really mean when we say the reCamera is the first open-source programmable AI camera? The reCamera has open source product design and provides modular hardware of sensor board, core board, and base board to customize. The device is built to give developers the flexibility to adapt it to their needs with ease. It also comes with native support of Ultralytics YOLO models, enabling seamless use of YOLO’s advanced computer vision capabilities straight out of the box.
Native support makes it possible for the reCamera to be fully optimized to run YOLO models like Ultralytics YOLOv8 and Ultralytics YOLO11 without any setup or compatibility issues. With the Ultralytics models already pre-installed and ready to deploy, the need for additional setup steps like integrating software or dealing with extra costs is eliminated, so developers can focus on building their applications.
Whether you’re developing AIoT solutions, working with robotics, or tackling any computer vision project, the reCamera is intended to help you get started quickly and effortlessly.
Elaine Wu also elaborated on the technical strengths of the reCamera, and how it overcomes the limitations of traditional IP (Internet Protocol) cameras.
Unlike conventional cameras, which often require external hardware like mini PCs or servers to process video and run AI models, the reCamera integrates everything into a single compact unit.
This standalone design makes it easier to deploy and removes the need for additional devices. It’s also fully programmable, so users can run AI models directly on the device without relying on a separate host machine, making it a more efficient and versatile solution.
At the heart of the reCamera is the SG200X processor, built using the RISC-V architecture. This processor is specifically designed for edge AI applications, delivering powerful performance while using minimal energy.
It supports video technologies like H.264 and H.265, which compress video files to save storage and bandwidth without losing quality. Additional features like HDR (High Dynamic Range) imaging, 3D noise reduction, and lens correction ensure that the visuals are clear and professional, even in challenging conditions.
With the ability to perform 1 trillion operations per second (1 TOPS), the processor can handle demanding tasks like real-time object detection, and a smaller 8-bit microcontroller handles simpler operations to save power.
The reCamera also stands out for its modular design, which includes three main parts: the core board, sensor board, and baseboard. Developers can swap and upgrade components easily.
For example, you can replace the camera sensor for higher resolution or add extra hardware like microphones or displays. The baseboard offers flexible communication options, including USB, Ethernet, and more advanced interfaces like Power over Ethernet (PoE) and RS-485, making it adaptable to various use cases.
The reCamera is a reliable tool for a range of real-world applications. Its advanced computer vision capabilities and adaptability make it a great fit for developers and businesses looking to integrate AI-enabled solutions into their projects.
Some of its key applications include:
With its flexibility, compact size, and ease of integration, the reCamera can help deliver impactful AI solutions for a variety of computer vision needs.
Elaine Wu captured the audience’s attention with a live demonstration of the reCamera, showing just how easy it is to set up and use. Using Node-RED, a visual programming tool, she walked through the simple process of deploying the reCamera: set the resolution, upload a YOLO model, and deploy. In just a few moments, the reCamera was live and accurately performing real-time object detection.
During the demo, the reCamera quickly identified everyday objects like a bottle, cup, and remote on her desk. Elaine explained that its seamless integration with Ultralytics YOLO models allows it to deliver fast, reliable results, making it a great option for developers who want a straightforward way to implement Vision AI without coding.
She also pointed out reCamera’s flexibility regarding video quality and customization. The device supports recording in up to 2K resolution and sensor upgrades to improve performance even further.
Wrapping up her talk at YV24, Elaine Wu encouraged the developer community to explore reCamera’s open-source platform, with hardware schematics and the reCamera OS already available on GitHub, and plans to release application designs in the future.
The reCamera is a major step toward simplifying AI model deployment with pre-installed Ultralytics YOLO models, and it gives developers the freedom to customize their solutions without needing coding expertise. The vision behind the reCamera is to create a collaborative ecosystem that inspires innovation and new possibilities in Vision AI.
The reCamera, developed by Seeed Studio in partnership with Ultralytics, is a game-changing hardware solution featuring native integration with YOLO models. It simplifies deploying pre-installed models in production environments, offering developers four versatile versions to suit various needs. This collaboration marks an important step forward in making advanced computer vision technology more accessible and adaptable for a wide range of applications.
For more information on AI and its applications, visit our GitHub repository and join our community. You can also check out our solutions pages for innovations in sectors like AI in self-driving and agriculture. 🚀
