How to Use Your Current Cameras for Vision AI
Almost any camera with a USB, RTSP, HTTP-MJPEG, ONVIF, or RTMP feed can power a computer vision pipeline, so you rarely need new hardware to start running models on live video.
GoPro cameras go where fixed cameras can't: on a helmet, a drone, a vehicle bumper, a fishing boat, or a factory cart. That makes them one of the most common sources of training footage for computer vision, from sports analytics and wildlife surveys to field inspections and mobile robotics. Roboflow lets you upload GoPro clips, extract and label frames, train a model on your own data, and deploy it with Roboflow Inference.
The HERO13 Black is the camera to start with: 5.3K60 and 4K120 video, 27 MP photos, HyperSmooth stabilization, and waterproof to 10 m without a housing. The MAX2 records true 8K 360-degree video for full-scene capture you can reframe later, and the compact HERO is the budget 4K pick when size and weight matter.
• Featured: HERO13 Black (5.3K60, 27 MP), MAX2 (8K 360), HERO (4K, 86 g)
• Attributes: Rugged, waterproof, stabilized, wide field of view, battery-powered
• Integration: Upload recorded video to Roboflow, or use USB webcam mode and RTMP live streaming to feed a live Roboflow Inference pipeline
Where Roboflow fits: GoPros are recording cameras first, so most teams start by uploading clips and training on sampled frames. When you need real-time results, connect a HERO over USB-C as a webcam or stream over RTMP to a machine running Roboflow Inference. The same model works either way, and you can retrain as your environment changes.
Want AI without the integration work? Roboflow’s AI1 deployment device packages onboard AI compute, integrated lighting, and an industrial camera into a plug-and-play system for real-time computer vision - no separate camera, lighting, or edge computer to spec.
