noahmr/zed-yolov5
Object detection with YOLOv5, TensorRT and Stereolabs ZED
This project helps roboticists or automation engineers integrate real-time object detection into their systems using a Stereolabs ZED stereo depth camera. You feed it a pre-trained YOLOv5 model and a live camera feed or recorded video, and it outputs bounding boxes and class labels for detected objects, displayed visually or for system consumption. It's designed for those building high-performance, embedded vision applications.
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Use this if you need fast, accurate object detection with depth information for applications like robotic navigation, industrial automation, or real-time spatial awareness, leveraging the Stereolabs ZED camera and NVIDIA Jetson platforms.
Not ideal if you need a solution for standard 2D cameras, are not working with NVIDIA hardware, or prefer a Python-based implementation for simpler scripting and prototyping.
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Language
C++
License
MIT
Category
Last pushed
Jan 18, 2022
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