noahmr/zed-yolov5

Object detection with YOLOv5, TensorRT and Stereolabs ZED

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Emerging

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.

No commits in the last 6 months.

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.

robotics industrial-automation real-time-vision embedded-systems object-detection
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 16 / 25
Community 14 / 25

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Stars

8

Forks

3

Language

C++

License

MIT

Last pushed

Jan 18, 2022

Commits (30d)

0

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