Go Object Detection Package (YOLO V3)

This page summarizes the projects mentioned and recommended in the original post on reddit.com/r/golang

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  • gocv

    Go package for computer vision using OpenCV 4 and beyond.

    The repo leverages gocv and can be run using CUDA(performance results here). If there's any interest I can create one for YOLO V4 as well.

  • yolov3

    Go implementation of the yolo v3 object detection system (by wimspaargaren)

    The repo leverages gocv and can be run using CUDA(performance results here). If there's any interest I can create one for YOLO V4 as well.

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  • yolov5

    YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

    Only an enthusiast but since yolo only states 50fps in an example as a metric to go off of I can only speculate comparisons to yolov5. I'd assume go is slightly faster being a compiled program but not by much since python is acting like a glorified scripting language and the wrapper is doing almost all the work. Go would have a faster inference for small to medium sized loads but python can compensate with batch inference with large sized loads resulting in an insignificant difference. Where go could really excell is if you wanted to make a microservice or something.

  • odam

    ODAM - Object detection and Monitoring

    I'm working on similar project (yolov4): https://github.com/LdDl/odam But, I'm using gocv.Mat -> darknet-based image (go darknet bindings) conversion.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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