Go YOLO V3
This repository provides a plug and play implementation of the Yolo V3 object detection system in Go, leveraging gocv.
Prerequisites
Since this implementation builds on top of the gocv library, make sure you either use one of the provided docker images to run the example, or install the opencv dependencies on your system.
Furthermore, make sure you've got the yolov3 models downloaded before running the examples.
Simply run $ make models
Run the examples
Bird example
$ make bird-example
Output
Street example
$ make street-example
Output
Webcam example
$ make webcam-example
Note that this will not run smoothly on most machines, as the default net target type is set to NetTargetCPU. If you have cuda installed, adjust the net initialization to:
conf := yolov3.DefaultConfig()
// Adjust the backend and target type
conf.NetBackendType = gocv.NetBackendCUDA
conf.NetTargetType = gocv.NetTargetCUDA
// Create the net with created config
yolonet, err := yolov3.NewNetWithConfig(vehicleWeights, vehicleNetcfg, cocoNames, conf)
if err != nil {
log.WithError(err).Fatal("unable to create yolo net")
}
Cuda example
Execute 50 fps test render with cuda, also see the CUDA section.
$ make cuda-example
CUDA
If you're interested in running yolo in Go with CUDA support, check the cmd/example_cuda to see a dummy example and test results of running object detection at 50 fps. The gocv cuda README provides detailed installation instructions.
Issues
If you have any issues, feel free to open a PR or create an issue!
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