El Bruno

Hi !

Sometime ago, I wrote a simple Python class a wrapper for YoloV3. This allows me to write 5 lines of code to analyze an image. Once I use this class, I only press F5 in Visual Studio Code and it’s magic:

A sample usage will be similar to this one. The only required parameter for the YoloV3 analyzer is the confidence. 0.5 is good enough for this demo:

https://gist.github.com/elbruno/11e54a5aba0966a877f2fabfec46c228

And the output is rocking, not only cats, also dogs and humans !

I added a couple of parameters to define if we want labels and bounding boxes in the output image. The same image without bounding boxes will be:

And finally, the main class to perform this. It’s a very simple one, and feel free to use it and remember that you must check the official YoloV3 repository to get the files:

• coco.names
• yolov3.cfg
• yolov3.weights

https://gist.github.com/elbruno/9f98990632ef89c75bece1ca33526aab

References

• Sample Image https://www.pikist.com/free-photo-sxybr
• GitHub, YoloV4
• YOLOv4: Optimal Speed and Accuracy of Object Detection