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Yolo_mark
GUI for marking bounded boxes of objects in images for training neural network Yolo v3 and v2
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InfluxDB
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My work heavily involves the use of the yolo algorithm such as optimising it for performance on mobile devices. Yolov5 is made by a private company that has been pushing sub bar models for a while. I've benchmarked their smallest models comparing them to Yolov4 tiny and the results were staggering, v4 being around 3-4 times faster. Yolov4 has way more resources for development, I highly suggest checking out this repo https://github.com/AlexeyAB/darknet
There is still no point retraining your model with its own output tho. You will get better results annotating it yourself. You can make use of this annotation tool https://github.com/darkpgmr/DarkLabel to save annotation time. If your training images are frames in a video, by using this tool you can propagate your bounding boxes into future frames. The boxes will eventually drift tho, so you will have to reinitialise the boxes every now and then.
One interesting thing to consider is about using a new model's output as training data is the following. If you use some object tracking algorithm like SORT, you might be able to find frames where the object was "tracked" even though the model didn't detect the object (some type of flickering). In this case, you're able to run the model on video and make it better by giving it these new bounding boxes based on "tracking". Does that make sense?