The given repo mainly shows how to train custom objects on yolov3.
You only look once (YOLO) is a state-of-the-art, real-time object detection system.The full detail of the working of YOLO and its performance is given in detail in the following link.
Yolov3 is trained on coco dataset but we can train it for our own custom datasets,detailed information is given on the particular github repo
Mainly four custom files should be added for detecting the desired objects, as I have done for mask detection.
As per my model I have trained it till 2000 iterations(total 6000 iterations) that took me nearly 6 hours because of GPU constraints.For efficient training store the last trained model and then ,resume the training from the last pretrained weights.This is the link to the 2000th iterations of the model. This can be used for further efficient training, Trained weights
This is link to the dataset, images
The folder containes the images and the corresponding text files which contain the annotations of the masked and non-masked images. For annotations of images I have used LabelImg , its a tool graphical image annotation tool.
