how to train on VOC dataset？ about scaledyolov4 HOT 4 OPEN

Example of YOLOv4-large:

1. Follow Training YOLO on VOC to prepare VOC data.
2. Follow coco.data to create voc.data.
3. add argument --data data/voc.data when training.

from scaledyolov4.

@WongKinYiu @infinite013
Now I can confirm @WongKinYiu are wrong.
The YOLO format is not same as before(it also mean is not the same as yolov4 )
(Yolo-CSP copy the code of YOLOv5 of the https://github.com/ultralytics/yolov5.and it is the author of yolov3. It's has the different dataset format :)
now:

Each row is class x_center y_center width height format.

The https://pjreddie.com/darknet/yolo/ make the VOC dataset with:

<object-class> <x> <y> <width> <height>

Although it can train and no error.
But it is wrong as i show at #205

x_center y_center width height format. is a relavtive coordinate.
<x> <y> <width> <height> is the absolute coordinate.

from scaledyolov4.

no, the https://pjreddie.com/darknet/yolo/ make the VOC dataset with relative coordinate.

https://github.com/AlexeyAB/darknet/blob/master/scripts/voc_label.py#L12-L23

from scaledyolov4.

@WongKinYiu
The https://pjreddie.com/darknet/yolo/ make the VOC dataset with relative coordinate. It does.
But when the image is flipped, the angle is changed, and various mosaic enhancements are performed, the values ​​of x and y do not seem to change correctly. Just like the train_batch0 picture shows.

I'm wrong.I think this is a kind of mosaic enhancements.I trained 300 and get good detections.

from scaledyolov4.