For example, if you have a trained model, you can generate annotations of test images after getting class names and bounding boxes (just for labelImg, like this).
For testing, just try this script
from convertmask.utils.img2xml import processor_singleObj
if __name__ == "__main__":
"""will cause some error on Windows \n
such as the file or dirname starts with 't' or 'n' or numbers \n
"""
f = open("./test_img2xml", 'w')
f.writelines(
processor_singleObj.img2xml("test", "aa", "test\\test.xx", 12, 23,
"aaa", 123, 444, 4523, 664))
f.close()
This is for single object. The function 'img2xml' needs a parameter list like: (folder:str,filename:str,path:str,width:int,height:int,name:str, xmin:int,ymin:int,xmax:int,ymax:int)
For multiple objects, try processor_multiObj.py. The function 'img2xml_multiobj' needs a parameter list like: (tmpPath: str, aimPath: str, folder: str, filename: str, path: str, width: int, height: int, objs: list)
parameter 'tmpPath' can be same as parameter 'aimPath'. parameter 'objs' is a list like '[{'name':'xxx','difficult':0,'bndbox':{'xmin':??,...,'ymax':??}}]'