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import argparse
def get_args():
parser = argparse.ArgumentParser(description='Process some integers.')
parser.add_argument('--model_dir', type = str,
help =' the directory of the model,default using the Bird_D model included',
default='')
parser.add_argument('--det_model', type = str,
help ='you can select from yolo5,fasterrcnn, retinanetknn, retinanet, megadetector and yolonas',
default='retinanet')
parser.add_argument('--det_conf', type = float, default=0.1,
help ='Confidence threshold of your detection model')
parser.add_argument('--cla_model', type = str,
help ='you can select from res18 and mixmatch',
default='')
parser.add_argument('--image_root',type = str,
help = 'The root dir where image are stores')
parser.add_argument('--csv_root',type = str, default='',
help = 'The root dir where image info are stores')
parser.add_argument('--image_ext',type = str, default = 'JPG',
help = 'the extension of the image(without dot), default is JPG')
parser.add_argument('--image_altitude',type = int, default = 90,
help = 'the altitude of the taken image, default is set to be 90')
parser.add_argument('--image_location',type = str, default = 'No_Where',
help = 'the location of the taken image, default is set to be 90')
parser.add_argument('--image_date',type = str, default = '2022-10-26',
help = 'the date of the taken image, default is set to be 2022-10-26')
parser.add_argument('--use_altitude',type = bool, default = True,
help = 'whether to use altitude to scale the image, default is True')
parser.add_argument('--out_dir',type = str,
help = 'where the output will be generated,default is ./results',
default = './results')
parser.add_argument('--visualize',type = bool,
help = 'whether to have visualization stored to result, default is True',
default = False)
parser.add_argument('--evaluate',type = bool,
help = 'whether to evaluate the reslt,default is False',
default = False)
args = parser.parse_args()
#if the image_root input is with extension(*.JPG) wrap into list
#else fetch the list of image
return args
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