run.py

from glob import glob
import cv2
import argparse

parser = argparse.ArgumentParser()

parser.add_argument('--gpu',dest = "gpu" ,type=int, default = -1,
                    help='enter the number of gpu')



parser.add_argument('--image_out',dest = "out" , default = "out.jpg",
                    help='enter the path to the output')

args = parser.parse_args()
files = glob("Images/normal/*")
from Inference import Infer

Inference_class = Infer(detect_thresh = 0.5,gpu=args.gpu)
for n,i in enumerate(files) :
    i = cv2.imread(i)
    bboxes,classes,scores = Inference_class.infer(image_path=i,out="out/Classification/"+str(n)+".jpg")

    for s,b in enumerate(bboxes):
        y,x,y2,x2 = b
        cv2.putText(l, classes[s], (int(x), int(y)), cv2.FONT_HERSHEY_SIMPLEX,
                   1, (0,0,255), 2, cv2.LINE_AA)
        cv2.rectangle(l,(int(x),int(y)),(int(x2),int(y2)),(0,255,0),2)

    cv2.write("out/Classification/"+str(n)+".jpg",i)