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main.py
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56 lines (52 loc) · 2.1 KB
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from Detect_cmnd.model_center import CENTER_MODEL
import glob
import cv2
import os
from Detect_fields.detect import Detector_fields
from ocr import OCR
import time
class CMND(object):
def __init__(self):
self.Detect_cmnd=CENTER_MODEL(weight_path="Detect_cmnd/weights/model_cmnd_best.pth")
self.Detect_fields=Detector_fields()
self.ocr=OCR()
self.fields=['id','name','date','ad1','ad2']
def predict(self,img):
restext={}
t1=time.time()
font = cv2.FONT_HERSHEY_SIMPLEX
img_aligned= self.Detect_cmnd.detect(img)
print("centernet ",time.time()-t1)
t1=time.time()
if(img_aligned is not None):
img_aligned=cv2.resize(img_aligned,(800,650))
res,resimg=self.Detect_fields.detect(img_aligned,0.3)
print("yolo ",time.time()-t1)
t1=time.time()
for x in self.fields:
restext[x]=self.ocr.predict(resimg[x],res[x],x)
if(restext[x] is None ): restext[x]=""
print("ocr ",time.time()-t1)
# if(cl=="id"):
# text=(self.id.recognize(im))
# # if(cl=="name"):
# else:
# text=self.str.recognize(im)
# img_aligned=cv2.putText(img_aligned,text,(box[0],box[1]),font,1,(255,0,0),1,cv2.LINE_AA)
#for box in res[x]:
#print("a")
#img_aligned=cv2.rectangle(img_aligned,(box[0],box[1]),(box[2],box[3]),(255,0,0),2,1)
else :
img_aligned = cv2.resize(img,(750,600))
res,resimg=self.Detect_fields.detect(img_aligned,0.3)
for x in self.fields:
restext[x]=self.ocr.predict(resimg[x],res[x],x)
#for box in res[x]:
#img_aligned=cv2.rectangle(img_aligned,(box[0],box[1]),(box[2],box[3]),(255,0,0),2,1)
restext['name']=restext['name'].upper()
return img_aligned,restext
if __name__=="__main__":
X=CMND()
img=cv2.imread("image/331.jpg")
cv2.imshow("image",X.prepare(img))
cv2.waitKey(0)