HyperLPR/demo.py

import sys
reload(sys)
sys.setdefaultencoding("utf-8")




import time

def SpeedTest(image_path):
    grr = cv2.imread(image_path)
    model = pr.LPR("model/cascade.xml", "model/model12.h5", "model/ocr_plate_all_gru.h5")
    model.SimpleRecognizePlateByE2E(grr)
    t0 = time.time()
    for x in range(20):
        model.SimpleRecognizePlateByE2E(grr)
    t = (time.time() - t0)/20.0
    print "Image size :" + str(grr.shape[1])+"x"+str(grr.shape[0]) +  " need " + str(round(t*1000,2))+"ms"

    

from PIL import ImageFont
from PIL import Image
from PIL import ImageDraw
fontC = ImageFont.truetype("./Font/platech.ttf", 14, 0)

def drawRectBox(image,rect,addText):
    cv2.rectangle(image, (int(rect[0]), int(rect[1])), (int(rect[0] + rect[2]), int(rect[1] + rect[3])), (0,0, 255), 2,cv2.LINE_AA)
    cv2.rectangle(image, (int(rect[0]-1), int(rect[1])-16), (int(rect[0] + 115), int(rect[1])), (0, 0, 255), -1,
                  cv2.LINE_AA)
    img = Image.fromarray(image)
    draw = ImageDraw.Draw(img)
    draw.text((int(rect[0]+1), int(rect[1]-16)), addText.decode("utf-8"), (255, 255, 255), font=fontC)
    imagex = np.array(img)
    return imagex





import HyperLPRLite as pr
import cv2
import numpy as np
grr = cv2.imread("images_rec/2_.jpg")
model = pr.LPR("model/cascade.xml","model/model12.h5","model/ocr_plate_all_gru.h5")
for pstr,confidence,rect in model.SimpleRecognizePlateByE2E(grr):
        if confidence>0.7:
            image = drawRectBox(grr, rect, pstr+" "+str(round(confidence,3)))
            print "plate_str:"
            print pstr
            print "plate_confidence"
            print confidence
            
cv2.imshow("image",image)
cv2.waitKey(0)



SpeedTest("images_rec/2_.jpg")