Create demo.py
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import sys
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reload(sys)
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sys.setdefaultencoding("utf-8")
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from PIL import ImageFont
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from PIL import Image
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from PIL import ImageDraw
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fontC = ImageFont.truetype("./Font/platech.ttf", 14, 0)
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import time
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def SpeedTest(image_path):
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grr = cv2.imread(image_path)
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model = pr.LPR("model/cascade.xml", "model/model12.h5", "model/ocr_plate_all_gru.h5")
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model.SimpleRecognizePlateByE2E(grr)
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t0 = time.time()
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for x in range(20):
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model.SimpleRecognizePlateByE2E(grr)
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t = (time.time() - t0)/20.0
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print "Image size :" + str(grr.shape[1])+"x"+str(grr.shape[0]) + " need " + str(round(t*1000,2))+"ms"
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def drawRectBox(image,rect,addText):
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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)
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cv2.rectangle(image, (int(rect[0]-1), int(rect[1])-16), (int(rect[0] + 115), int(rect[1])), (0, 0, 255), -1,
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cv2.LINE_AA)
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img = Image.fromarray(image)
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draw = ImageDraw.Draw(img)
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draw.text((int(rect[0]+1), int(rect[1]-16)), addText.decode("utf-8"), (255, 255, 255), font=fontC)
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imagex = np.array(img)
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return imagex
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import HyperLPRLite as pr
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import cv2
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import numpy as np
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grr = cv2.imread("images_rec/2_.jpg")
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model = pr.LPR("model/cascade.xml","model/model12.h5","model/ocr_plate_all_gru.h5")
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for pstr,confidence,rect in model.SimpleRecognizePlateByE2E(grr):
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if confidence>0.7:
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image = drawRectBox(grr, rect, pstr+" "+str(round(confidence,3)))
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print "plate_str:"
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print pstr
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print "plate_confidence"
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print confidence
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cv2.imshow("image",image)
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cv2.waitKey(0)
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SpeedTest("images_rec/2_.jpg")
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