56 lines
1.4 KiB
Python
56 lines
1.4 KiB
Python
import cv2 as cv
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from PIL import Image
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import pytesseract as tess
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def recoginse_text(image):
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"""
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步骤：
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1、灰度，二值化处理
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2、形态学操作去噪
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3、识别
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:param image:
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:return:
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"""
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# 灰度 二值化
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gray = cv.cvtColor(image,cv.COLOR_BGR2GRAY)
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# 如果是白底黑字 建议 _INV
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ret,binary = cv.threshold(gray,0,255,cv.THRESH_BINARY_INV| cv.THRESH_OTSU)
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# 形态学操作 (根据需要设置参数（1，2）)
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kernel = cv.getStructuringElement(cv.MORPH_RECT,(1,2)) #去除横向细线
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morph1 = cv.morphologyEx(binary,cv.MORPH_OPEN,kernel)
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kernel = cv.getStructuringElement(cv.MORPH_RECT, (2, 1)) #去除纵向细线
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morph2 = cv.morphologyEx(morph1,cv.MORPH_OPEN,kernel)
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cv.imshow("Morph",morph2)
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# 黑底白字取非，变为白底黑字（便于pytesseract 识别）
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cv.bitwise_not(morph2,morph2)
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textImage = Image.fromarray(morph2)
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# 图片转文字
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text=tess.image_to_string(textImage)
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n=10 #根据不同国家车牌固定数目进行设置
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print("识别结果:")
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print(text[1:n])
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def main():
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# 读取需要识别的数字字母图片，并显示读到的原图
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src = cv.imread("cp.jpg")
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cv.imshow("src",src)
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# 识别
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recoginse_text(src)
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cv.waitKey(0)
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cv.destroyAllWindows()
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if __name__=="__main__":
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main()
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