问如何使用OpenCV检测文本

EN

import cv2
import numpy as np

# load image
img = cv2.imread("rock.jpg")

# convert to gray
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# threshold image
thresh = cv2.threshold(gray, 150, 255, cv2.THRESH_BINARY)[1]

# apply morphology to clean up small white or black regions
kernel = np.ones((5,5), np.uint8)
morph = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel)
morph = cv2.morphologyEx(morph, cv2.MORPH_OPEN, kernel)

# thin region to remove excess black border
kernel = np.ones((3,3), np.uint8)
morph = cv2.morphologyEx(morph, cv2.MORPH_ERODE, kernel)

# find contours
cntrs = cv2.findContours(morph, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cntrs = cntrs[0] if len(cntrs) == 2 else cntrs[1]

# Contour filtering -- keep largest, vertically oriented object (h/w > 1)
area_thresh = 0
for c in cntrs:
    area = cv2.contourArea(c)
    x,y,w,h = cv2.boundingRect(c)
    aspect = h / w
    if area > area_thresh and aspect > 1:
        big_contour = c
        area_thresh = area

# extract region of text contour from image
x,y,w,h = cv2.boundingRect(big_contour)
text = img[y:y+h, x:x+w]

# extract region from thresholded image
binary_text = thresh[y:y+h, x:x+w]  

# write result to disk
cv2.imwrite("rock_thresh.jpg", thresh)
cv2.imwrite("rock_morph.jpg", morph)
cv2.imwrite("rock_text.jpg", text)
cv2.imwrite("rock_binary_text.jpg", binary_text)

cv2.imshow("THRESH", thresh)
cv2.imshow("MORPH", morph)
cv2.imshow("TEXT", text)
cv2.imshow("BINARY TEXT", binary_text)
cv2.waitKey(0)
cv2.destroyAllWindows()