Repository for OpenCV's extra modules
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#!/usr/bin/python
import sys
import os
import cv2
import numpy as np
from matplotlib import pyplot as plt
print '\ndetect_er_chars.py'
print ' A simple demo script using the Extremal Region Filter algorithm described in:'
print ' Neumann L., Matas J.: Real-Time Scene Text Localization and Recognition, CVPR 2012\n'
if (len(sys.argv) < 2):
print ' (ERROR) You must call this script with an argument (path_to_image_to_be_processed)\n'
quit()
pathname = os.path.dirname(sys.argv[0])
img = cv2.imread(str(sys.argv[1]))
gray = cv2.imread(str(sys.argv[1]),0)
erc1 = cv2.text.loadClassifierNM1(pathname+'/trained_classifierNM1.xml')
er1 = cv2.text.createERFilterNM1(erc1)
erc2 = cv2.text.loadClassifierNM2(pathname+'/trained_classifierNM2.xml')
er2 = cv2.text.createERFilterNM2(erc2)
regions = cv2.text.detectRegions(gray,er1,er2)
#Visualization
rects = [cv2.boundingRect(p.reshape(-1, 1, 2)) for p in regions]
for rect in rects:
cv2.rectangle(img, rect[0:2], (rect[0]+rect[2],rect[1]+rect[3]), (0, 0, 255), 2)
img = img[:,:,::-1] #flip the colors dimension from BGR to RGB
plt.imshow(img)
plt.xticks([]), plt.yticks([]) # to hide tick values on X and Y axis
plt.show()