項目一:OpenCVで銀行カード番号を識別する

import cv2

def sort_contours(cnts, method="left-to-right"):
    reverse = False
    i = 0

    if method == "right-to-left" or method == "bottom-to-top":
        reverse = True

    if method == "top-to-bottom" or method == "bottom-to-top":
        i = 1
    boundingBoxes = [cv2.boundingRect(c) for c in cnts] #        ，         x,y,h,w
    (cnts, boundingBoxes) = zip(*sorted(zip(cnts, boundingBoxes),
                                        key=lambda b: b[1][i], reverse=reverse))
    #          x         ，             ，      。

    return cnts, boundingBoxes
def resize(image, width=None, height=None, inter=cv2.INTER_AREA):
    dim = None
    (h, w) = image.shape[:2]
    if width is None and height is None:
        return image
    if width is None:
        r = height / float(h)
        dim = (int(w * r), height)
    else:
        r = width / float(w)
        dim = (width, int(h * r))
    resized = cv2.resize(image, dim, interpolation=inter)
    return resized

#      
from imutils import contours
import numpy as np
import argparse
import cv2
import myutils

#     
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required=True,
	help="path to input image")
ap.add_argument("-t", "--template", required=True,
	help="path to template OCR-A image")
args = vars(ap.parse_args())

#        
FIRST_NUMBER = {
	"3": "American Express",
	"4": "Visa",
	"5": "MasterCard",
	"6": "Discover Card"
}
#     
def cv_show(name,img):
	cv2.imshow(name, img)
	cv2.waitKey(0)
	cv2.destroyAllWindows()
#         
img = cv2.imread(args["template"])
cv_show('img',img)
#    
ref = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
cv_show('ref',ref)
#     
ref = cv2.threshold(ref, 10, 255, cv2.THRESH_BINARY_INV)[1]
cv_show('ref',ref)

#     
#cv2.findContours()           ，    （     ）,cv2.RETR_EXTERNAL      ，cv2.CHAIN_APPROX_SIMPLE       
#   list               

ref_, refCnts, hierarchy = cv2.findContours(ref.copy(), cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
#     ，          
cv2.drawContours(img,refCnts,-1,(0,0,255),3) #-1         
cv_show('img',img)
print (np.array(refCnts).shape)#  10 
refCnts = myutils.sort_contours(refCnts, method="left-to-right")[0] #  ，    ，    
#          ，0    0。
digits = {}

#        （10   ）
for (i, c) in enumerate(refCnts):
	#         resize     
	(x, y, w, h) = cv2.boundingRect(c)
	roi = ref[y:y + h, x:x + w]
	roi = cv2.resize(roi, (57, 88))

	#             
	digits[i] = roi
#   for     ，                      。      。

#       
rectKernel = cv2.getStructuringElement(cv2.MORPH_RECT, (9, 3))
sqKernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 5))

#      ，   
image = cv2.imread(args["image"])
cv_show('image',image)
image = myutils.resize(image, width=300)#resize         
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
cv_show('gray',gray)

#    ，        
tophat = cv2.morphologyEx(gray, cv2.MORPH_TOPHAT, rectKernel) 
cv_show('tophat',tophat) 
# Sobel    ，     x  ，  y      
gradX = cv2.Sobel(tophat, ddepth=cv2.CV_32F, dx=1, dy=0, #ksize=-1    3*3 
	ksize=-1)


gradX = np.absolute(gradX)
(minVal, maxVal) = (np.min(gradX), np.max(gradX))
gradX = (255 * ((gradX - minVal) / (maxVal - minVal)))
gradX = gradX.astype("uint8")

print (np.array(gradX).shape)
cv_show('gradX',gradX)

#     （   ，   ）       
gradX = cv2.morphologyEx(gradX, cv2.MORPH_CLOSE, rectKernel) 
cv_show('gradX',gradX)
#THRESH_OTSU          ，    ，         0
thresh = cv2.threshold(gradX, 0, 255,
	cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1] 
cv_show('thresh',thresh)

#       

thresh = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, sqKernel) #       
cv_show('thresh',thresh)

#     

thresh_, threshCnts, hierarchy = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
	cv2.CHAIN_APPROX_SIMPLE)

cnts = threshCnts
cur_img = image.copy()
cv2.drawContours(cur_img,cnts,-1,(0,0,255),3) 
cv_show('img',cur_img)
locs = []

#     （         locs ）
for (i, c) in enumerate(cnts):
	#     
	(x, y, w, h) = cv2.boundingRect(c)
	ar = w / float(h)

	#        ，       ，             
	if ar > 2.5 and ar < 4.0:

		if (w > 40 and w < 55) and (h > 10 and h < 20):
			#      
			locs.append((x, y, w, h))

#             
locs = sorted(locs, key=lambda x:x[0])
output = []

#            
for (i, (gX, gY, gW, gH)) in enumerate(locs):
	# initialize the list of group digits
	groupOutput = []

	#           
	group = gray[gY - 5:gY + gH + 5, gX - 5:gX + gW + 5]#            ，     
	cv_show('group',group)
	#    
	group = cv2.threshold(group, 0, 255,
		cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]#      ，     ，             ，    。
	cv_show('group',group)
	#         
	group_,digitCnts,hierarchy = cv2.findContours(group.copy(), cv2.RETR_EXTERNAL,
		cv2.CHAIN_APPROX_SIMPLE)
	digitCnts = contours.sort_contours(digitCnts,
		method="left-to-right")[0]

	#             
	for c in digitCnts:
		#          ，resize       
		(x, y, w, h) = cv2.boundingRect(c)
		roi = group[y:y + h, x:x + w]
		roi = cv2.resize(roi, (57, 88))#resize   ，       ，            
		cv_show('roi',roi)

		#       
		scores = []

		#            
		for (digit, digitROI) in digits.items():
			#     
			result = cv2.matchTemplate(roi, digitROI,
				cv2.TM_CCOEFF)
			(_, score, _, _) = cv2.minMaxLoc(result)
			scores.append(score)

		#         
		groupOutput.append(str(np.argmax(scores)))

	#    
	cv2.rectangle(image, (gX - 5, gY - 5),
		(gX + gW + 5, gY + gH + 5), (0, 0, 255), 1)
	cv2.putText(image, "".join(groupOutput), (gX, gY - 15),
		cv2.FONT_HERSHEY_SIMPLEX, 0.65, (0, 0, 255), 2)

	#     
	output.extend(groupOutput)

#     
print("Credit Card Type: {}".format(FIRST_NUMBER[output[0]]))
print("Credit Card #: {}".format("".join(output)))
cv2.imshow("Image", image)
cv2.waitKey(0)