Clever Geek Handbook

世界和AI数据挑战：盲文识别入门

人工智能和数据分析技术正越来越迅速地进入我们的生活；它们可以为解决以前从未实施过的人们真正重要的社会问题提供另一个机会。为此，ASI数字开发中心组织了“世界AI和数据挑战赛”，目的是构建寻找社会问题及其解决方案的过程。2020年2月，ASI数字开发中心的团队邀请我参加了比赛的专家。在这篇文章中，我将向您介绍一下比赛本身，以及如何开始解决比赛中一项有趣的任务-盲文识别。您可以参加2020年8月31日之前解决竞赛的这一任务和其他任务。





关于比赛



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im = cv2.imread('../data/Photo_Turlom_C1_2.jpeg')
im = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)




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im = cv2.blur(im,(3,3))
im = cv2.adaptiveThreshold(im, 255, cv2.ADAPTIVE_THRESH_MEAN_C,
                           cv2.THRESH_BINARY_INV, 5, 4)
im = cv2.medianBlur(im, 3)
_,im = cv2.threshold(im, 0, 255, cv2.THRESH_OTSU)
im = cv2.GaussianBlur(im, (3,3), 0)
_,im = cv2.threshold(im, 0, 255, cv2.THRESH_OTSU)
plt.imshow(im)


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orb = cv2.ORB_create(5000)
f,d = orb.detectAndCompute(im,None)


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def plot_dots(im,dots):
    img = np.zeros_like(im)
    for x in dots:
        cv2.circle(img,(int(x[0]),int(x[1])),1,(255,0,0))
    plt.imshow(img)

pts = [x.pt for x in f]
plot_dots(cim,pts)






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min_x, min_y, max_x, max_y = \
   [int(f([z[i] for z in pts])) 
       for f in (min,max) for i in (0,1)]


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off = 5
src_pts = np.array([(min_x-off,min_y-off),(min_x-off,max_y+off),
                    (max_x+off,min_y-off),(max_x+off,max_y+off)])
dim = 500
dst_pts = np.array([(0,0),(0,dim),(dim,0),(dim,dim)])
h,m = cv2.findHomography(src_pts,dst_pts)
trim = cv2.warpPerspective(cim,h,(dim,dim))
plt.imshow(trim)




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char_h = 32
char_w = 22
def slice(img):
    dy,dx = img.shape
    y = 0
    while y+char_h<dy:
        x=0
        while x+char_w<dx:
            #    x
            while np.max(img[y:y+char_h,x])!=0:
                x+=1
            while np.max(img[y:y+char_h,x+char_w])!=0:
                x-=1
            #    
            if np.max(img[y:y+char_h,x:x+char_w])>0:
                yield img[y:y+char_h,x:x+char_w]
            x+=char_w
        y+=char_h

sliced = list(slice(trim))


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