Question

我试图用MNIST作为数据集＆amp; amp;来预测手写数字。蟒蛇。现在，我必须将已裁剪的图像作为程序的输入。使用以下函数进行进一步处理以使其成为MNIST数据集格式，但如何自动裁剪作为输入的随机图像？

def imageprepare(argv):
    """
    This function returns the pixel values.
    The imput is a png file location.
    """
    im = Image.open(argv).convert('L')
    width = float(im.size[0])
    height = float(im.size[1])
    newImage = Image.new('L', (28, 28), (255)) #creates white canvas of 28x28 pixels

    if width > height: #check which dimension is bigger
        #Width is bigger. Width becomes 20 pixels.
        nheight = int(round((20.0/width*height),0)) #resize height according to ratio width
        if (nheigth == 0): #rare case but minimum is 1 pixel
            nheigth = 1  
        # resize and sharpen
        img = im.resize((20,nheight), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)
        wtop = int(round(((28 - nheight)/2),0)) #caculate horizontal pozition
        newImage.paste(img, (4, wtop)) #paste resized image on white canvas
    else:
        #Height is bigger. Heigth becomes 20 pixels. 
        nwidth = int(round((20.0/height*width),0)) #resize width according to ratio height
        if (nwidth == 0): #rare case but minimum is 1 pixel
            nwidth = 1
         # resize and sharpen
        img = im.resize((nwidth,20), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)
        wleft = int(round(((28 - nwidth)/2),0)) #caculate vertical pozition
        newImage.paste(img, (wleft, 4)) #paste resized image on white canvas

    #newImage.save("sample.png")

    tv = list(newImage.getdata()) #get pixel values

    #normalize pixels to 0 and 1. 0 is pure white, 1 is pure black.
    tva = [ (255-x)*1.0/255.0 for x in tv] 
    return tva

Answer 1

您可以使用OpenCV轮廓来定位实际图像中的潜在数字，其中一些技术将取决于您正在使用的实际数据。在http://www.pyimagesearch.com/2017/02/13/recognizing-digits-with-opencv-and-python/有一个数字候选位置示例这可以给你一些指示。

但是，您可能会遇到一些脚本的问题，因为我相信在所有欧洲脚本中，每个数字应该是连续且不同的，我不确定这两个点是否适用于所有脚本。

python - 裁剪手写数字的图像

1 个答案: