python类MinFilter()的实例源码

def detect_gf_result(image_path):
    from PIL import ImageFilter, Image
    import pytesseract
    img = Image.open(image_path)
    for x in range(img.width):
        for y in range(img.height):
            if img.getpixel((x, y)) < (100, 100, 100):
                img.putpixel((x, y), (256, 256, 256))
    gray = img.convert('L')
    two = gray.point(lambda x: 0 if 68 < x < 90 else 256)
    min_res = two.filter(ImageFilter.MinFilter)
    med_res = min_res.filter(ImageFilter.MedianFilter)
    for _ in range(2):
        med_res = med_res.filter(ImageFilter.MedianFilter)
    res = pytesseract.image_to_string(med_res, config='-psm 6')
    return res.replace(' ', '')

def detect_gf_result(image_path):
    from PIL import ImageFilter, Image
    img = Image.open(image_path)
    if hasattr(img, "width"):
        width, height = img.width, img.height
    else:
        width, height = img.size
    for x in range(width):
        for y in range(height):
            if img.getpixel((x, y)) < (100, 100, 100):
                img.putpixel((x, y), (256, 256, 256))
    gray = img.convert('L')
    two = gray.point(lambda p: 0 if 68 < p < 90 else 256)
    min_res = two.filter(ImageFilter.MinFilter)
    med_res = min_res.filter(ImageFilter.MedianFilter)
    for _ in range(2):
        med_res = med_res.filter(ImageFilter.MedianFilter)
    return invoke_tesseract_to_recognize(med_res)

def minfilter_img(imdir,outdir):
    im = Image.open(imdir)
    out_filename = outdir
    out_img = im.filter(ImageFilter.MinFilter).save(out_filename, 'JPEG', quality=100)

def vcode(self):

        # ?????
        r = self._session.get('https://trade.gf.com.cn/yzm.jpgx')
        r.raise_for_status()

        # ?????????????
        img_buffer = BytesIO(r.content)
        img = Image.open(img_buffer)
        if hasattr(img, "width"):
            width, height = img.width, img.height
        else:
            width, height = img.size
        for x in range(width):
            for y in range(height):
                if img.getpixel((x, y)) < (100, 100, 100):
                    img.putpixel((x, y), (256, 256, 256))

        gray = img.convert('L')
        two = gray.point(lambda x: 0 if 68 < x < 90 else 256)
        min_res = two.filter(ImageFilter.MinFilter)
        med_res = min_res.filter(ImageFilter.MedianFilter)
        for _ in range(1):
            med_res = med_res.filter(ImageFilter.MedianFilter)

        # ??tesseract-ocr??????????
        vcode = pytesseract.image_to_string(med_res)
        img.close()
        img_buffer.close()

        vcode = vcode.replace(' ', '')
        if self.code_rule.findall(vcode) != []:
            logger.debug('vcode is: %s' % vcode)
            return vcode
        else:
            raise VerifyCodeError('verify code error: %s' % vcode)

def filter_footer(self, img):
        """Filter to remove the hight quality footer for an image."""
        # Some sites like MangaFox add an extra footer in the original
        # image.  This footer remove importan space in the Kindle, and
        # we need to remove it.
        #
        # The algorithm use as a leverage the normal noise present in
        # an scanned image, that is higher than the one in the footer.
        # This means that this filter will only work in medium quality
        # scanners, but possibly not in high quality ones.
        #
        # The process is like this:
        #
        #   1.- Binarize the image, moving the noise at the same level
        #       that the real information.
        #
        #   2.- Use a MinFilter of size 3 to a big mass of pixels that
        #       containg high frequency data.  That usually means
        #       pixels surrounded with blanks.
        #
        #   3.- Do a Gaussian filter to lower more the high frequency
        #       data, moving the mass close arround the pixel.  This
        #       will lower more the pixels surrounded with gaps.
        #
        #   4.- Discard the pixels with low mass.
        #
        _img = ImageOps.invert(img.convert(mode='L'))
        _img = _img.point(lambda x: x and 255)
        _img = _img.filter(ImageFilter.MinFilter(size=3))
        _img = _img.filter(ImageFilter.GaussianBlur(radius=5))
        _img = _img.point(lambda x: (x >= 48) and x)
        # If the image is white, we do not have bbox
        return img.crop(_img.getbbox()) if _img.getbbox() else img