我应该如何处理,然后从这张图片中找到编号:
def process_img(screen):
global filename
ap = argparse.ArgumentParser()
ap.add_argument("-p", "--preprocess", type=str, default="thresh",
help="type of preprocessing to be done")
args = vars(ap.parse_args())
b = screen.copy()
resizedimg = cv2.resize(b, (750,500))
gamma = 0.3 # change the value here to get different result
adjusted = adjust_gamma(resizedimg, gamma=gamma)
ret, thresh = cv2.threshold(adjusted, 127, 255, cv2.THRESH_BINARY)
kernel = np.ones((3, 3), np.uint8)
img = cv2.erode(thresh, kernel, iterations=1)
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
if args["preprocess"] == "thresh":
img_gray = cv2.threshold(img_gray, 0, 255,
cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]
elif args["preprocess"] == "blur":
img_gray = cv2.medianBlur(img_gray, 3)
blurred = cv2.GaussianBlur(img_gray, (5, 5), 0)
edged = cv2.Canny(blurred, 50, 200, 255)
filename = "{}.png".format(os.getpid())
cv2.imwrite(filename, blurred)
return blurred
text = pytesseract.image_to_string(Image.open(filename), lang='eng', config='--psm 13 --oem 3 -c '
'tessedit_char_whitelist=0123456789')
但是,即使在我尝试调整设置并使之如此设置时,也只有大多数情况下这是行不通的,从而仅使文本边缘稍微模糊/平滑。不过,我无法对此进行很多改进,如果有人提出建议,将不胜感激。