from pil import image
from pil import imageenhance
import pytesseract
img = image.open('sanyecao.jpg')
img = img.convert('rgb') #這裡也可以嘗試使用l
enhancer = imageenhance.color(img)
enhancer = enhancer.enhance(0)
enhancer = imageenhance.brightness(enhancer)
enhancer = enhancer.enhance(2)
enhancer = imageenhance.contrast(enhancer)
enhancer = enhancer.enhance(8)
enhancer = imageenhance.sharpness(enhancer)
img = enhancer.enhance(20)
text=pytesseract.image_to_string(img)
這個情況有很多種,也不說了,可以自己去嘗試,簡單寫個調整亮度
#調整亮度
filename = "sanyecao.jpg"
img = cv2.imread(filename, 0)
print(np.shape(img))
kernel = np.ones((1,1), np.uint8)
dilate = cv2.dilate(img, kernel, iterations=1)
cv2.imwrite('new_dilate.jpg', dilate)
#還有些常用的方法
cv2.canny
cv2.erode
cv2.rectangle
original_img = cv2.imread("qingwen.png", 0)
# canny(): 邊緣檢測
img1 = cv2.gaussianblur(original_img,(3,3),0)
canny = cv2.canny(img1, 50, 150)
# 形態學：邊緣檢測
_,thr_img = cv2.threshold(original_img,210,255,cv2.thresh_binary)#設定紅色通道閾值210（閾值影響梯度運算效果）
kernel = cv2.getstructuringelement(cv2.morph_rect,(5,5)) #定義矩形結構元素
gradient = cv2.morphologyex(thr_img, cv2.morph_gradient, kernel) #梯度
cv2.imshow("original_img", original_img)
cv2.imshow("gradient", gradient)
cv2.imshow('canny', canny)