opencv 眼部模糊

# 眼部打碼

import numpy as np
import cv2

# 打碼
def anonymize_face_pixelate(image, blocks=3):
    # 將輸入圖像劃分爲NxN個塊
    (h, w) = image.shape[:2]
    xSteps = np.linspace(0, w, blocks + 1, dtype="int")
    ySteps = np.linspace(0, h, blocks + 1, dtype="int")
    # 在x和y方向上循環遍歷塊
    for i in range(1, len(ySteps)):
        for j in range(1, len(xSteps)):
            # 計算開始和結束（x，y）座標
            # 當前塊
            startX = xSteps[j - 1]
            startY = ySteps[i - 1]
            endX = xSteps[j]
            endY = ySteps[i]
            # 使用NumPy數組切片提取ROI，計算
            # ROI的均值，然後用
            # 表示原始圖像中ROI上的RGB值
            roi = image[startY:endY, startX:endX]
            (B, G, R) = [int(x) for x in cv2.mean(roi)[:3]]
            cv2.rectangle(image, (startX, startY), (endX, endY),
                (B, G, R), -1)
    # 返回像素化的模糊圖像
    return image

# opencv 下載
eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')

# 讀取打碼圖片
img = cv2.imread('demo/demo.jpg')

# 獲取眼部
eyes = eye_cascade.detectMultiScale(img)
for (ex,ey,ew,eh) in eyes:
    eye_img = img[ey:ey+eh, ex:ex+ew]
    eye_img = anonymize_face_pixelate(eye_img, blocks=10)
    img[ey:ey+eh, ex:ex+ew] = eye_img
    
cv2.imshow('img',img)
cv2.waitKey(0)