[人工智能]证件照人像与背景分离（Python&cv）

代码：

import cv2
import numpy as np
#标记特定颜色区域
def Mark_Color(img, flag_color):
    #自定义
    if flag_color ==0:
        lower = np.array([24, 43, 46], dtype="uint8")
        upper = np.array([43, 255, 255], dtype="uint8")
    #黑色
    elif flag_color ==1:
        lower = np.array([0, 0, 0], dtype="uint8")
        upper = np.array([180, 255, 46], dtype="uint8")
    # 灰色
    elif flag_color == 2:
        lower = np.array([0, 0, 46], dtype="uint8")
        upper = np.array([180, 43, 220], dtype="uint8")
    # 白色
    elif flag_color == 3:
        lower = np.array([0, 0, 221], dtype="uint8")
        upper = np.array([180, 30, 255], dtype="uint8")
    # 红色
    elif flag_color == 4:
        lower = np.array([156, 43, 46], dtype="uint8")
        upper = np.array([180, 255, 255], dtype="uint8")
    # 红色2
    elif flag_color == 5:
        lower = np.array([0, 43, 46], dtype="uint8")
        upper = np.array([10, 255, 255], dtype="uint8")
    # 橙色
    elif flag_color == 6:
        lower = np.array([11, 43, 46], dtype="uint8")
        upper = np.array([25, 255, 255], dtype="uint8")
    # 黄色
    elif flag_color == 7:
        lower = np.array([26, 43, 46], dtype="uint8")
        upper = np.array([34, 255, 255], dtype="uint8")
    # 绿色
    elif flag_color == 8:
        lower = np.array([35, 43, 46], dtype="uint8")
        upper = np.array([77, 255, 255], dtype="uint8")
    # 青色
    elif flag_color == 9:
        lower = np.array([78, 43, 46], dtype="uint8")
        upper = np.array([99, 255, 255], dtype="uint8")
    # 蓝色
    elif flag_color == 10:
        lower = np.array([100, 43, 46], dtype="uint8")
        upper = np.array([124, 255, 255], dtype="uint8")
    # 紫色
    else:
        lower = np.array([125, 43, 46], dtype="uint8")
        upper = np.array([155, 255, 255], dtype="uint8")

    converted = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
    markingMask = cv2.inRange(converted, lower, upper)

    return markingMask
    # markingMask = cv2.GaussianBlur(markingMask, (5, 5), 0)
    # marked_img = cv2.bitwise_and(img, img, mask=markingMask)
    # return marked_img
# Read image
# im_in = cv2.imread("2inch_blue_1.jpg", cv2.IMREAD_GRAYSCALE);
img_path = '2inch_blue_1.jpg'

img = cv2.imread(img_path)

# 分离背景（背景为白色，人物为黑色）
im_in = Mark_Color(img, 10)


# Threshold.
# Set values equal to or above 220 to 0.
# Set values below 220 to 255.
th, im_th = cv2.threshold(im_in, 220, 255, cv2.THRESH_BINARY_INV);

# Copy the thresholded image.
im_floodfill = im_th.copy()

# Mask used to flood filling.
# Notice the size needs to be 2 pixels than the image.
h, w = im_th.shape[:2]
mask = np.zeros((h + 2, w + 2), np.uint8)

# Floodfill from point (0, 0)
cv2.floodFill(im_floodfill, mask, (0, 0), 255);

# Invert floodfilled image
im_floodfill_inv = cv2.bitwise_not(im_floodfill)

# Combine the two images to get the foreground.
im_out = im_th | im_floodfill_inv

# Display images.
cv2.imshow("Thresholded Image", im_th)
cv2.imshow("Floodfilled Image", im_floodfill)
cv2.imshow("Inverted Floodfilled Image", im_floodfill_inv)
cv2.imshow("Foreground", im_out)
cv2.waitKey(0)

效果：
按照Display依次为：

然后，可以继续设计有趣的应用。