opencv_tutorials/python/code_112/opencv_112.py at master · HZHCoder1990/opencv_tutorials · GitHub

History

59 lines (51 loc) · 1.71 KB

Raw

import numpy as np

import cv2 as cv

image = cv.imread('toux.jpg')

cv.imshow("input", image)

h, w ,ch = image.shape

# 构建图像数据

data = image.reshape((-1,3))

data = np.float32(data)

# 图像分割

criteria = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_MAX_ITER, 10, 1.0)

num_clusters = 4

ret,label,center=cv.kmeans(data, num_clusters, None, criteria, num_clusters, cv.KMEANS_RANDOM_CENTERS)

# 生成mask区域

index = label[0][0]

center = np.uint8(center)

color = center[0]

mask = np.ones((h, w), dtype=np.uint8)*255.

label = np.reshape(label, (h, w))

# alpha图

mask[label == index] = 0

# 高斯模糊

se = cv.getStructuringElement(cv.MORPH_RECT, (3, 3))

# 膨胀，防止背景出现

cv.erode(mask, se, mask)

#边缘模糊

mask = cv.GaussianBlur(mask, (5, 5), 0)

cv.imshow('background-mask',mask)

# 白色背景

bg = np.ones(image.shape, dtype=np.float)*255.

# 粉丝背景

purle = np.array([255, 0, 255])

bg_color = np.tile(purle, (image.shape[0], image.shape[1], 1))

alpha = mask.astype(np.float32) / 255.

fg = alpha[..., None] * image

new_image = fg + (1 - alpha[..., None])*bg

new_image_purle = fg + (1 - alpha[..., None])*bg_color

# # blend image

# result = np.zeros((h, w, ch), dtype=np.uint8)

# for row in range(h):

# for col in range(w):

# w1 = mask[row, col] / 255.0

# b, g, r = image[row, col]

# b = w1 * 255.0 + b * (1.0 - w1)

# g = w1 * 0 + g * (1.0 - w1)

# r = w1 * 255 + r * (1.0 - w1)

# result[row, col] = (b, g, r)

cv.imshow("background substitution", bg_color.astype(np.uint8))

cv.imwrite("white.jpg", np.hstack((image, new_image.astype(np.uint8))))

cv.imwrite("purle.jpg", np.hstack((image, new_image_purle.astype(np.uint8))))

cv.waitKey(0)

cv.destroyAllWindows()

opencv_tutorials/python/code_112/opencv_112.py at master · HZHCoder1990/opencv_tutorials · GitHub

Expand file tree

Breadcrumbs

opencv_112.py

Latest commit

History

Breadcrumbs

opencv_112.py

File metadata and controls