是否可以在 python 中的图像上创建随机形状？

Question

我需要在图像上创建一些斑点。这些斑点是不规则形状的（主要是我试图添加一个大圆圈，然后尝试在大圆圈的边缘添加较小的圆圈，使其成为“不规则”的圆形）。这里我只是在例子中展示了一个圆圈。 因为我有一个充满图像的目录，所以每个图像的大小、位置和点数都需要不同。这里给出了我尝试过的方法：

import glob
import cv2
import numpy as np
import random


count = 0
cv_img = []
for img in glob.glob('Lenna_(test_image).png'):
    n = cv2.imread(img)
    for i in range(random.randint(1, 5)):
        
        c1 = random.randrange(75,200,1)
        c2 = random.randrange(70,350,1)
        r1 = random.randint(8,18)
        
        n1_img = cv2.circle(n,(c1,c2),(r1),(255,255,255),-1, lineType = 4)
        
        
        cv_img.append(n1_img)
        cv2.imwrite('result.png',n1_img)
    count = count+1

This is the image I get

但我想补充一点。我是用油漆做的。 This is the thing I want to add on the image

Answer 1

这是在 Python/OpenCV/Numpy/Skimage 中生成随机形状的一种方法。

定义随机数生成器的种子值（以更改形状的模式）
定义输出宽度和高度
创建随机噪声图像
模糊噪声图像
将模糊图像拉伸到全动态范围
对拉伸图像设置阈值
应用形态学清理阈值图像
保存结果

import cv2
import skimage.exposure
import numpy as np
from numpy.random import default_rng

# define random seed to change the pattern
seedval = 55
rng = default_rng(seed=seedval)

# define image size
width=500
height=500

# create random noise image
noise = rng.integers(0, 255, (height,width), np.uint8, True)

# blur the noise image to control the size
blur = cv2.GaussianBlur(noise, (0,0), sigmaX=15, sigmaY=15, borderType = cv2.BORDER_DEFAULT)

# stretch the blurred image to full dynamic range
stretch = skimage.exposure.rescale_intensity(blur, in_range='image', out_range=(0,255)).astype(np.uint8)

# threshold stretched image to control the size
thresh = cv2.threshold(stretch, 175, 255, cv2.THRESH_BINARY)[1]

# apply morphology open and close to smooth out shapes
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (9,9))
result = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel)
result = cv2.morphologyEx(result, cv2.MORPH_CLOSE, kernel)

# save result
cv2.imwrite('random_blobs.png', result)

# show results
cv2.imshow('noise', noise)
cv2.imshow('blur', blur)
cv2.imshow('stretch', stretch)
cv2.imshow('thresh', thresh)
cv2.imshow('result', result)
cv2.waitKey(0)
cv2.destroyAllWindows()

结果：

您现在可以拍摄此图像并将其添加到背景图像中，以在背景上插入白色斑点。

Answer 2

这是将带有黑色边框的白色斑点添加到 Python/OpenCV 中的某些图像的完整代码。

输入：

import cv2
import skimage.exposure
import numpy as np
from numpy.random import default_rng

# read input image
img = cv2.imread('lena.jpg')
height, width = img.shape[:2]

# define random seed to change the pattern
seedval = 75
rng = default_rng(seed=seedval)

# create random noise image
noise = rng.integers(0, 255, (height,width), np.uint8, True)

# blur the noise image to control the size
blur = cv2.GaussianBlur(noise, (0,0), sigmaX=15, sigmaY=15, borderType = cv2.BORDER_DEFAULT)

# stretch the blurred image to full dynamic range
stretch = skimage.exposure.rescale_intensity(blur, in_range='image', out_range=(0,255)).astype(np.uint8)

# threshold stretched image to control the size
thresh = cv2.threshold(stretch, 175, 255, cv2.THRESH_BINARY)[1]

# apply morphology open and close to smooth out and make 3 channels
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (9,9))
mask = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel)
mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)
mask = cv2.merge([mask,mask,mask])

# add mask to input
result1 = cv2.add(img, mask)

# use canny edge detection on mask
edges = cv2.Canny(mask,50,255)

# thicken edges and make 3 channel
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3,3))
edges = cv2.morphologyEx(edges, cv2.MORPH_DILATE, kernel)
edges = cv2.merge([edges,edges,edges])

# merge edges with result1 (make black in result where edges are white)
result2 = result1.copy()
result2[np.where((edges == [255,255,255]).all(axis=2))] = [0,0,0]

# add noise to result where mask is white
noise = cv2.merge([noise,noise,noise])
result3 = result2.copy()
result3 = np.where(mask==(255,255,255), noise, result3)

# save result
cv2.imwrite('lena_random_blobs1.jpg', result1)
cv2.imwrite('lena_random_blobs2.jpg', result2)
cv2.imwrite('lena_random_blobs3.jpg', result3)

# show results
cv2.imshow('noise', noise)
cv2.imshow('blur', blur)
cv2.imshow('stretch', stretch)
cv2.imshow('thresh', thresh)
cv2.imshow('mask', mask)
cv2.imshow('edges', edges)
cv2.imshow('result1', result1)
cv2.imshow('result2', result2)
cv2.imshow('result3', result3)
cv2.waitKey(0)
cv2.destroyAllWindows()

结果 1（白色斑点）：

结果 2（带黑色边框的白色斑点）：

结果 3（带有黑色边框的噪声斑点）：

是否可以在 python 中的图像上创建随机形状？

Is it possible to create a random shape on an image in python?

python

opencv

random