如何添加运动模糊到numpy数组

Question

我有一个numpy数组来自image

那么，是否有一个好的方法来做到这一点: from PIL import Image a = Image.open('img') a = a.filter(MOTION_BLUR)

Answer 1

import cv2
import numpy as np
img = cv2.imread('input.jpg')
cv2.imshow('Original', img)
size = 15
# generating the kernel
kernel_motion_blur = np.zeros((size, size))
kernel_motion_blur[int((size-1)/2), :] = np.ones(size)
kernel_motion_blur = kernel_motion_blur / size
# applying the kernel to the input image
output = cv2.filter2D(img, -1, kernel_motion_blur)
cv2.imshow('Motion Blur', output)
cv2.waitKey(0)

解释可以在这里找到

Answer 2

画一条旋转的线作为内核，然后对带有该内核的图像应用卷积滤波器

下面的代码使用了opencv框架。

import cv2
import numpy as np
#size - in pixels, size of motion blur
#angel - in degrees, direction of motion blur
def apply_motion_blur(image, size, angle):
    k = np.zeros((size, size), dtype=np.float32)
    k[ (size-1)// 2 , :] = np.ones(size, dtype=np.float32)
    k = cv2.warpAffine(k, cv2.getRotationMatrix2D( (size / 2 -0.5 , size / 2 -0.5 ) , angle, 1.0), (size, size) )  
    k = k * ( 1.0 / np.sum(k) )        
    return cv2.filter2D(image, -1, k) 

Answer 3

如果你想应用垂直，你可以使用这个内核:

kernel_motion_blur = np.zeros((size, size))
kernel_motion_blur[int(:, (size-1)/2)] = np.ones(size)
kernel_motion_blur = kernel_motion_blur / size

Answer 4

我将使用matplotlib:

from PIL import Image
img = Image.open('your_image')
imgplot = plt.imshow(img, interpolation="bicubic")