Pinch/bulge 使用 Python OpenCV 的失真

Question

我想使用 Python OpenCV 在图像上应用 pinch/bulge 过滤器。结果应该是这样的例子：

https://pixijs.io/pixi-filters/tools/screenshots/dist/bulge-pinch.gif

我阅读了以下 Whosebug post 应该是过滤器的正确公式：Formulas for Barrel/Pincushion distortion

但我正在努力在 Python OpenCV 中实现它。

我读过有关在图像上应用滤镜的地图：Distortion eﬀect using OpenCv-python

据我了解，代码可能如下所示：

import numpy as np
import cv2 as cv

f_img = 'example.jpg'
im_cv = cv.imread(f_img)

# grab the dimensions of the image
(h, w, _) = im_cv.shape

# set up the x and y maps as float32
flex_x = np.zeros((h, w), np.float32)
flex_y = np.zeros((h, w), np.float32)

# create map with the barrel pincushion distortion formula
for y in range(h):
    for x in range(w):
        flex_x[y, x] = APPLY FORMULA TO X
        flex_y[y, x] = APPLY FORMULA TO Y

# do the remap  this is where the magic happens
dst = cv.remap(im_cv, flex_x, flex_y, cv.INTER_LINEAR)

cv.imshow('src', im_cv)
cv.imshow('dst', dst)

cv.waitKey(0)
cv.destroyAllWindows()

这是实现示例图像中呈现的失真的正确方法吗？非常感谢任何有关有用资源或示例的帮助。

Answer 1

您可以使用 Python Wand 中的内爆和爆炸选项来做到这一点，它使用 ImageMagick。

输入：

from wand.image import Image
import numpy as np
import cv2

with Image(filename='zelda1.jpg') as img:
    img.virtual_pixel = 'black'
    img.implode(0.5)
    img.save(filename='zelda1_implode.jpg')
    # convert to opencv/numpy array format
    img_implode_opencv = np.array(img)
    img_implode_opencv = cv2.cvtColor(img_implode_opencv, cv2.COLOR_RGB2BGR)

with Image(filename='zelda1.jpg') as img:
    img.virtual_pixel = 'black'
    img.implode(-0.5 )
    img.save(filename='zelda1_explode.jpg')
    # convert to opencv/numpy array format
    img_explode_opencv = np.array(img)
    img_explode_opencv = cv2.cvtColor(img_explode_opencv, cv2.COLOR_RGB2BGR)

# display result with opencv
cv2.imshow("IMPLODE", img_implode_opencv)
cv2.imshow("EXPLODE", img_explode_opencv)
cv2.waitKey(0)

内爆：

爆炸：

Answer 2

在熟悉 ImageMagick 源代码后，我找到了一种应用失真公式的方法。在函数的帮助下，这是一种扭曲图像的方法：

import numpy as np
import cv2 as cv

f_img = 'example.jpg'
im_cv = cv.imread(f_img)

# grab the dimensions of the image
(h, w, _) = im_cv.shape

# set up the x and y maps as float32
flex_x = np.zeros((h, w), np.float32)
flex_y = np.zeros((h, w), np.float32)

# create map with the barrel pincushion distortion formula
for y in range(h):
    delta_y = scale_y * (y - center_y)
    for x in range(w):
        # determine if pixel is within an ellipse
        delta_x = scale_x * (x - center_x)
        distance = delta_x * delta_x + delta_y * delta_y
        if distance >= (radius * radius):
            flex_x[y, x] = x
            flex_y[y, x] = y
        else:
            factor = 1.0
            if distance > 0.0:
                factor = math.pow(math.sin(math.pi * math.sqrt(distance) / radius / 2), -amount)
            flex_x[y, x] = factor * delta_x / scale_x + center_x
            flex_y[y, x] = factor * delta_y / scale_y + center_y

# do the remap  this is where the magic happens
dst = cv.remap(im_cv, flex_x, flex_y, cv.INTER_LINEAR)

cv.imshow('src', im_cv)
cv.imshow('dst', dst)

cv.waitKey(0)
cv.destroyAllWindows()

这与使用 ImageMagick 中的 convert -implode 函数具有相同的效果。

Pinch/bulge 使用 Python OpenCV 的失真

Pinch/bulge distortion using Python OpenCV

python

opencv

image-processing

filter

distortion