我想使用 Python OpenCV 在图像上应用收缩/凸出滤镜。结果应该是这个例子的某种形式:
https://pixijs.io/pixi-filters/tools/screenshots/dist/bulge-pinch.gif
我已阅读以下 stackoverflow 帖子,它应该是滤波器的正确公式:桶形/枕形失真的公式
但我正在努力在 Python OpenCV 中实现这一点。
我读过有关在图像上应用滤镜的地图:使用 OpenCv-python 的扭曲效果
根据我的理解,代码可能看起来像这样:
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?非常感谢有关有用资源或最好的示例的任何帮助。
熟悉 ImageMagick 源代码后,我找到了一种应用失真公式的方法。借助 OpenCV remap 函数,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。
您可以使用 Python Wand 中的内爆和爆炸选项来做到这一点,Python Wand 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:
对于那些寻找纯Python和带有矢量化的凸出效果优化版本的人。在这里。
我使用
numpy
重新实现了通过向量/矩阵运算生成映射矩阵的部分,并将它们包装在一个方便的 BulgeEffect
类中。我还提供了一个演示程序以供快速测试。
该效果的关键部分是用于计算效果圆内像素位移的数学函数。不知何故,我无法让 @Davi Jones 在他的答案中使用的公式起作用。因此,我使用自己的略有不同的函数:
scale * sin(pi * x) ^ amount
。您更改此表达式即可获得不同的失真效果。
代码可能设计得不好,而且我不是Pythonic(其中某些部分可能有更多Pythonic版本。)。因此,它有待改进。
要应用效果,您必须创建
BulgeEffect
类的实例,将图像设置为 image 属性,设置选项(中心、效果半径、扭曲量等),调用 apply 方法,然后获取从图像属性返回的结果。
我不喜欢这个工作流程。这对我来说很丑,但我最终无法得到一个更优雅的版本。
演示中的示例:
bulge_effect.image = img_copy
bulge_effect.set_options(BulgeOptions(x, y, 100, quality=BulgeQuality.LOW))
bulge_effect.apply()
img_copy = bulge_effect.image
要使图像内爆,您可以给出正的比例值。默认比例值为
-0.45
。
有 4 种质量模式完全映射到 opencv 的插值模式。
import cv2
import numpy as np
from enum import IntEnum
class BulgeQuality(IntEnum):
LOW = 0
NORMAL = 1
HIGH = 2
HIGHEST = 3
class BulgeOptions:
def __init__(self, x, y, radius, scale=-0.45, amount=4, quality=BulgeQuality.NORMAL) -> None:
self.center = np.array([x, y], np.float32)
self.radius = radius
self.scale = scale
self.amount = amount
self.quality = quality
class BulgeEffect:
INTERP_TYPES = [cv2.INTER_NEAREST, cv2.INTER_LINEAR, cv2.INTER_CUBIC, cv2.INTER_LANCZOS4]
def __init__(self, img, options=None):
self._map_x = None
self._map_y = None
self._img = img
self._create_map()
if options is None:
options = BulgeOptions(img.shape[1] // 2, img.shape[0] // 2, 50)
self._options = options
self._build_map()
@property
def amount(self):
return self._options.amount
@property
def center(self):
return self._options.center
@property
def image(self):
return self._img
@property
def quality(self):
return self._options.quality
@property
def radius(self):
return self._options.radius
@property
def scale(self):
return self._options.scale
@image.setter
def image(self, image, image_changed=False):
self._img = image
if image_changed:
self._create_map()
def set_options(self, options):
self._options = options
self._create_map()
self._build_map()
def apply(self):
self._img = cv2.remap(self._img, self._map_x, self._map_y, self._get_interp_from_quality(self.quality))
def _create_map(self):
W = self._img.shape[1]
H = self._img.shape[0]
self._map_y, self._map_x = np.mgrid[:H, :W].astype(np.float32)
def _build_map(self):
dv_x = self._map_x - self._options.center[0]
dv_y = self._map_y - self._options.center[1]
circle_distances = np.sqrt(dv_x ** 2 + dv_y ** 2)
circle_indices = circle_distances <= self._options.radius
t = circle_distances / self._options.radius
s = -0.45 * (np.sin(np.pi * t)) ** 4
self._map_x[circle_indices] = self._map_x[circle_indices] + np.multiply(dv_x[circle_indices], s[circle_indices])
self._map_y[circle_indices] = self._map_y[circle_indices] + np.multiply(dv_y[circle_indices], s[circle_indices])
def _get_interp_from_quality(self, quality):
return BulgeEffect.INTERP_TYPES[quality]
img = None
img_copy = None
bulge_effect = None
def on_mouse_move(x, y, button):
global img_copy
if img is None:
return
np.copyto(img_copy, img)
bulge_effect.image = img_copy
bulge_effect.set_options(BulgeOptions(x, y, 100, quality=BulgeQuality.LOW))
bulge_effect.apply()
img_copy = bulge_effect.image
cv2.imshow("buldge", img_copy)
def get_button(flags):
if flags & cv2.EVENT_FLAG_LBUTTON:
return 'left'
if flags & cv2.EVENT_FLAG_RBUTTON:
return 'right'
if flags & cv2.EVENT_FLAG_MBUTTON:
return 'middle'
return 'none'
def mouse_event_handler(event, x, y, flags, param):
button_down = [cv2.EVENT_LBUTTONDOWN, cv2.EVENT_RBUTTONDOWN, cv2.EVENT_MBUTTONDOWN]
button_up = [cv2.EVENT_LBUTTONUP, cv2.EVENT_RBUTTONUP, cv2.EVENT_MBUTTONUP]
button = get_button(flags)
if event == cv2.EVENT_MOUSEMOVE:
on_mouse_move(x, y, button)
if __name__ == "__main__":
img = cv2.imread('test2.png')
img_copy = img.copy()
bulge_effect = BulgeEffect(img_copy)
cv2.imshow('buldge', img_copy)
cv2.setMouseCallback('buldge', mouse_event_handler)
cv2.waitKey(0)