Python-opencv学习第二十九课：高斯双边模糊
文章目录
一、学习部分
记录笔者学习Python-opencv学习第二十九课：高斯双边模糊，代码资料来源于网络贾老师视频。
二、代码部分
1.引入库
代码如下：
import cv2 as cv
import matplotlib.pyplot as plt
import numpy as np
2.读入数据
代码如下：
def bitfilter_demo():
#image=cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png",cv.IMREAD_GRAYSCALE)#灰度图
image = cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png") # 灰度图
cv.imshow("input",image)
#result=cv.GaussianBlur(image,(0,0),15)#高斯模糊API(模糊 可改参数)
result = cv.bilateralFilter(image,0,100,10,) # 高斯双边模糊API(模糊 可改参数)类似于磨皮PS
cv.imshow("result", result)
cv.waitKey(0)
cv.destroyAllWindows()
3.完整代码
代码如下：
import cv2 as cv
import matplotlib.pyplot as plt
import numpy as np
def read_demo_():
image = cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png") # BGR 0-255
cv.imshow("input", image)
cv.waitKey(0)
cv.destroyAllWindows()
def color_space_demo_():
image = cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png") # BGR 0-255
gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY) # 将bgr转换为gray
hsv = cv.cvtColor(image, cv.COLOR_BGR2HSV) # 将bgr转换为hsv
thsv = cv.cvtColor(image, cv.COLOR_HSV2BGR) # 将HSV转换为BGR
# cv.namedwindow("input",cv.WINDOW.AUTOSIZE)
cv.imshow("gray", gray) # 显示一个窗口名为gray的gray图像
cv.imshow("hsv", hsv) # 显示一个窗口名为hsv的hsv图像
cv.imshow("thsv", thsv) # 显示一个窗口名为thsv的thsv图像
cv.waitKey(0) # 相当于按键操作，当键盘触发时候，显示图片窗口关闭，否则不关闭
cv.destroyAllWindows()
def mat_demo_():
image = cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png") # BGR 0-255
h, w, c = image.shape # 打印图像的维度 H高度 W宽度 C通道数，色彩图片有三通道，灰色图片零通道
roi = image[100:200, 100:200, :] # 感兴趣局部区域像素分布 H高度100-200像素，W宽度100-200像素。灰度图像就没有最后一个冒号
blank = np.zeros((h, w, c), dtype=np.uint8) # 产生一个空白窗口，需要说明H,W,C以及字节数，这是区别于np.zeros_like()函数。
# blank[60:200, 60:280, :] = image[60:200, 60:280, :] # blank和image要一致才能匹配
# blank = np.copy(image)#使用copy函数直接进行复制，将blank上述注释掉
blank = image # 实现原图到blank的复制
cv.imshow("image", image) # 显示原图窗口
cv.imshow("blank", blank) # 显示blank空白窗口
cv.waitKey(0) # 相当于按键操作，当键盘触发时候，显示图片窗口关闭，否则不关闭
cv.destroyAllWindows()
def pixel_demo():
image = cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png") # BGR 0-255
cv.imshow("input", image)
h, w, c = image.shape # 打印图像维度
for row in range(h): # 行
for col in range(w): # 列
b, g, r = image[row, col] # 图像写像素
image[row, col] = (0, g, r) # 取反操作，可对其进行更改
cv.imshow("result", image) # 显示取反后的图片
cv.imwrite("C:/Users/akaak/Pictures/OpenCV/csdn/4/savedexample.png", image) # 保存数据图
cv.waitKey(0) # 设置关闭窗口
cv.destroyAllWindows()
def math_demo():
image = cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png") # BGR 0-255
cv.imshow("input", image)
h, w, c = image.shape # 打印图像维度
blank = np.zeros_like(image) # 创建一个和image同尺寸的blank空白窗口
blank[:, :] = (2, 2, 2) # 让blank空白窗口上面的像素都是50x50
cv.imshow("blank", blank) # 显示一个blank空白窗口，窗口上面的像素都是50x50
# result=cv.add(image,blank)#进行加减时候，两幅图像大小必须一致，数据类型可以不用一致(增加亮度变亮）
# result = cv.subtract(image, blank) # 进行加减时候，两幅图像大小必须一致，数据类型可以不用一致（减少亮度变黑）
result = cv.divide(image, blank) # 改变对比度，对比度降低
# result = cv.multiply(image, blank)#改变对比度，对比度提高
cv.imshow("result", result) # 显示取反后的图片
# cv.imwrite("C:/Users/akaak/Pictures/OpenCV/csdn/4/savedexample.png", image)#保存数据图
cv.waitKey(0) # 设置关闭窗口
cv.destroyAllWindows()
def nothing(x):
print(x)
def adjust_light_demo():
image = cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png") # BGR 0-255
cv.namedWindow("input", cv.WINDOW_AUTOSIZE) # 创建一个自动大小的窗口
cv.createTrackbar("lightness", "input", 0, 100, nothing) # 创建一个名为lightness的trackbar,窗口与创建窗口一致。0-100,无回调
cv.imshow("input", image)
blank = np.zeros_like(image) # 创建一个和image同尺寸的blank空白窗口
while True:
pos = cv.getTrackbarPos("lightness", "input") # 拖动第几个TrackBar，TrackBar在哪个窗口。
blank[:, :] = (pos, pos, pos) # 让blank空白窗口上面的像素都是50x50
# cv.imshow("blank", blank)#显示一个blank空白窗口，窗口上面的像素都是50x50
result = cv.add(image, blank)
cv.imshow("result", result) # 显示取反后的图片
# cv.imwrite("C:/Users/akaak/Pictures/OpenCV/csdn/4/savedexample.png", image)#保存数据图
c = cv.waitKey(1) # 设置关闭窗口
if c == 27: # Esc
break
cv.destroyAllWindows()
def adjust_contrast_demo():
image = cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png") # BGR 0-255
cv.namedWindow("input", cv.WINDOW_AUTOSIZE) # 创建一个自动大小的窗口
cv.createTrackbar("lightness", "input", 0, 100, nothing) # 创建一个名为lightness的trackbar,窗口与创建窗口一致。0-100,无回调
cv.createTrackbar("contrast", "input", 100, 200, nothing) # 创建一个名为contrast的trackbar,窗口与创建窗口一致。100-200,无回调
cv.imshow("input", image)
blank = np.zeros_like(image) # 创建一个和image同尺寸的blank空白窗口
while True:
# pos=cv.getTrackbarPos("lightness","input")#拖动第几个TrackBar，TrackBar在哪个窗口。
light = cv.getTrackbarPos("lightness", "input") # 拖动第几个TrackBar，TrackBar在哪个窗口。亮度
contrast = cv.getTrackbarPos("contrast", "input") / 100 # 拖动第几个TrackBar，TrackBar在哪个窗口。对比度
print("light:", light, "contrast:", contrast) # 打印输出实时light和contrast
# blank[:,:]=(light,light,light)#让blank空白窗口上面的像素都是50x50
# cv.imshow("blank", blank)#显示一个blank空白窗口，窗口上面的像素都是50x50
result = cv.addWeighted(image, contrast, blank, 0.5, light) # 对比度和亮度调整函数
cv.imshow("result", result) # 显示取反后的图片
# cv.imwrite("C:/Users/akaak/Pictures/OpenCV/csdn/4/savedexample.png", image)#保存数据图
c = cv.waitKey(1) # 设置关闭窗口
if c == 27: # Esc
break
cv.destroyAllWindows()
def keys_demo():
image = cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png") # BGR 0-255
cv.namedWindow("input", cv.WINDOW_AUTOSIZE) # 创建一个自动大小的窗口
cv.imshow("input", image)
while True:
c = cv.waitKey(1) # 设置关闭窗口
gray = image
if c == 49: # 1控制gray窗口
gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
cv.imshow("result", gray) # 显示灰度图片
if c == 50: # 2控制hsv窗口
hsv = cv.cvtColor(image, cv.COLOR_BGR2HSV)
cv.imshow("result", hsv) # 显示灰度图片
if c == 51: # 3控制图像几何操作
invert = cv.bitwise_not(image)
cv.imshow("result", invert) # 显示图片几何操作
if c == 27: # Esc关闭所有窗口
break
cv.destroyAllWindows()
def color_table_demo():
colormap = [
cv.COLORMAP_AUTUMN,
cv.COLORMAP_BONE,
cv.COLORMAP_JET,
cv.COLORMAP_WINTER,
cv.COLORMAP_RAINBOW,
cv.COLORMAP_OCEAN,
cv.COLORMAP_SUMMER,
cv.COLORMAP_SPRING,
cv.COLORMAP_COOL,
cv.COLORMAP_PINK,
cv.COLORMAP_HOT,
cv.COLORMAP_PARULA,
cv.COLORMAP_MAGMA,
cv.COLORMAP_INFERNO,
cv.COLORMAP_PLASMA,
cv.COLORMAP_VIRIDIS,
cv.COLORMAP_CIVIDIS,
cv.COLORMAP_TWILIGHT,
cv.COLORMAP_TWILIGHT_SHIFTED
] # 自带颜色表操作代码19个
image = cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png") # BGR 0-255
cv.namedWindow("input", cv.WINDOW_AUTOSIZE) # 创建一个自动大小的窗口
cv.imshow("input", image)
index = 0
while True:
dst = cv.applyColorMap(image, colormap[index] % 19) # 循环19颜色
index += 1
cv.imshow("color style", dst)
c = cv.waitKey(1000) # 设置关闭窗口
if c == 27: # Esc关闭所有窗口
break
cv.destroyAllWindows()
def bitwise_demo():
b1 = np.zeros((400, 400, 3), dtype=np.uint8) # 创建一个彩色图片
b1[:, :] = (255, 0, 255) # 赋值
b2 = np.zeros((400, 400, 3), dtype=np.uint8) # 创建一个彩色图片
b2[:, :] = (0, 255, 0) # 赋值
cv.imshow("b1", b1)
cv.imshow("b2", b2)
dst1 = cv.bitwise_and(b1, b2) # 与
dst2 = cv.bitwise_or(b1, b2) # 或
cv.imshow("bitwise_and", dst1)
cv.imshow("bitwise_or", dst2)
cv.waitKey(0) # 设置关闭窗口
cv.destroyAllWindows()
def channel_split_demo():
b1 = cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png") # BGR 0-255
print(b1.shape) # 打印维度
cv.imshow("input", b1)
cv.imshow("b1", b1[:, :, 2])
mv = cv.split(b1) # 图像分离
print(len(mv))
mv[0][:, :] = 255 #
result = cv.merge(mv) # 图像合并
dst = np.zeros(b1.shape, dtype=np.uint8)
cv.mixChannels([b1], [dst], fromTo=[2, 0, 1, 1, 0, 2]) # 通道混合
cv.imshow("output4", dst)
cv.imshow("result", result)
cv.waitKey(0) # 设置关闭窗口
cv.destroyAllWindows()
def colorspace_demo():
b1 = cv.imread("C:/Users/akaak/Pictures/OpenCV/csdn/12/greenback.jpg") # BGR 0-255
print(b1.shape) # 打印维度
cv.imshow("input", b1)
hsv = cv.cvtColor(b1, cv.COLOR_BGR2HSV) # BGR转换为HSV
cv.imshow("hsv", hsv)
mask = cv.inRange(hsv, (35, 43, 46), (77, 255, 255)) # 根据像素范围进行过滤，把符合像素范围的保留，赋成0黑色和1白色(其实就是将绿色背景变成白色背景）
cv.imshow("mask", mask)
cv.bitwise_not(mask, mask) # 取反操作
result = cv.bitwise_and(b1, b1, mask=mask) # 原图与mask区域相与（mask大于0的区域）
cv.imshow("result", result)
cv.waitKey(0) # 设置关闭窗口
cv.destroyAllWindows()
def pixel_stat_demo():
b1 = cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png") # BGR 0-255
print(b1.shape) # 打印维度
cv.imshow("input", b1)
means, dev = cv.meanStdDev(b1) # 均值与方差
print(means, "dev:", dev)
cv.waitKey(0) # 设置关闭窗口
cv.destroyAllWindows()
def drawing_demo():
b1 = cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png") #
temp = np.copy(b1)
cv.rectangle(b1, (140, 50), (260, 210), (0, 0, 255), 4, 8, 0) # 左上角 右上角 颜色 线宽（<0填充，>0不填充） 领域
# cv.circle(b1,(200,200),100,(255,0,0),-2,8,0)#中心位置 半径 颜色 线宽 领域
# cv.line(b1,(50,50),(400,400),(0,255.0),4,8,0)
# b1[:,:,:]=0#还原
cv.putText(b1, "99% face", (50, 50), cv.FONT_HERSHEY_SIMPLEX, 1.0, (0, 255, 255), 2, 8) # 位置坐标 字体 字号 颜色 线宽 领域
cv.imshow("b1", b1)
cv.waitKey(0) # 设置关闭窗口
cv.destroyAllWindows()
def random_color_demo():
b1 = np.zeros((512, 512, 3), dtype=np.uint8)
while True: # 无休止的绘制
xx = np.random.randint(0, 512, 2, dtype=np.int) # 随机位置
yy = np.random.randint(0, 512, 2, dtype=np.int) # 随机位置
bgr = np.random.randint(0, 255, 3, dtype=np.int32) # 随机颜色
print(bgr[0], bgr[1], bgr[2])
cv.line(b1, (xx[0], yy[0]), (xx[1], yy[1]), (np.int(bgr[0]), np.int(bgr[1]), np.int(bgr[2])), 2, 8,
0) # 随机位置绘制 随机颜色绘制
cv.imshow("input", b1)
c = cv.waitKey(10) # 设置关闭窗口
if c == 27:
break
cv.destroyAllWindows()
def polyline_drawing_demo():
canvas = np.zeros((512, 512, 3), dtype=np.uint8)
pts = np.array([[100, 100], [350, 100], [450, 280], [320, 450], [80, 400]], dtype=np.int32) # 五个点
# cv.fillPoly(canvas,[pts],(255,0,255),8,0)#填充多边形
# cv.polylines(canvas,[pts],True,(0,0,255),2,8,0);#绘制多边形
cv.drawContours(canvas, [pts], -1, (255, 0, 0), -1) # 万能操作 集合上个两个API优点 填充＋绘制
cv.imshow("poyline", canvas)
c = cv.waitKey(0) # 设置关闭窗口
cv.destroyAllWindows()
# b1=np.zeros((512,512,3),dtype=np.uint8)
b1 = cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png")
img = np.copy(b1)
x1 = -1
x2 = -1
y1 = -1
y2 = -1
def mouse_drawing(event, x, y, flags, param): # 回调函数mouse_drawing
global x1, y1, x2, y2 # 全局变量
print(x, y) # 回调函数(给系统)
if event == cv.EVENT_LBUTTONDOWN: # 按下
x1 = x
y1 = y
if event == cv.EVENT_MOUSEMOVE: # 移动
if x1 < 0 or y1 < 0:
return
x2 == x
y2 = y
dx = x2 - x1
dy = y2 - y1
if dx > 0 or dy > 0:
b1[:, :, :] = img[:, :, :]
cv.rectangle(b1, (x1, y1), (x2, y2), (0, 0, 255), 2, 8, 0) # 绘制矩形
if event == cv.EVENT_LBUTTONUP: # 抬起
x2 == x
y2 = y
dx = x2 - x1
dy = y2 - y1
if dx > 0 or dy > 0:
b1[:, :, :] = img[:, :, :]
cv.rectangle(b1, (x1, y1), (x2, y2), (0, 0, 255), 2, 8, 0)
x1 = -1 # 重置回原来的初始值
x2 = -1
y1 = -1
y2 = -1
def mouse_demo():
cv.namedWindow("mouse_demo", cv.WINDOW_AUTOSIZE) # 创建一个窗口
cv.setMouseCallback("mouse_demo", mouse_drawing) # 调用鼠标操作
while True:
cv.imshow("mouse_demo", b1)
c = cv.waitKey(10)
if c == 27:
break
cv.destroyAllWindows()
def norm_demo():
image = cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png")
cv.namedWindow("norm_demo", cv.WINDOW_AUTOSIZE) # 创建一个窗口
print(image / 255.0)
# cv.imshow("norm_demo",image/255.0)#归一化演示 浮点数
# cv.imshow("norm_demo", np.float32(image))#浮点数
# cv.imshow("norm_demo", np.float32(image) / 255.0)#归一化0-1
# cv.imshow("norm_demo", np.uint8(image))#正常显示
# result=np.zeros_like(np.float32(image))
# cv.normalize(np.float32(image),result,0,1,cv.NORM_MINMAX,dtype=cv.CV_32F)
# cv.imshow("norm_demo", result)
result = np.zeros_like(np.float32(image))
cv.normalize(np.float32(image), result, 0, 1, cv.NORM_MINMAX, dtype=cv.CV_32F)
cv.imshow("norm_demo", np.uint8(result * 255)) # 浮点数变字节 深度学习
cv.waitKey(0)
cv.destroyAllWindows()
def resize_demo():
image = cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png")
h,w,c=image.shape
cv.namedWindow("resize_demo", cv.WINDOW_AUTOSIZE) # 创建一个窗口
dst=cv.resize(image,(w//h,h//2),interpolation=cv.INTER_NEAREST)#放缩与插值
dst = cv.resize(image,(0,0),fx=0.75,fy=0.75,interpolation=cv.INTER_NEAREST) # 指定大小放缩与插值
cv.imshow("resize_demo", dst)
cv.waitKey(0)
cv.destroyAllWindows()
def flip_demo():
image = cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png")
cv.namedWindow("flip_demo", cv.WINDOW_AUTOSIZE) # 创建一个窗口
#dst=cv.flip(image,0)#0上下翻转
#dst = cv.flip(image, 1) # 1左右翻转
dst = cv.flip(image, -1) # -1对角线翻转
cv.imshow("image", image)
cv.imshow("flip_demo", dst)
cv.waitKey(0)
cv.destroyAllWindows()
def rotate_demo():
src=cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png")
cv.imshow("image",src)
h,w,c=src.shape
#定义矩阵
M=np.zeros((2,3),dtype=np.float32)
#定义角度
alpha=np.cos(np.pi/4.0)
beta=np.sin(np.pi/4.0)
print("alpha:",alpha)
#初始化矩阵
M[0,0]=alpha
M[1,1] =alpha
M[0,1] =beta
M[1,0] =-beta
cx=w/2
cy=h/2
tx=(1-alpha)*cx-beta*cy
ty=beta*cx+(1-alpha)*cy
M[0,2] = tx
M[1,2] = ty
#change with full size
bound_w=int(h*np.abs(beta)+w*np.abs(alpha))
bound_h = int(h * np.abs(alpha) + w * np.abs(beta))
#添加中心位置迁移
M[0, 2] +=bound_w/2-tx
M[1, 2] +=bound_h/2-ty
dst=cv.warpAffine(src,M,(bound_w,bound_h))
cv.imshow("rotate without cropping",dst)
cv.waitKey(0)
cv.destroyAllWindows()
def video_demo():
cap=cv.VideoCapture("C:/Users/akaak/Videos/01.mp4")#读视频 通过摄像头/路径
w=cap.get(cv.CAP_PROP_FRAME_WIDTH)#获取宽度
h=cap.get(cv.CAP_PROP_FRAME_HEIGHT)#获取高度
fps=cap.get(cv.CAP_PROP_FPS)#获取帧率：1s中播放多少张图像
#out=cv.VideoWriter("C:/Users/akaak/Videos/TEST.mp4",cv.VideoWriter_fourcc('P','I','M','1'),fps,(np.int(w),np.int(h)),True)
out=cv.VideoWriter("C:/Users/akaak/Videos/TEST.mp4", cv.CAP_ANY,np.int(cap.get(cv.CAP_PROP_FOURCC)),fps,(np.int(w),np.int(h)),True)
#out = cv.VideoWriter("C:/Users/akaak/Videos/TEST.mp4", cv.CAP_FFMPEG, np.int(cap.get(cv.CAP_PROP_FOURCC)), fps,(np.int(w), np.int(h)), True)#没有test生成
print(w,h,fps)
while True:
ret,frame=cap.read()
#frame=cv.flip(frame,1)
if ret is not True:#读完视频自动关闭
break
cv.imshow("frame",frame)
hsv=cv.cvtColor(frame,cv.COLOR_BGR2HSV)#hsv转换
cv.imshow("result",hsv)#显示hsv
out.write(hsv)#保存
c=cv.waitKey(10)
if c==27:
break
cv.destroyAllWindows()
out.release()#写完释放
cap.release()#相机用完也释放
def image_hist():
image=cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png")
cv.imshow("input",image)
color=('blue','green','red')#三通道
for i,color in enumerate(color):#每个通道循环一次
hist=cv.calcHist([image],[i],None,[256],[0,256])#计算直方图统计的API函数
print(hist)#打印
plt.plot(hist,color=color)
plt.xlim([0,256])#可改参数【32】
plt.show()
cv.waitKey(0)
cv.destroyAllWindows()
def hist2d_demo():
image=cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png")
hsv=cv.cvtColor(image,cv.COLOR_BGR2HSV)#转成hsv
hist=cv.calcHist([hsv],[0,1],None,[48,48],[0,180,0,256])#h 0-180 s 0-256 计算2d直方图
dst=cv.resize(hist,(400,400))#变幻尺寸400*400
cv.normalize(dst,dst,0,255,cv.NORM_MINMAX)#归一化0-255 key point!
cv.imshow("image",image)
dst=cv.applyColorMap(np.uint8(dst),cv.COLORMAP_JET)#色彩填充
cv.imshow("hist",dst)
plt.imshow(hist,interpolation='nearest')
plt.title("2D Histogram")
plt.show()
cv.waitKey(0)
cv.destroyAllWindows()
def eqhist_demo():
image=cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png",cv.IMREAD_GRAYSCALE)#灰度图
cv.imshow("input",image)
result=cv.equalizeHist(image)#直方图均衡化API
cv.imshow("result", result)
cv.waitKey(0)
cv.destroyAllWindows()
def conv_demo():
#image=cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png",cv.IMREAD_GRAYSCALE)#灰度图
image = cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png") # 灰度图
cv.imshow("input",image)
result=cv.blur(image,(15,15))#卷积和API(模糊 可改参数)
cv.imshow("result", result)
cv.waitKey(0)
cv.destroyAllWindows()
def Gaussian_demo():
#image=cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png",cv.IMREAD_GRAYSCALE)#灰度图
image = cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png") # 灰度图
cv.imshow("input",image)
#result=cv.GaussianBlur(image,(0,0),15)#高斯模糊API(模糊 可改参数)
result = cv.GaussianBlur(image, (5, 5), 15) # 高斯模糊API(模糊 可改参数)高斯核函数必须是奇数
cv.imshow("result", result)
cv.waitKey(0)
cv.destroyAllWindows()
def bitfilter_demo():
#image=cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png",cv.IMREAD_GRAYSCALE)#灰度图
image = cv.imread("C:/Users/akaak/Pictures/OpenCV/1.png") # 灰度图
cv.imshow("input",image)
#result=cv.GaussianBlur(image,(0,0),15)#高斯模糊API(模糊 可改参数)
result = cv.bilateralFilter(image,0,100,10,) # 高斯双边模糊API(模糊 可改参数)类似于磨皮PS
cv.imshow("result", result)
cv.waitKey(0)
cv.destroyAllWindows()
if __name__ == "__main__":
bitfilter_demo()
三、运行结果
总结
本文介绍了笔者学习Python-opencv第二十九课：高斯双边模糊，学习了cv.bilateralFilter(image,0,100,10,) 函数实现了对图像高斯双边模糊的操作。（代码资料来源于网络贾老师视频）