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OpenCV之基本阈值操作

python代码： import cv2 as cv import numpy as np # # THRESH_BINARY = 0 # THRESH_BINARY_INV = 1 # THRESH_TRUNC = 2 # THRESH_TOZERO = 3 # THRESH_TOZERO_INV = 4 # src = cv.imread("./test.png") cv.namedWindow("input", cv.WINDOW_AUTOSIZE) cv.imshow("input", src)

2021-08-13

4470

OpenCV之二值图像介绍

python代码： import cv2 as cv import numpy as np src = cv.imread("./test.png") cv.namedWindow("input", cv.WINDOW_AUTOSIZE) cv.imshow("input", src) T = 127 # 转换为灰度图像 gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY) h, w = gray.shape T = cv.mean(gray)[0] print("cu

2021-08-13

2510

OpenCV之图像模板匹配

python代码： import cv2 as cv import numpy as np def template_demo(): src = cv.imread("./test.png") tpl = cv.imread("./test01.png") cv.imshow("input", src) cv.imshow("tpl", tpl) th, tw = tpl.shape[:2] result = cv.matchTemplate(src, t

2021-08-13

3930

OpenCV之USM 锐化增强算法

python代码： import cv2 as cv import numpy as np src = cv.imread("./test.png") cv.namedWindow("input", cv.WINDOW_AUTOSIZE) cv.imshow("input", src) # sigma = 5、15、25 blur_img = cv.GaussianBlur(src, (0, 0), 5) usm = cv.addWeighted(src, 1.5, blur_img, -0.5, 0)

2021-08-05

9510

OpenCV之图像梯度 – 拉普拉斯算子(二阶导数算子)

python代码： import cv2 as cv import numpy as np image = cv.imread("./test.png") cv.namedWindow("input", cv.WINDOW_AUTOSIZE) cv.imshow("input", image) h, w = image.shape[:2] src = cv.GaussianBlur(image, (0, 0), 1) dst = cv.Laplacian(src, cv.CV_32F, ksize=3,

2021-07-27

5910

OpenCV之快速的图像边缘滤波算法

python代码： import cv2 as cv import numpy as np src = cv.imread("./test.png") cv.namedWindow("input", cv.WINDOW_AUTOSIZE) cv.imshow("input", src) h, w = src.shape[:2] dst = cv.edgePreservingFilter(src, sigma_s=100, sigma_r=0.4, flags=cv.RECURS_FILTER) resu

2021-07-23

3520

OpenCV之边缘保留滤波算法 – 均值迁移模糊(mean-shift blur)

python代码： import cv2 as cv import numpy as np src = cv.imread("./test.png") cv.namedWindow("input", cv.WINDOW_AUTOSIZE) cv.imshow("input", src) h, w = src.shape[:2] dst = cv.pyrMeanShiftFiltering(src, 15, 30, termcrit=(cv.TERM_CRITERIA_MAX_ITER+cv.TERM_C

2021-07-20

5660

OpenCV之边缘保留滤波算法 – 高斯双边模糊

python代码： import cv2 as cv import numpy as np src = cv.imread("./test.png") cv.namedWindow("input", cv.WINDOW_AUTOSIZE) cv.imshow("input", src) h, w = src.shape[:2] dst = cv.bilateralFilter(src, 0, 100, 10) result = np.zeros([h, w*2, 3], dtype=src.dtype)

2021-07-20

4350

OpenCV之图像均值与高斯模糊

python代码： import cv2 as cv import numpy as np src = cv.imread("./test.png") cv.namedWindow("input", cv.WINDOW_AUTOSIZE) cv.imshow("input", src) dst1 = cv.blur(src, (5, 5)) dst2 = cv.GaussianBlur(src, (5, 5), sigmaX=15) dst3 = cv.GaussianBlur(src, (0, 0)

2021-07-20

5410

OpenCV之图像像素读写

python代码： import cv2 as cv src = cv.imread("./test.png") cv.namedWindow("input", cv.WINDOW_AUTOSIZE) cv.imshow("input", src) h, w, ch = src.shape print("h , w, ch", h, w, ch) for row in range(h): for col in range(w): b, g, r = src[row, col]

2021-07-19

2040

OpenCV之图像创建与赋值

python代码： import cv2 as cv import numpy as np src = cv.imread("./test.png") cv.namedWindow("input", cv.WINDOW_AUTOSIZE) cv.imshow("input", src) # 克隆图像 m1 = np.copy(src) # 赋值 m2 = src src[100:200,200:300,:] = 255 cv.imshow("m2",m2) m3 = np.zeros(src.sha

2021-07-19

4350

OpenCV之图像像素算术操作(加减乘除)

python代码： import cv2 as cv import numpy as np src1 = cv.imread("./test0.jpg") src2 = cv.imread("./test0.jpg") cv.imshow("input1", src1) cv.imshow("input2", src2) h, w, ch = src1.shape print("h , w, ch", h, w, ch) add_result = np.zeros(src1.shape, src1.dt

2021-07-19

2920

OpenCV之图像伪彩色增强

python代码： import cv2 as cv src = cv.imread("test1.png") cv.namedWindow("input", cv.WINDOW_AUTOSIZE) cv.imshow("input", src) dst = cv.applyColorMap(src, cv.COLORMAP_COOL) cv.imshow("output", dst) # 伪色彩 image = cv.imread("test0.jpg") color_image = cv.apply

2021-07-19

6150

OpenCV之图像插值

python代码： import cv2 as cv src = cv.imread("./test.png") cv.namedWindow("input", cv.WINDOW_AUTOSIZE) cv.imshow("input", src) h, w = src.shape[:2] print(h, w) dst = cv.resize(src, (w*2, h*2), fx=0.75, fy=0.75, interpolation=cv.INTER_NEAREST) cv.imshow("IN

2021-07-19

3690

OpenCV之图像翻转

python代码： import cv2 as cv import numpy as np src = cv.imread("./test.png") cv.namedWindow("input", cv.WINDOW_AUTOSIZE) cv.imshow("input", src) # X Flip 倒影 dst1 = cv.flip(src, 0); cv.imshow("x-flip", dst1); # Y Flip 镜像 dst2 = cv.flip(src, 1); cv.imshow(

2021-07-19

2690

OpenCV之视频读写

python代码： import cv2 as cv import numpy as np capture = cv.VideoCapture("./test.avi") # capture = cv.VideoCapture(0) 打开摄像头 height = capture.get(cv.CAP_PROP_FRAME_HEIGHT) width = capture.get(cv.CAP_PROP_FRAME_WIDTH) count = capture.get(cv.CAP_PROP_FRAME_C

2021-07-19

3990

OpenCV之图像像素值统计

python代码： import cv2 as cv import numpy as np src = cv.imread("./test.png", cv.IMREAD_GRAYSCALE) cv.namedWindow("input", cv.WINDOW_AUTOSIZE) cv.imshow("input", src) min, max, minLoc, maxLoc = cv.minMaxLoc(src) print("min: %.2f, max: %.2f"% (min, max)) pr

2021-07-19

5990

OpenCV之色彩空间与色彩空间转换

python代码： import cv2 as cv src = cv.imread("test.jpg") cv.namedWindow("rgb", cv.WINDOW_AUTOSIZE) cv.imshow("rgb", src) # RGB to HSV hsv = cv.cvtColor(src, cv.COLOR_BGR2HSV) cv.imshow("hsv", hsv) # RGB to YUV yuv = cv.cvtColor(src, cv.COLOR_BGR2YUV) cv.i

2021-07-19

3850

OpenCV之图像通道分离合并

python代码： import cv2 as cv src = cv.imread("./test.png") cv.namedWindow("input", cv.WINDOW_AUTOSIZE) cv.imshow("input", src) # 蓝色通道为零 mv = cv.split(src) mv[0][:, :] = 0 dst1 = cv.merge(mv) cv.imshow("output1", dst1) # 绿色通道为零 mv = cv.split(src) mv[1][:,

2021-07-19

2710

ubuntu下make编译生成动态库，然后python调用cpp。

python ubuntu c++

摘要总结：本文介绍了如何在Ubuntu系统下使用g++编译出动态库，并使用Python调用cpp的函数。通过实例介绍了OpenTLD算法，并给出了具体的实现步骤和代码示例。

2018-01-09

1.5K0

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