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添加番外篇5，更改结构 2018年11月22日
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‎04. 图像基本操作/cv2_basic_operations.py

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# More: http://ex2tron.wang
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# ex2tron's blog:
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# http://ex2tron.wang
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import cv2
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img = cv2.imread('lena.jpg')
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# 1.获取像素的值
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px = img[100, 100]
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print(px) # [119 108 201]
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px = img[100, 90]
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print(px) # [103 98 197]
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# 只获取蓝色blue通道的值
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px_blue = img[100, 100, 0]
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print(px_blue) # 119
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px_blue = img[100, 90, 0]
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print(px_blue) # 103
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# 2.修改像素的值
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img[100, 100] = [255, 255, 255]
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print(img[100, 100]) # [255 255 255]
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img[100, 90] = [255, 255, 255]
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print(img[100, 90]) # [255 255 255]
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# 3.图片形状
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print(img.shape) # (263, 263, 3)
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# 形状中包括高度、宽度和通道数
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print(img.shape) # (263, 247, 3)
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# 形状中包括行数、列数和通道数
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height, width, channels = img.shape
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# img是灰度图的话：height, width = img.shape
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# 总像素数
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print(img.size) # 263*263*3=207507
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print(img.size) # 263*247*3=194883
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# 数据类型
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print(img.dtype) # uint8
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‎04. 图像基本操作/cv2_exercise1.py

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# More: http://ex2tron.wang
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# ex2tron's blog:
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# http://ex2tron.wang
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import cv2
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‎04. 图像基本操作/lena.jpg

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‎05. 颜色空间转换/cv2_changing_color_space.py

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# More: http://ex2tron.wang
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# ex2tron's blog:
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# http://ex2tron.wang
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import cv2
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import numpy as np
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img = cv2.imread('lena.jpg')
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print(flags)
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# 蓝色的HSV值
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import numpy as np
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blue = np.uint8([[[255, 0, 0]]])
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hsv_blue = cv2.cvtColor(blue, cv2.COLOR_BGR2HSV)
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print(hsv_blue) # [[[120 255 255]]]

‎05. 颜色空间转换/cv2_exercises1.py

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# More: http://ex2tron.wang
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# ex2tron's blog:
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# http://ex2tron.wang
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import cv2
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import numpy as np

‎06. 阈值分割/cv2_thresholding.py

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# More: http://ex2tron.wang
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# ex2tron's blog:
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# http://ex2tron.wang
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import cv2
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import matplotlib.pyplot as plt

‎07. 图像几何变换/cv2_geometric_transformations.py

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# More: http://ex2tron.wang
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# ex2tron's blog:
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# http://ex2tron.wang
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import cv2
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import numpy as np
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import matplotlib.pyplot as plt
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img = cv2.imread('drawing.jpg')
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cv2.waitKey(0)
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# 2.平移图片
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# 2.翻转图片
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import numpy as np
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# 参数2=0：垂直翻转(沿x轴)，参数2>0: 水平翻转(沿y轴)
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# 参数2<0: 水平垂直翻转
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dst = cv2.flip(img, -1)
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# np.hstack: 横向并排，对比显示
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cv2.imshow('flip', np.hstack((img, dst))) # np.hstack: 横向并排，对比显示
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cv2.waitKey(0)
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# 3.平移图片
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rows, cols = img.shape[:2]
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# 定义平移矩阵，需要是numpy的float32类型
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# x轴平移100，y轴平移50
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cv2.waitKey(0)
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# 3.45°旋转图片并缩小一半
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M = cv2.getRotationMatrix2D((cols / 2, rows / 2), 45, 0.5)
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# 4.45°顺时针旋转图片并缩小一半
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M = cv2.getRotationMatrix2D((cols / 2, rows / 2), -45, 0.5)
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dst = cv2.warpAffine(img, M, (cols, rows))
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cv2.imshow('rotation', dst)
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cv2.waitKey(0)
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# 4.翻转图片
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# 参数2=0：垂直翻转(沿x轴)，参数2>0: 水平翻转(沿y轴)
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# 参数2<0: 水平垂直翻转
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dst = cv2.flip(img, 1)
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# np.hstack: 横向并排，对比显示
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cv2.imshow('flip', np.hstack((img, dst))) # np.hstack: 横向并排，对比显示
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cv2.waitKey(0)
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# 5.仿射变换
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# 变换前的三个点
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pts1 = np.float32([[50, 65], [150, 65], [210, 210]])
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# 变换后的三个点
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pts2 = np.float32([[50, 100], [150, 65], [100, 250]])
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# 生成变换矩阵，维数：2*3
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M = cv2.getAffineTransform(pts1, pts2)
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dst = cv2.warpAffine(img, M, (cols, rows))
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plt.subplot(121), plt.imshow(img), plt.title('input')
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plt.subplot(122), plt.imshow(dst), plt.title('output')
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plt.show()

‎08. 绘图功能/cv2_drawing_functions.py

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# More: http://ex2tron.wang
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# ex2tron's blog:
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# http://ex2tron.wang
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import cv2
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import numpy as np

‎08. 绘图功能/cv2_exercise1.py

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# More: http://ex2tron.wang
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# ex2tron's blog:
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# http://ex2tron.wang
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import cv2
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import numpy as np

‎09. 图像混合/cv2_image_blending.py

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# More: http://ex2tron.wang
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# ex2tron's blog:
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# http://ex2tron.wang
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import cv2
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import numpy as np

‎README.md

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# OpenCV-Python图像处理教程
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## OpenCV-Python图像处理教程（源码及素材）
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> 教程地址：[ex2tron's Blog](http://ex2tron.wang)

‎番外篇01. 代码性能优化/cv2_optimization.py

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# More: http://ex2tron.wang
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# ex2tron's blog:
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# http://ex2tron.wang
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import cv2
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import numpy as np

‎番外篇03. 滑动条/cv2_trackbar.py

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# More: http://ex2tron.wang
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# ex2tron's blog:
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# http://ex2tron.wang
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import cv2
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import numpy as np

‎番外篇04. Otsu阈值法/cv2_otsu_thresholding.py

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# More: http://ex2tron.wang
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# ex2tron's blog:
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# http://ex2tron.wang
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import cv2
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from matplotlib import pyplot as plt

‎07. 图像几何变换/card.jpg renamed to ‎番外篇05. 仿射变换和透视变换原理/card.jpg

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‎07. 图像几何变换/cv2_perspective_transformation.py renamed to ‎番外篇05. 仿射变换和透视变换原理/cv2_affine_perspective_transformation.py

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# More: http://ex2tron.wang
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# ex2tron's blog:
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# http://ex2tron.wang
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import cv2
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import numpy as np
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import matplotlib.pyplot as plt
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img = cv2.imread('card.jpg')
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img = cv2.imread('drawing.jpg')
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rows, cols = img.shape[:2]
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# 1.仿射变换
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# 变换前的三个点
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pts1 = np.float32([[50, 65], [150, 65], [210, 210]])
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# 变换后的三个点
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pts2 = np.float32([[50, 100], [150, 65], [100, 250]])
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# 生成变换矩阵，维数：2*3
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M = cv2.getAffineTransform(pts1, pts2)
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dst = cv2.warpAffine(img, M, (cols, rows))
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plt.subplot(121), plt.imshow(img), plt.title('input')
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plt.subplot(122), plt.imshow(dst), plt.title('output')
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plt.show()
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# 2.透视变换
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img = cv2.imread('card.jpg')
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# 原图中卡片的四个角点
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pts1 = np.float32([[148, 80], [437, 114], [94, 247], [423, 288]])
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# 变换后分别在左上、右上、左下、右下四个点
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pts2 = np.float32([[0, 0], [320, 0], [0, 178], [320, 178]])
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# 生成透视变换矩阵
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M = cv2.getPerspectiveTransform(pts1, pts2)
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# 进行透视变换
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# 进行透视变换，参数3是目标图像大小
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dst = cv2.warpPerspective(img, M, (320, 178))
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# matplotlib默认以RGB通道显示，所以需要用[:, :, ::-1]翻转一下

‎番外篇05. 仿射变换和透视变换原理/drawing.jpg

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‎番外篇05. 鼠标绘图/cv2_mouse_drawing.py renamed to ‎番外篇06. 鼠标绘图/cv2_mouse_drawing.py

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‎番外篇05. 鼠标绘图/cv2_mouse_drawing_example.py renamed to ‎番外篇06. 鼠标绘图/cv2_mouse_drawing_example.py

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‎番外篇05. 鼠标绘图/cv2_mouse_drawing_exercise1.py renamed to ‎番外篇06. 鼠标绘图/cv2_mouse_drawing_exercise1.py

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‎番外篇05. 鼠标绘图/cv2_mouse_drawing_exercise2.py renamed to ‎番外篇06. 鼠标绘图/cv2_mouse_drawing_exercise2.py

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‎番外篇06. 亮度与对比度/cv2_contrast_brightness.py renamed to ‎番外篇07. 亮度与对比度/cv2_contrast_brightness.py

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‎番外篇06. 亮度与对比度/cv2_exercise1.py renamed to ‎番外篇07. 亮度与对比度/cv2_exercise1.py

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‎番外篇06. 亮度与对比度/lena.jpg renamed to ‎番外篇07. 亮度与对比度/lena.jpg

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‎番外篇07. 卷积基础(图片边框)/6_by_6.bmp renamed to ‎番外篇08. 卷积基础(图片边框)/6_by_6.bmp

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‎番外篇07. 卷积基础(图片边框)/cv2_border_convolution.py renamed to ‎番外篇08. 卷积基础(图片边框)/cv2_border_convolution.py

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‎番外篇07. 卷积基础(图片边框)/lena.jpg renamed to ‎番外篇08. 卷积基础(图片边框)/lena.jpg

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‎番外篇08. 图像梯度/cv2_image_gradient.py renamed to ‎番外篇09. 图像梯度/cv2_image_gradient.py

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‎番外篇08. 图像梯度/sudoku.jpg renamed to ‎番外篇09. 图像梯度/sudoku.jpg

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‎番外篇09. 轮廓层级/circle_ring.jpg renamed to ‎番外篇10. 轮廓层级/circle_ring.jpg

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‎番外篇09. 轮廓层级/cv2_exercise1.py renamed to ‎番外篇10. 轮廓层级/cv2_exercise1.py

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‎番外篇09. 轮廓层级/cv2_understand_hierarchy.py renamed to ‎番外篇10. 轮廓层级/cv2_understand_hierarchy.py

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‎番外篇09. 轮廓层级/hierarchy.jpg renamed to ‎番外篇10. 轮廓层级/hierarchy.jpg

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‎番外篇10. 凸包及更多轮廓特征/convex.jpg renamed to ‎番外篇11. 凸包及更多轮廓特征/convex.jpg

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‎番外篇10. 凸包及更多轮廓特征/cv2_convex_hull.py renamed to ‎番外篇11. 凸包及更多轮廓特征/cv2_convex_hull.py

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‎番外篇10. 凸包及更多轮廓特征/unregular.jpg renamed to ‎番外篇11. 凸包及更多轮廓特征/unregular.jpg

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‎番外篇11. 尺度空间与图像金字塔/cv2_pyrdown_pyrup.py renamed to ‎番外篇12. 尺度空间与图像金字塔/cv2_pyrdown_pyrup.py

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‎番外篇11. 尺度空间与图像金字塔/lena.jpg renamed to ‎番外篇12. 尺度空间与图像金字塔/lena.jpg

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