opencv的各项基础操作，共109个实例，均在anaconda3、python3.7和opencv4环境下成功调试。

简介：
code_001 | [图片读取与显示](python/code_001/opencv_001.py) | ✔️code_002 | [图片灰度化](python/code_002/opencv_002.py) | ✔️code_003 | [图像创建与赋值](python/code_003/opencv_003.py) | ✔️code_004 | [图像像素读写](python/code_004/opencv_004.py) | ✔️code_005 | [图像像素算术操作(加减乘除)](python/code_005/opencv_005.py) | ✔️code_006 | [图像伪彩色增强](python/code_006/opencv_006.py) | ✔️code_007 | [图像像素操作(逻辑操作)](python/code_007/opencv_007.py) | ✔️code_008 | [图像通道分离合并](python/code_008/opencv_008.py) | ✔️code_009 | [色彩空间与色彩空间转换](python/code_009/opencv_009.py) | ✏️code_010 | [图像像素值统计](python/code_010/opencv_010.py) | ✔️code_011 | [图像像素归一化](python/code_011/opencv_011.py) | ✔️code_012 | [视频读写](python/code_012/opencv_012.py) | ✔️code_013 | [图像翻转](python/code_013/opencv_013.py) | ✔️code_014 | [图像插值](python/code_014/opencv_014.py) | ✔️code_015 | [绘制几何形状](python/code_015/opencv_015.py) | ✔️code_016 | [图像ROI与ROI操作](python/code_016/opencv_016.py) | ✔️code_017 | [图像直方图](python/code_017/opencv_017.py) | ✔️code_018 | [图像直方图均衡化](python/code_018/opencv_018.py) | ✏️code_019 | [图像直方图比较](python/code_019/opencv_019.py) | ✔️code_020 | [图像直方图反向投影](python/code_020/opencv_020.py) | ✔️code_021 | [图像卷积操作](python/code_021/opencv_021.py) | ✔️code_022 | [图像均值与高斯模糊](python/code_022/opencv_022.py) | ❣️code_023 | [中值模糊](python/code_023/opencv_023.py) | ✔️code_024 | [图像噪声](python/code_024/opencv_024.py) | ✔️code_025 | [图像去噪声](python/code_025/opencv_025.py) | ✔️code_026 | [高斯双边模糊](python/code_026/opencv_026.py) | ✔️code_027 | [均值迁移模糊(mean-shift blur)](python/code_027/opencv_027.py) | ✔️code_028 | [图像积分图算法](python/code_028/opencv_028.py) | ✔️code_029 | [快速的图像边缘滤波算法](python/code_029/opencv_029.py) | ✔️code_030 | [自定义滤波器](python/code_030/opencv_030.py) | ✔️code_031 | [Sobel算子](python/code_031/opencv_031.py) | ✔️code_032 | [更多梯度算子](python/code_032/opencv_032.py) | ✔️code_033 | [拉普拉斯算子(二阶导数算子)](python/code_033/opencv_033.py) | ✔️code_034 | [图像锐化](python/code_034/opencv_034.py) | ✔️code_035 | [USM 锐化增强算法](python/code_035/opencv_035.py) | ✔️code_036 | [Canny边缘检测器](python/code_036/opencv_036.py) | ❣️code_037 | [图像金字塔](python/code_037/opencv_037.py) | ✔️code_038 | [拉普拉斯金字塔](python/code_038/opencv_038.py) | ✔️code_039 | [图像模板匹配](python/code_039/opencv_039.py) | ✔️code_040 | [二值图像介绍](python/code_040/opencv_040.py) | ✔️code_041 | [基本阈值操作](python/code_041/opencv_041.py) | ✔️code_042 | [图像二值寻找法OTSU](python/code_042/opencv_042.py) | ✏️code_043 | [图像二值寻找法TRIANGLE](python/code_043/opencv_043.py) | ✔️code_044 | [图像自适应阈值算法](python/code_044/opencv_044.py) | ✏️code_045 | [图像二值与去噪](python/code_045/opencv_045.py) | ✏️code_046 | [图像连通组件寻找](python/code_046/opencv_046.py) | ✔️code_047 | [图像连通组件状态统计](python/code_047/opencv_047.py) | ✔️code_048 | [轮廓寻找](python/code_048/opencv_048.py) | ❣️code_049 | [轮廓外接矩形](python/code_049/opencv_049.py) | ❣️code_050 | [轮廓矩形面积与弧长](python/code_050/opencv_050.py) | ✏️code_051 | [轮廓逼近](python/code_051/opencv_051.py) | ✔️code_052 | [几何矩计算中心](python/code_052/opencv_052.py) | ✔️code_053 | [使用Hu矩阵实现轮廓匹配](python/code_053/opencv_053.py) | ✔️code_054 | [轮廓圆与椭圆拟合](python/code_054/opencv_054.py) | ✔️code_055 | [凸包检测](python/code_055/opencv_055.py) | ✏️code_056 | [直线拟合与极值点寻找](python/code_056/opencv_056.py) | ✔️code_057 | [点多边形测试](python/code_057/opencv_057.py) | ✔️code_058 | [寻找最大内接圆](python/code_058/opencv_058.py) | ✔️code_059 | [霍夫曼直线检测](python/code_059/opencv_059.py) | ✔️code_060 | [概率霍夫曼直线检测](python/code_060/opencv_060.py) | ❣️code_061 | [霍夫曼圆检测](python/code_061/opencv_061.py) | ❣️code_062 | [膨胀和腐蚀](python/code_062/opencv_062.py) | ❣️code_063 | [结构元素](python/code_063/opencv_063.py) | ✔️code_064 | [开运算](python/code_064/opencv_064.py) | ✏️code_065 | [闭运算](python/code_065/opencv_065.py) | ✏️code_066 | [开闭运算的应用](python/code_066/opencv_066.py) | ✏️code_067 | [顶帽](python/code_067/opencv_067.py) | ✔️code_068 | [黑帽](python/code_068/opencv_068.py) | ✔️code_069 | [图像梯度](python/code_069/opencv_069.py) | ✔️code_070 | [基于梯度的轮廓发现](python/code_070/opencv_070.py) | ✏️code_071 | [击中击不中](python/code_071/opencv_071.py) | ✔️code_072 | [缺陷检测1](python/code_072) | ✔️code_073 | [缺陷检测2](python/code_073/opencv_073.py) | ✔️code_074 | [提取最大轮廓和编码关键点](python/code_074) | ✔️code_075 | [图像修复](python/code_075/opencv_075.py) | ✔️code_076 | [图像透视变换应用](python/code_076/opencv_076.py) | ✏️code_077 | [视频读写和处理](python/code_077/opencv_077.py) | ✏️code_078 | [识别与跟踪视频中的特定颜色对象](python/code_078) | ✔️code_079 | [视频分析-背景/前景 提取](python/code_079/opencv_079.py) | ✔️code_080 | [视频分析–背景消除与前景ROI提取](python/code_080) | ✔️code_081 | [角点检测-Harris角点检测](python/code_081) | ✔️code_082 | [角点检测-Shi-Tomas角点检测](python/code_082) | ✏️code_083 | [角点检测-亚像素角点检测](python/code_083) | ✔️code_084 | [视频分析-KLT光流跟踪算法-1](python/code_084) | ✏️code_085 | [视频分析-KLT光流跟踪算法-2](python/code_085) | ✏️code_086 | [视频分析-稠密光流分析](python/code_086) | ✏️code_087 | [视频分析-帧差移动对象分析](python/code_087/opencv_087.py) | ✔️code_088 | [视频分析-均值迁移](python/code_088) | ✏️code_089 | [视频分析-连续自适应均值迁移](python/code_089) | ✏️code_090 | [视频分析-对象移动轨迹绘制](python/code_090) | ✔️code_091 | [对象检测-HAAR级联分类器](python/code_091) | ✔️code_092 | [对象检测-HAAR特征分析](python/code_092) | ✔️code_093 | [对象检测-LBP特征分析](python/code_093/opencv_093.py) | ✔️code_094 | [ORB 特征关键点检测](python/code_094) | ✏️code_095 | [ORB 特征描述子匹配](python/code_095) | ✔️code_096 | [多种描述子匹配方法](python/code_096) | ✏️code_097 | [基于描述子匹配的已知对象定位](python/code_097) | ✏️code_098 | [SIFT 特征关键点检测](python/code_097) | ✔️code_099 | [SIFT 特征描述子匹配](python/code_097) | ✔️code_100 | [HOG 行人检测](python/code_100/opencv_100.py) | ✔️code_101 | [HOG 多尺度检测](python/code_101/opencv_101.py) | ✏️code_102 | [HOG 提取描述子](python/code_102/opencv_102.py) | ✔️code_103 | [HOG 使用描述子生成样本数据](python/code_103/opencv_103.py) | ✔️code_104 | [(检测案例)-HOG+SVM 训练](python/code_104/opencv_104.py) | ✔️code_105 | [(检测案例)-HOG+SVM 预测](python/code_105/opencv_105.py) | ✔️code_106 | [AKAZE 特征与描述子](python/code_106) | ✔️code_107 | [Brisk 特征与描述子](python/code_107) | ✔️code_108 | [GFTT关键点检测](python/code_108) | ✔️code_109 | [BLOB 特征分析](python/code_109) | ✔️