From af06691ca57a4484d904d4ddd11cbd32f332b6a3 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E7=8E=8B=E7=A3=8A?= <295628068@qq.com> Date: Mon, 21 May 2018 18:26:16 +0800 Subject: [PATCH] =?UTF-8?q?=E6=B7=BB=E5=8A=A0=E5=9B=BE=E7=89=87=E4=BF=AE?= =?UTF-8?q?=E5=A4=8D?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- README.md | 3 + doc/opencv/hsv.md | 36 +++++ doc/settingup.md | 276 +++++++++++++++++++-------------------- faceai/img/inpaint.png | Bin 0 -> 50709 bytes faceai/img/oldimg.png | Bin 0 -> 505021 bytes faceai/opencv/hsv.py | 2 - faceai/opencv/inpaint.py | 25 ++++ res/inpaint.png | Bin 0 -> 113415 bytes 8 files changed, 202 insertions(+), 140 deletions(-) create mode 100644 doc/opencv/hsv.md create mode 100644 faceai/img/inpaint.png create mode 100644 faceai/img/oldimg.png create mode 100644 faceai/opencv/inpaint.py create mode 100644 res/inpaint.png diff --git a/README.md b/README.md index 26bb050..699276a 100644 --- a/README.md +++ b/README.md @@ -7,6 +7,7 @@ 1. 性别识别 1. 表情识别(生气、厌恶、恐惧、开心、难过、惊喜、平静等七种情绪) 2. 视频对象提取 +3. 图片修复(适用去除水印) 3. 眼动追踪(待完善) 3. 换脸(待实现) @@ -52,6 +53,8 @@ 视频对象提取 +图片修复 + # 其他教程 # diff --git a/doc/opencv/hsv.md b/doc/opencv/hsv.md new file mode 100644 index 0000000..e9d986d --- /dev/null +++ b/doc/opencv/hsv.md @@ -0,0 +1,36 @@ +# 视频对象提取 # + + + +``` +import cv2 +import numpy as np + +cap = cv2.VideoCapture(0) + +while (1): + _, frame = cap.read() + hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) + + #在PS里用取色器的HSV + psHSV = [112, 89, 52] + diff = 40 #上下浮动值 + #因为PS的HSV(HSB)取值是:0~360、0~1、0~1,而OpenCV的HSV是:0~180、0~255、0~255,所以要对ps的hsv进行处理,H/2、SV*255 + lowerHSV = [(psHSV[0] - diff) / 2, (psHSV[1] - diff) * 255 / 100, + (psHSV[2] - diff) * 255 / 100] + upperHSV = [(psHSV[0] + diff) / 2, (psHSV[1] + diff) * 255 / 100, + (psHSV[2] + diff) * 255 / 100] + + mask = cv2.inRange(hsv, np.array(lowerHSV), np.array(upperHSV)) + + res = cv2.bitwise_and(frame, frame, mask=mask) + res = cv2.GaussianBlur(res, (5, 5), 1) + + cv2.imshow('frame', frame) + # cv2.imshow('mask', mask) + cv2.imshow('res', res) + if cv2.waitKey(1) & 0xFF == ord('q'): + break + +cv2.destroyAllWindows() +``` \ No newline at end of file diff --git a/doc/settingup.md b/doc/settingup.md index 3fe281f..33a9ca1 100644 --- a/doc/settingup.md +++ b/doc/settingup.md @@ -1,142 +1,142 @@ - # OpenCV环境搭建 # - - 本文将介绍OpenCV在Python3.x上的实现,分为Window版和Linux版。 - - ## Windows版环境搭建 ## - - > 系统环境:windows 10 + python 3.6 + OpenCV 3.4.1 - - - ### 一、安装python ### - - python的安装之前在[python自学笔记](https://github.com/vipstone/python)的项目中描述了,在这不做重复说明,有需要的朋友,点击查看:[python环境安装](https://github.com/vipstone/python/blob/master/%E5%BC%80%E5%8F%91%E7%8E%AF%E5%A2%83%E6%90%AD%E5%BB%BA.md) - - ### 二、安装numpy模块 ### - - 根据上文提示,现在我们已经正确安装了python和pip(安装和管理python包的工具),在正式安装OpenCV之前,首先我们要安装numpy模块。 - numpy:是一个定义了数值数组和矩阵类型和它们的基本运算的语言扩展,OpenCV引用了numpy模块,所以安装OpenCV之前必须安装numpy。 - - 本文安装python模块使用的是.whl文件安装的。 - - **whl文件是什么?** - - whl是一个python的压缩包,其中包含了py文件以及经过编译的pyd文件。 - - **whl安装命令** - > pip3 install 存放路径\xxx.whl - - 回到主题,我们是要安装numpy模块的。 - - 第一步:先去网站下载对应的numpy版本,下载地址:https://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy 本人是64为系统python3.6所以对应的最新版本是:numpy‑1.14.2+mkl‑cp36‑cp36m‑win_amd64.whl,点击下载到D:根目录。 - - 百度云链接:https://pan.baidu.com/s/10RefansrC4_0zsNehjyKTg - - 提取密码:gua3 - - - 第2步:启动命令窗体运行 - > pip3 install d:\numpy‑1.14.2+mkl‑cp36‑cp36m‑win_amd64.whl - - 命令窗体显示: - - Processing d:\numpy-1.14.2+mkl-cp36-cp36m-win_amd64.whl - - Installing collected packages: numpy - - Successfully installed numpy-1.14.2+mkl - - 说明已经安装成功。 - - - ### 三、安装OpenCV ### - 同样安装OpenCV模块和numpy方式类似。 - - 第1步:实现去网站下载OpenCV对于的.whl版本压缩包,网址:https://www.lfd.uci.edu/~gohlke/pythonlibs/#opencv 本人下载的版本是:opencv_python‑3.4.1‑cp36‑cp36m‑win_amd64.whl 64位系统对应python3.6的,下载到d盘根目录。 - - 百度云链接:https://pan.baidu.com/s/10RefansrC4_0zsNehjyKTg - - 提取密码:gua3 - - 第2步:启动命令窗体运行 - > pip3 install d:\opencv_python-3.4.1-cp36-cp36m-win_amd64.whl - - 窗体显示: - - Processing d:\opencv_python-3.4.1-cp36-cp36m-win_amd64.whl - - Installing collected packages: opencv-python - - Successfully installed opencv-python-3.4.1 - - 说明安装成功。 - - ### 四、运行OpenCV ### - 到此,我们的环境配置已经完成了,终于到了可以撸代码的时刻了,想想还有一点小激动呢。 - - - ``` python - import cv2 - - print(cv2.__version__) - - # 输出:3.4.1 - ``` - 上面我们简单的打印了OpenCV的版本号,如果能正常输出不报错,说明我们已经把OpenCV的python环境搭建ok了。 - - 什么?感觉还不过瘾,那就来撸一张图,用OpenCV把它展示出来,代码如下: - ``` python - import cv2 - - filepath = "img/meinv.png" - img = cv2.imread(filepath) - cv2.namedWindow('Image') - cv2.imshow('Image', img) - cv2.waitKey(0) - cv2.destroyAllWindows() - ``` - - 展示效果如图:![正在加载图片](https://raw.githubusercontent.com/vipstone/opencvLab/master/res/show-meinv.png) - - - - ---------- - ## Linux版环境搭建 ## - - >Ubuntu 18.04 - >Python 3.6.5 - >Pip 10.0.1 - >Numpy 1.14.3 - >OpenCV 3.4.0 - - Ubuntu有一个好处就是内置Python环境,不需要像Windows那样在为Python环境折腾了,但要注意的是Ubuntu本身自带的apt-get和安装的pip的数据源是国外的,所以使用起来都很慢,一定要把apt-get和pip的数据源更换成国内的,请移步到:[《Ubuntu apt-get和pip源更换》](http://www.cnblogs.com/vipstone/p/9038023.html) - - ### 正式安装 ### - 根据上面的提示,你已经配置好了开发环境,现在需要正式安装了,当然Ubuntu的安装也比Windows简单很多,只需要使用pip安装包,安装相应的模块即可。 - - #### 安装Numpy #### - 使用命令:pip3 install numpy - - 使用命令:python3,进入python脚本执行环境,输入代码查看numpy是否安装成功,以及numpy的安装版本: - ``` - import numpy - - numpy.__version__ - ``` - 正常输入版本号,证明已经安装成功。 - - 如图:![](http://icdn.apigo.cn/numpy-setup-success.png) - - #### 安装OpenCV #### - OpenCV的安装在Ubuntu和numpy相似,使用命令: - >pip3 install opencv-python - - 使用命令:python3,进入python脚本执行环境,输入代码查看OpenCV版本: - ``` - import cv2 +# OpenCV环境搭建 # + +本文将介绍OpenCV在Python3.x上的实现,分为Window版和Linux版。 + +## Windows版环境搭建 ## + +> 系统环境:windows 10 + python 3.6 + OpenCV 3.4.1 + + +### 一、安装python ### + +python的安装之前在[python自学笔记](https://github.com/vipstone/python)的项目中描述了,在这不做重复说明,有需要的朋友,点击查看:[python环境安装](https://github.com/vipstone/python/blob/master/%E5%BC%80%E5%8F%91%E7%8E%AF%E5%A2%83%E6%90%AD%E5%BB%BA.md) + +### 二、安装numpy模块 ### + +根据上文提示,现在我们已经正确安装了python和pip(安装和管理python包的工具),在正式安装OpenCV之前,首先我们要安装numpy模块。 +numpy:是一个定义了数值数组和矩阵类型和它们的基本运算的语言扩展,OpenCV引用了numpy模块,所以安装OpenCV之前必须安装numpy。 + +本文安装python模块使用的是.whl文件安装的。 + +**whl文件是什么?** + +whl是一个python的压缩包,其中包含了py文件以及经过编译的pyd文件。 + +**whl安装命令** +> pip3 install 存放路径\xxx.whl + +回到主题,我们是要安装numpy模块的。 + +第一步:先去网站下载对应的numpy版本,下载地址:https://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy 本人是64为系统python3.6所以对应的最新版本是:numpy‑1.14.2+mkl‑cp36‑cp36m‑win_amd64.whl,点击下载到D:根目录。 + +百度云链接:https://pan.baidu.com/s/10RefansrC4_0zsNehjyKTg + +提取密码:gua3 + + +第2步:启动命令窗体运行 +> pip3 install d:\numpy‑1.14.2+mkl‑cp36‑cp36m‑win_amd64.whl + +命令窗体显示: + +Processing d:\numpy-1.14.2+mkl-cp36-cp36m-win_amd64.whl + +Installing collected packages: numpy + +Successfully installed numpy-1.14.2+mkl + +说明已经安装成功。 + + +### 三、安装OpenCV ### +同样安装OpenCV模块和numpy方式类似。 + +第1步:实现去网站下载OpenCV对于的.whl版本压缩包,网址:https://www.lfd.uci.edu/~gohlke/pythonlibs/#opencv 本人下载的版本是:opencv_python‑3.4.1‑cp36‑cp36m‑win_amd64.whl 64位系统对应python3.6的,下载到d盘根目录。 + +百度云链接:https://pan.baidu.com/s/10RefansrC4_0zsNehjyKTg + +提取密码:gua3 + +第2步:启动命令窗体运行 +> pip3 install d:\opencv_python-3.4.1-cp36-cp36m-win_amd64.whl + +窗体显示: + +Processing d:\opencv_python-3.4.1-cp36-cp36m-win_amd64.whl + +Installing collected packages: opencv-python + +Successfully installed opencv-python-3.4.1 + +说明安装成功。 + +### 四、运行OpenCV ### +到此,我们的环境配置已经完成了,终于到了可以撸代码的时刻了,想想还有一点小激动呢。 + + +``` python +import cv2 + +print(cv2.__version__) + +# 输出:3.4.1 +``` +上面我们简单的打印了OpenCV的版本号,如果能正常输出不报错,说明我们已经把OpenCV的python环境搭建ok了。 + +什么?感觉还不过瘾,那就来撸一张图,用OpenCV把它展示出来,代码如下: +``` python +import cv2 + +filepath = "img/meinv.png" +img = cv2.imread(filepath) +cv2.namedWindow('Image') +cv2.imshow('Image', img) +cv2.waitKey(0) +cv2.destroyAllWindows() +``` + +展示效果如图:![正在加载图片](https://raw.githubusercontent.com/vipstone/opencvLab/master/res/show-meinv.png) + + - cv2.__version__ - ``` - 正常输入版本号,证明已经安装成功。 +---------- +## Linux版环境搭建 ## + +>Ubuntu 18.04 +>Python 3.6.5 +>Pip 10.0.1 +>Numpy 1.14.3 +>OpenCV 3.4.0 + +Ubuntu有一个好处就是内置Python环境,不需要像Windows那样在为Python环境折腾了,但要注意的是Ubuntu本身自带的apt-get和安装的pip的数据源是国外的,所以使用起来都很慢,一定要把apt-get和pip的数据源更换成国内的,请移步到:[《Ubuntu apt-get和pip源更换》](http://www.cnblogs.com/vipstone/p/9038023.html) + +### 正式安装 ### +根据上面的提示,你已经配置好了开发环境,现在需要正式安装了,当然Ubuntu的安装也比Windows简单很多,只需要使用pip安装包,安装相应的模块即可。 + +#### 安装Numpy #### +使用命令:pip3 install numpy + +使用命令:python3,进入python脚本执行环境,输入代码查看numpy是否安装成功,以及numpy的安装版本: +``` +import numpy + +numpy.__version__ +``` +正常输入版本号,证明已经安装成功。 + +如图:![](http://icdn.apigo.cn/numpy-setup-success.png) + +#### 安装OpenCV #### +OpenCV的安装在Ubuntu和numpy相似,使用命令: +>pip3 install opencv-python + +使用命令:python3,进入python脚本执行环境,输入代码查看OpenCV版本: +``` +import cv2 + +cv2.__version__ +``` +正常输入版本号,证明已经安装成功。 # 常见错误 # diff --git a/faceai/img/inpaint.png b/faceai/img/inpaint.png new file mode 100644 index 0000000000000000000000000000000000000000..ba1807754384cf47b37afabe888e0895a0adccf3 GIT binary patch literal 50709 zcmbTed010d*FGFasuigg>jb3MC>9hdpa>#IOEm_hkx2xBJc`JqrJ@nSkYlBaVkHs; 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+19,8 @@ upperHSV = [(psHSV[0] + diff) / 2, (psHSV[1] + diff) * 255 / 100, (psHSV[2] + diff) * 255 / 100] - # Threshold the HSV image to get only blue colors mask = cv2.inRange(hsv, np.array(lowerHSV), np.array(upperHSV)) - # Bitwise-AND mask and original image res = cv2.bitwise_and(frame, frame, mask=mask) res = cv2.GaussianBlur(res, (5, 5), 1) diff --git a/faceai/opencv/inpaint.py b/faceai/opencv/inpaint.py new file mode 100644 index 0000000..6a616cd --- /dev/null +++ b/faceai/opencv/inpaint.py @@ -0,0 +1,25 @@ +#coding=utf-8 +#图片修复 + +import cv2 +import numpy as np + +path = "img/inpaint.png" + +img = cv2.imread(path) +hight, width, depth = img.shape[0:3] + +thresh = cv2.inRange(img, np.array([240, 240, 240]), np.array([255, 255, 255])) +kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3)) +hi_mask = cv2.dilate(thresh, kernel, iterations=3) +specular = cv2.inpaint(img, hi_mask, 5, flags=cv2.INPAINT_TELEA) + +cv2.namedWindow("Image", 0) +cv2.resizeWindow("Image", int(width / 2), int(hight / 2)) +cv2.imshow("Image", img) + +cv2.namedWindow("newImage", 0) +cv2.resizeWindow("newImage", int(width / 2), int(hight / 2)) +cv2.imshow("newImage", specular) +cv2.waitKey(0) +cv2.destroyAllWindows() \ No newline at end of file diff --git a/res/inpaint.png b/res/inpaint.png new file mode 100644 index 0000000000000000000000000000000000000000..d419bf676da7200f7239cc503053ca03881912de GIT binary patch literal 113415 zcmXtDw1%NTC=_XNhXREbcXxO9V#VEE0u(Dy+=@HJrMSDhQzXG9NbulX`rUhf zWUaH#tekabvS+`~>~|+ZMM)YRl?W9M4h~&bMnVk^4*u%(WAzsBdMD2XT!V?yw_Axk{=lp`M7Ej6iHWhuxH&g0?OKi5%N!e zKEr$_y#sz?*U*?zoi z%&n{tF)}fM{21xW4)8PAP+9~;V>2o+`SP^As!Q_uQ)!eAXz}(ApSm7zH9|X}g0Z;Z zu7?h2l%@UaY&iw5=hf8>U^|J*WX_5=(j~B*r@uKfBZ;&_*+zPL`PF{A^y&+~O(VWt z*gm1K$Qb@o5#ETH4DegX)0*qljN|j3V~pU-TG8hD@o-6W--Xi$O`dIst^j*(KJ^A&gG(zm9ju|1r=B9D_lr=u2cr`ceKzIAa zvFglFRZ?2yS3hf->DC}(Rbk>?a|E!9!#Pyw2lkyWq>8W7joVrfl+SU5{i&7&CbuoI zEfJefle3EEP-cRwc@-scS{T!n`=qqDJ%56Xu37%y1Ev4F*_S>pimiPR3C=NWlh|LX 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