I have to face many difficult situations when I configure OpenCV on Windows 7 using Visual Studio 2012, install Python to run the script crop_face.py, and create test data to detect and recognize my faces. So I decided to write out my results from beginning to end to detect and recognize my faces. I hope this report will be useful for beginners to study OpenCV.
The content of this report is to guide in a step by step manner to enable the reader to configure and run OpenCV on Windows. I do not focus on explaining the meaning of OpenCV library. You can get more details about OpenCV here.
I have copied all the source code for this report from this article and refer to the guide to configure OpenCV on Windows from many other websites.
In this report, I used OpenCV 2.4.5 on Windows 7 using Visual Studio 2012.
Step 1: Download OpenCV 2.4.5
You can download OpenCV2.4.5 on Windows from here.
You extract OpenCV-2.4.5 with the specified path. For example:
Step 2: Create a New C++ Project in Visual Studio 2012
Open Visual Studio 2012.
Select File -> New -> Project
Create empty project Win32 Application in Visual C++.
Create a new file *.cpp. I named it facerec_video.cpp.
Copy the source code src/facerec_video.cpp from here.
Please change this source code:
Step 3: Configure OpenCV in Visual Studio 2012
3.1. Configuration Properties -> C/C++ -> General -> Additional Include Directories
Add your OpenCV path to Additional Include Directories:
3.2. Linker -> General
3.3 Linker -> Input
Please press F7 -> Build successful (If your project has an error, please review from step 1 to step 3 carefully.)
Step 4: Setup Windows Environment
Control Panel\All Control Panel Items\System
Click ‘Advanced system settings’
- Click ‘Environment Variables’ in Tab Advanced
- Click New… in ‘User variables for Administrator’
- Variable name:
- Variable value: D:\01_baotd1\00_OpenSource\OpenCV_245\build
- Select Path in ‘System Variables’ and click Edit…
- Add to the end: ;%OPENCV_DIR%\x86\vc11\bin
If you cannot run the OpenCV, you must restart your computer or your Visual Studio.
Step 5: Install Python to run script crop_face.py
In this report, I used Python and library image as follows:
Step 6: Create Test Data to OpenCV Recognize Your Faces
In order for OpenCV to recognize your faces, you need to create your faces. You should prepare one or more of your pictures with extensions *.jpg (OpenCV can detect and recognize more image types. In my report, I used image *.jpg) and placed them in one folder. In order to run script crop_face.py correctly, you must provide the position of left eye and right eye. I used
Paint to get the position of my left eye and right eye. You move your mouse to the left eye position, the status bar of
Paint will display the position (x,y) of left eye. Please note this position. And do the same process for right eye and other images. Please take a look at my example below:
I updated the script crop_face.py for creating image easily. I attached the updated script in this report. Here is the example to run crop_face.py on Windows 7:
Step 7: Create csv.ext File
Here is the example of csv.ext file. When you crop your faces successfully, you should put all your crop faces to one folder. Please notice that the csv.ext file must contain at least two objects.
Step 8: Run and Enjoy
In order to easily run, I modified the original source code as follows (I do not like to run the application with command line):
F5 and enjoy.
This is the first report that I created on CodeProject. I hope beginners will get some benefit from this report.