Metadata-Version: 1.1
Name: ccv
Version: 0.0.2
Summary: FFI bindings to libccv
Home-page: https://github.com/gpip/py-ccv
Author: Guilherme Polo
Author-email: gp@instaprint.me
License: UNKNOWN
Description: ## Build
        
        Clone both `ccv` and `py-ccv`:
        
        ```
        mkdir ccv_build
        cd ccv_build
        git clone https://github.com/liuliu/ccv
        git clone https://github.com/gpip/py-ccv
        ```
        
        Patch `ccv` so it can be compiled as a dynamic lib, and compile it:
        
        ```
        cd ccv/lib
        patch -p2 < ../../py-ccv/dynlib.patch
        ./configure
        make libccv.so
        ```
        
        Build and install the Python wrapper (`ARCHFLAGS` was used on a OSX build, adjust for your platform):
        
        ```
        cd ../../py-ccv
        ARCHFLAGS='-arch x86_64' INCDIR=../ccv/lib LIBDIR=../ccv/lib python setup.py install
        ```
        
        ## Build only this wrapper
        
        If you already have `libccv.so` then you might want to install directly via pip:
        
        ```
        LDFLAGS="-L$(pwd)/ccv/lib" CFLAGS="-I$(pwd)/ccv/lib" pip install ccv
        ```
        
        Remember to adjust the paths according to where `libccv.so` and `ccv.h` are installed in your system.
        
        
        ## Face Detection Usage
        
        (`DYLD_LIBRARY_PATH` was used on OSX, adjust it for your platform)
        
        ##### Face detection using SCD
        
        ```
        $ DYLD_LIBRARY_PATH=../ccv/lib python -m ccv.face_detect -c ../ccv/samples/face.sqlite3 img/lena.png
        img/lena.png Feature(x1=229, y1=216, x2=381, y2=368, confidence=5.014610767364502)
        ```
        
        ##### Face detection using BBF
        
        ```
        $ DYLD_LIBRARY_PATH=../ccv/lib python -m ccv.face_detect --bbf -c ../ccv/samples/face img/lena.png
        img/lena.png Feature(x1=230, y1=211, x2=384, y2=365, confidence=0.4947386682033539)
        ```
        
        ##### Help
        
        ```
        $ DYLD_LIBRARY_PATH=../ccv/lib python -m ccv.face_detect.py --help
        Usage: face_detect.py [options] filename...
        
        Options:
          -h, --help            show this help message and exit
          --bbf                 Use BBF detector
          --scd                 Use SCD detector
          -c CASCADE, --cascade=CASCADE
                                Path to cascade to read
          --quiet
        ```
        
        ##### Using face_detect as a library
        
        ```
        from ccv import face_detect
        
        names = ['img/lena.png']
        result = face_detect.main('scd', '../ccv/samples/face.sqlite3', False, *names)
        
        # face_detect.main is a generator which yields tuples of
        # (<filename>, [<list of face_detect.Feature>])
        for name, rects in result:
            print name, rects
        ```
        
        
        ##### Visualization
        
        This wrapper does not include an utility to draw the resulting rectangles, so the following example uses ImageMagick:
        
        ```
        $ convert img/lena.png -fill none -stroke blue -strokewidth 3 -draw "rectangle 229,216 381,368" result.png
        ```
        
        ![](http://i.imgur.com/yzcxwqk.png)
        
        
        ## Using the library
        
        ```
        import sys
        from ccv import ccv_read, ccv_write, sobel, lib
        
        # Read file passed.
        inp = ccv_read(sys.argv[1])
        # Apply Sobel.
        res = sobel(inp, lib.CCV_8U)
        # Save the result as "sobel.jpg"
        ccv_write(res, "sobel.jpg")
        ```
        
        Pointers returned by the higher level wrapper, `ccv`, are automatically freed.
        
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Topic :: Software Development :: Libraries
