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FFI bindings to libccv

Project description

## Build

Clone both `ccv` and `py-ccv`:

mkdir ccv_build
cd ccv_build
git clone
git clone

Patch `ccv` so it can be compiled as a dynamic lib, and compile it:

cd ccv/lib
patch -p2 < ../../py-ccv/dynlib.patch

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 install

## Build only this wrapper

If you already have `` 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 `` 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 --help
Usage: [options] filename...

-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

##### 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


## 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.

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