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OpenSource Computer Vision
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OpenSource Computer Vision, more commonly known as OpenCV, is a more advanced image manipulation and processing software than PIL. It has been implemented in several
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languages and is widely used.
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OpenSource Computer Vision, more commonly known as OpenCV, is a more advanced
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image manipulation and processing software than PIL. It has been implemented
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in several languages and is widely used.
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Installation
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~~~~~~~~~~~~
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In Python, image processing using OpenCV is implemented using the ``cv2`` and ``NumPy`` modules.
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The `installation instructions for OpenCV <http://docs.opencv.org/2.4/doc/tutorials/introduction/table_of_content_introduction/table_of_content_introduction.html#table-of-content-introduction>`_ should guide you through configuring the project for yourself.
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In Python, image processing using OpenCV is implemented using the ``cv2`` and
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``NumPy`` modules. The `installation instructions for OpenCV
should guide you through configuring the project for yourself.
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NumPy can be downloaded from the Python Package Index(PyPI):
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.. code-block:: console
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$ pip install numpy
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$ pip install numpy
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Example
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.. code-block:: python
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from cv2 import*
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import numpy as np
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import numpy as np
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#Read Image
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img = cv2.imread('testimg.jpg')
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#Display Image
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#Applying Grayscale filter to image
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gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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#Saving filtered image to new file
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cv2.imwrite('graytest.jpg',gray)
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There are more Python-implemented examples of OpenCV in this `collection of tutorials <http://opencv-python-tutroals.readthedocs.org/en/latest/py_tutorials/py_tutorials.html>`_.
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#Saving filtered image to new file
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cv2.imwrite('graytest.jpg',gray)
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There are more Python-implemented examples of OpenCV in this `collection of
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