imagecrop 0.0.3

Use OpenCV to extract image crops using homography and feature matching

=========
imagecrop
=========
Image extraction using a template. Uses homography and feature matching,
storing results in a SQLite database for faster reprocessing.

Usage
=====


.. code-block:: python

from image_extract.extract import Extracter
ex = Extracter()
ex.crop_images(image_directory, crop_template, file_extension[, match_points])

Successful crops are extracted to a directory called ``successful_crops``,
directly underneath ``image_directory``. Each template used creates a subdirectory, named after its
MD5:

.. code::

image_directory
- img1.jpg
- …
- imgn.jpg
- successful_crops
- 2a1bdab44c5e81af34f47f3395a3da7e
- img1_cropped.jpg
The optional ``match_points`` argument controls the number of matching points which must
be detected in order for a match to occur. It is set to 30 by default.

Summaries
---------
Call ``ex.summary(path)`` to see information on extracted crops for a given directory.

Deleting Extracted Crops
------------------------
Call ``ex.delete(path[, template_md5])`` to delete extracted crops for a given template.
If no template MD5 value is given, all extracted crops in that directory are removed.


Accuracy
========
For best results, the template image should be of the same (or similar) resolution
as the image from which the crop is to be extracted.