Commit 118bbbea authored by aknecht2's avatar aknecht2

Name change & new repository

parents
Image Harvest Git Repo!
Full documentation can be found on the [Project Webiste](http://cropstressgenomics.org/phenomics.php)
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# -*- coding: utf-8 -*-
#
# Image Harvest documentation build configuration file, created by
# sphinx-quickstart on Thu Oct 30 10:00:12 2014.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All configuration values have a default; values that are commented out
# serve to show the default.
import sys
import os
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
#sys.path.insert(0, os.path.abspath('.'))
# -- General configuration ------------------------------------------------
# If your documentation needs a minimal Sphinx version, state it here.
#needs_sphinx = '1.0'
# Add any Sphinx extension module names here, as strings. They can be
# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
# ones.
extensions = [
'sphinx.ext.autodoc',
'sphinx.ext.doctest',
'sphinx.ext.intersphinx',
'sphinx.ext.todo',
'sphinx.ext.mathjax',
'sphinx.ext.viewcode',
]
#mathjax_path = "http://cdn.mathjax.org/mathjax/latest/MathJax.js"
# Add any paths that contain templates here, relative to this directory.
templates_path = ['_templates']
# The suffix of source filenames.
source_suffix = '.rst'
# The encoding of source files.
#source_encoding = 'utf-8-sig'
# The master toctree document.
master_doc = 'index'
# General information about the project.
project = u'Image Harvest'
copyright = u'2015, Avi Knecht'
# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the
# built documents.
#
# The short X.Y version.
version = '1.0'
# The full version, including alpha/beta/rc tags.
release = '1.0.1'
# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
#
# This is also used if you do content translation via gettext catalogs.
# Usually you set "language" from the command line for these cases.
language = None
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# non-false value, then it is used:
#today = ''
# Else, today_fmt is used as the format for a strftime call.
#today_fmt = '%B %d, %Y'
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# directories to ignore when looking for source files.
exclude_patterns = []
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# documents.
#default_role = None
# If true, '()' will be appended to :func: etc. cross-reference text.
#add_function_parentheses = True
# If true, the current module name will be prepended to all description
# unit titles (such as .. function::).
#add_module_names = True
# If true, sectionauthor and moduleauthor directives will be shown in the
# output. They are ignored by default.
#show_authors = False
# The name of the Pygments (syntax highlighting) style to use.
pygments_style = 'sphinx'
# A list of ignored prefixes for module index sorting.
#modindex_common_prefix = []
# If true, keep warnings as "system message" paragraphs in the built documents.
#keep_warnings = False
# -- Options for HTML output ----------------------------------------------
# The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes.
html_theme = 'default'
# Theme options are theme-specific and customize the look and feel of a theme
# further. For a list of options available for each theme, see the
# documentation.
html_theme_options = {
"stickysidebar": True,
}
# Add any paths that contain custom themes here, relative to this directory.
#html_theme_path = []
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# "<project> v<release> documentation".
#html_title = None
# A shorter title for the navigation bar. Default is the same as html_title.
#html_short_title = None
# The name of an image file (relative to this directory) to place at the top
# of the sidebar.
#html_logo = None
# The name of an image file (within the static path) to use as favicon of the
# docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32
# pixels large.
#html_favicon = None
# Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css".
html_static_path = ['_static']
# Add any extra paths that contain custom files (such as robots.txt or
# .htaccess) here, relative to this directory. These files are copied
# directly to the root of the documentation.
#html_extra_path = []
# If not '', a 'Last updated on:' timestamp is inserted at every page bottom,
# using the given strftime format.
#html_last_updated_fmt = '%b %d, %Y'
# If true, SmartyPants will be used to convert quotes and dashes to
# typographically correct entities.
#html_use_smartypants = True
# Custom sidebar templates, maps document names to template names.
#html_sidebars = {}
# Additional templates that should be rendered to pages, maps page names to
# template names.
#html_additional_pages = {}
# If false, no module index is generated.
#html_domain_indices = True
# If false, no index is generated.
#html_use_index = True
# If true, the index is split into individual pages for each letter.
#html_split_index = False
# If true, links to the reST sources are added to the pages.
#html_show_sourcelink = True
# If true, "Created using Sphinx" is shown in the HTML footer. Default is True.
#html_show_sphinx = True
# If true, "(C) Copyright ..." is shown in the HTML footer. Default is True.
#html_show_copyright = True
# If true, an OpenSearch description file will be output, and all pages will
# contain a <link> tag referring to it. The value of this option must be the
# base URL from which the finished HTML is served.
#html_use_opensearch = ''
# This is the file name suffix for HTML files (e.g. ".xhtml").
#html_file_suffix = None
# Language to be used for generating the HTML full-text search index.
# Sphinx supports the following languages:
# 'da', 'de', 'en', 'es', 'fi', 'fr', 'hu', 'it', 'ja'
# 'nl', 'no', 'pt', 'ro', 'ru', 'sv', 'tr'
#html_search_language = 'en'
# A dictionary with options for the search language support, empty by default.
# Now only 'ja' uses this config value
#html_search_options = {'type': 'default'}
# The name of a javascript file (relative to the configuration directory) that
# implements a search results scorer. If empty, the default will be used.
#html_search_scorer = 'scorer.js'
# Output file base name for HTML help builder.
htmlhelp_basename = 'Image Harvestdoc'
# -- Options for LaTeX output ---------------------------------------------
latex_elements = {
# The paper size ('letterpaper' or 'a4paper').
#'papersize': 'letterpaper',
# The font size ('10pt', '11pt' or '12pt').
#'pointsize': '10pt',
# Additional stuff for the LaTeX preamble.
#'preamble': '',
# Latex figure (float) alignment
#'figure_align': 'htbp',
}
# Grouping the document tree into LaTeX files. List of tuples
# (source start file, target name, title,
# author, documentclass [howto, manual, or own class]).
latex_documents = [
('index', 'Image Harvest.tex', u'Image Harvest Documentation',
u'Avi Knecht', 'manual'),
]
# The name of an image file (relative to this directory) to place at the top of
# the title page.
#latex_logo = None
# For "manual" documents, if this is true, then toplevel headings are parts,
# not chapters.
#latex_use_parts = False
# If true, show page references after internal links.
#latex_show_pagerefs = False
# If true, show URL addresses after external links.
#latex_show_urls = False
# Documents to append as an appendix to all manuals.
#latex_appendices = []
# If false, no module index is generated.
#latex_domain_indices = True
# -- Options for manual page output ---------------------------------------
# One entry per manual page. List of tuples
# (source start file, name, description, authors, manual section).
man_pages = [
('index', 'ih', u'Image Harvest Documentation',
[u'Avi Knecht'], 1)
]
# If true, show URL addresses after external links.
#man_show_urls = False
# -- Options for Texinfo output -------------------------------------------
# Grouping the document tree into Texinfo files. List of tuples
# (source start file, target name, title, author,
# dir menu entry, description, category)
texinfo_documents = [
('index', 'Image Harvest', u'Image Harvest Documentation',
u'Avi Knecht', 'Image Harvest', 'One line description of project.',
'Miscellaneous'),
]
# Documents to append as an appendix to all manuals.
#texinfo_appendices = []
# If false, no module index is generated.
#texinfo_domain_indices = True
# How to display URL addresses: 'footnote', 'no', or 'inline'.
#texinfo_show_urls = 'footnote'
# If true, do not generate a @detailmenu in the "Top" node's menu.
#texinfo_no_detailmenu = False
# Example configuration for intersphinx: refer to the Python standard library.
intersphinx_mapping = {'http://docs.python.org/': None}
Core Processing Example #1
===========================
This section will detail a shorter script that provides details on how to get started with
script form image processing. The script will detail how to use several core functions
to load, save, and show images.
Python Script
-----------------------
:download:`Download Script <../../examples/scripts/core1/core1.py>`
:download:`Download Image <../../examples/scripts/core1/base.png>`
.. code-block:: python
import ih.imgproc
plant = ih.imgproc.Image("/path/to/your/image")
plant.save("base")
plant.show("base")
plant.write("base.png")
plant.convertColor("bgr", "gray")
plant.save("gray")
plant.show("gray")
plant.write("gray.png")
plant.threshold(50)
plant.save("thresh50")
plant.show("thresh50")
plant.restore("gray")
plant.threshold(75)
plant.save("thresh75")
plant.show("thresh75")
plant.restore("gray")
plant.threshold(100)
plant.save("thresh100")
plant.show("thresh100")
plant.restore("gray")
plant.wait()
plant.restore("thresh50")
plant.write("thresh50.png")
This script shows how to get started with ih. Let's talk about it block by block:
.. code-block:: python
import ih.imgproc
plant = ih.imgproc.Image("/path/to/your/image")
These two lines setup your image. The first line imports a module, which is simply
a grouping of related in code. In this case, we import the 'imgproc' module, which
is a grouping of functions related to image processing. This module contains
all of ih's image processing functionality, and as a result, is the code we want to import
to process images. The second line creates an Image object named 'plant'.
Object Oriented Programming (OOP) can be a hard concept to understand at first.
In a simplistic form, objects are like nouns, and the methods we perform on the objects
are like verbs. Our Image object has certain properties that make it that type of object,
just like plants have properties that define them. This line accomplishes translating
the actual image into a form understandable by the code. The 'plant' object now has
properties that define it, and actions (methods) we can perform on it. The rest of the script
deals specifically with the methods we can perform on our image objects.
.. code-block:: python
plant.save("base")
plant.show("base")
plant.write("base.png")
These three lines use three separate methods on our plant object, :py:meth:`~ih.imgproc.Image.save`,
:py:meth:`~ih.imgproc.Image.show`, and :py:meth:`~ih.imgproc.Image.write`. Each of these
methods performs exactly what its named -- the save method saves the image for future use, the show method
displays the image, and the write method writes the image to a file. Each method has an argument
passed into it, determining the name to be used in each case. Calling plant.save("base") saves the image
with the name base, plant.show("base") shows the image with the window title base, and plant.write("base.png")
writes the image to a file named base.png. Here's what our base image looks like:
.. image:: ../../examples/scripts/core1/base.png
:align: center
.. code-block:: python
plant.convertColor("bgr", "gray")
plant.save("gray")
plant.show("gray")
plant.write("gray.png")
The :py:meth:`~ih.imgproc.Image.convertColor` method performs a color spectrum shift, changing our image from a color image i.e. "bgr"
to a gray scale image i.e. "gray". It should be noted, that all methods overwrite the current image -- which is way the save / restore
functionality is so important. Additionally, converting an image to gray scale from color is an important non-linear shift.
A color image is called "bgr" because of the three colors in the image, blue, green, and red. Each pixel has a value for
each of these colors, or channels. Converting to gray condenses the image to a single channel -- intensity.
This means that you **cannot** use :py:meth:`~ih.imgproc.Image.convertColor` to restore color to a gray scale image.
Although we do not use it in this example, the reason for saving the base image is to restore color in a future step.
The last three lines of this block of code perform the exact same function as the previous block, only using
different names for saving, showing, and writing. Here's what our gray scale image looks like:
.. image:: ../../examples/scripts/core1/gray.png
:align: center
.. code-block:: python
plant.threshold(50)
plant.save("thresh50")
plant.show("thresh50")
plant.restore("gray")
Now that we have a gray scale image, we perform a :py:meth:`~ih.imgproc.Image.threshold` on it. This simply
checks the value of each pixels intensity, and checks to see if it beats the cutoff we specify. In this case,
if the pixel has an intensity greater than 50, we keep it. Intensity values range from 0 to 255. The
:py:meth:`~ih.imgproc.Image.save` and :py:meth:`~ih.imgproc.Image.show` methods should be familiar,
but the fourth line contains a new method, :py:meth:`~ih.imgproc.Image.restore`. This method restores
the image to a previously saved image. In the previous block we saved our gray scale image under the name 'gray'.
Here, we simply restore that image after thresholding. The purpose of this is to compare multiple threshold values.
We restore the gray image at the end of each thresholding block to use the same image for thresholding. Here's the
result of thresholding by 50:
.. image:: ../../examples/scripts/core1/thresh50.png
:align: center
.. code-block:: python
plant.threshold(75)
plant.save("thresh75")
plant.show("thresh75")
plant.restore("gray")
This block is identical to the previous one, except we use a threshold value of 75 instead of 50,
and we rename our saved image and displayed image accordingly. Here's the result of thresholding
by 75:
.. image:: ../../examples/scripts/core1/thresh75.png
:align: center
.. code-block:: python
plant.threshold(100)
plant.save("thresh100")
plant.show("thresh100")
plant.restore("gray")
This block is identical to the previous one, except we use a threshold value of 100 instead of 75,
and we rename our saved image and displayed image accordingly. Here's the result of thresholding
by 100:
.. image:: ../../examples/scripts/core1/thresh100.png
:align: center
.. code-block:: python
plant.wait()
plant.restore("thresh50")
plant.write("thresh50.png")
The final block introduces a new method, :py:meth:`~ih.imgproc.Image.wait`. This method
simply halts execution until a key is pressed, then destroys all displayed windows. This
means that once this point in the script is hit, there should be 5 open windows, the base image,
the gray image, and one for each of the three thresholds. After execution is resumed,
we restore the threshold by 50, and write it to a file.
Command Line Script
-------------------
:download:`Download Script <../../examples/scripts/core1/core1.sh>`
:download:`Download Image <../../examples/scripts/core1/base.png>` (The image is identical to the one above)
.. code-block:: bash
#!/bin/bash
ih-convert-color --input "/path/to/your/image" --output "gray.png" --intype "bgr" --outtype "gray"
ih-threshold --input "gray.png" --output "thresh50.png" --thresh 50
ih-threshold --input "gray.png" --output "thresh75.png" --thresh 75
ih-threshold --input "gray.png" --output "thresh100.png" --thresh 100
This bash script performs the exact same workflow as the one above. Although not major, it is important to note the
differences between library and command line access. Command line access loads and writes an image at each step,
whereas library access loads once, and only writes when you tell it to. Additionally, script names are close to that
of the method, and all follow lower case format, with words seperated by dashes, and ih prependening all commands.
The most notable difference, is that a restore method is unnecessary with command-line input. We simply reuse the gray.png
file we wrote once. Additionally, there is no initial setup, you simply begin processing. The arguments pased into the
command line arguments match identically with the method arguments above.
This diff is collapsed.
This diff is collapsed.
..
REMEMBER TO UPDATE THE HIDDEN TOC TREE
AS SCRIPTS ARE ADDED TO THE EXAMPLES PAGE!!!
.. toctree::
:hidden:
ex_script_core1
ex_script_core2
ex_workflow_1.rst
Examples
========
Working through examples is a much better way of learning how to use ih than
reading implementation details. Additionally, creating workflows is a complicated
multi-step process. As such, many examples are detailed below, falling into
two broad categories. Script examples are those that deal with local computing.
Each script example includes a test image to download, as well as scripts
for library and command-line usage of ih. Workflow examples are those that
deal with distributed computing. They include template files for download,
but due to their nature, image sets are not available for download.
However, data sets are available through the OSG (Open Science Grid). Workflow examples
are very complex. Step by step instructions are provided, but it is **highly** recommended
to work through script examples before jumping into workflow examples.
Script Examples
---------------
There are many different script examples. Some are specific to functions,
others cover a broad range of functions. If you are getting started,
begin by working through the core processing examples. In particular,
if you are unfamiliar with Python, the first core processing script attempts
to explain some basic terms.
Core Processing
^^^^^^^^^^^^^^^
:doc:`Core Processing #1 <ex_script_core1>`, difficulty = easy.
:doc:`Core Processing #2 <ex_script_core2>`, difficulty = medium.
Workflow Examples
-----------------
:doc:`Workflow #1 <ex_workflow_1>`, difficulty = complex.
Welcome to Image Harvest documentation!
==============================================================
Link to GitHub: `ih <https://git.unl.edu/aknecht2/ih/>`_
Contents: