Merge pull request #7 from Collonville/develop

Version 0.02

Author: Collonville

.coveragerc

@@ -0,0 +1,2 @@
+[run]
+source = ife

.github/ISSUE_TEMPLATE.md

@@ -0,0 +1,17 @@
+# Python byte code
+__pycache__/
+*.py[cod]
+
+# PyCharm
+.idea/
+
+.coverage
+
+# Poetry build file
+.dist/
+dist/
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json

.github/PULL_REQUEST_TEMPLATE.md

@@ -0,0 +1,31 @@
+language: python
+
+python:
+  - "3.6"
+  - "3.6-dev"
+  - "3.7"
+  - "3.7-dev"
+
+branches:
+  only:
+    - master
+    - develop
+
+before_install:
+  - pip install --upgrade pip
+  - pip install black
+  - pip install poetry
+
+before_script:
+  - flake8 ife --ignore E501
+  - black --diff ife
+  - mypy --strict-optional --disallow-untyped-defs --disallow-untyped-calls --ignore-missing-imports --no-incremental ife
+
+install:
+  - poetry install -v
+  - pip install coveralls
+script:
+  - coverage run -m unittest discover
+
+after_success:
+  - coverallspoetrey

.gitignore

@@ -0,0 +1,27 @@
+Copyright (c) 2019, Collonville. All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are
+met:
+
+   * Redistributions of source code must retain the above copyright
+     notice, this list of conditions and the following disclaimer.
+   * Redistributions in binary form must reproduce the above
+     copyright notice, this list of conditions and the following disclaimer
+     in the documentation and/or other materials provided with the
+     distribution.
+   * Neither the name of Collonville nor the names of its
+     contributors may be used to endorse or promote products derived from
+     this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE

.travis.yml

@@ -1,2 +1,103 @@
-# ImageFeatureExtractor
-Want a great image features??? Use IFE package!!!
+# Image Feature Extractor(IFE)
+[![Coverage Status](https://coveralls.io/repos/github/Collonville/ImageFeatureExtractor/badge.svg)](https://coveralls.io/github/Collonville/ImageFeatureExtractor)
+[![Build Status](https://travis-ci.org/Collonville/ImageFeatureExtractor.svg?branch=develop)](https://travis-ci.org/Collonville/ImageFeatureExtractor)
+[![Codacy Badge](https://api.codacy.com/project/badge/Grade/115c65043153459cbfc5026ea53be08d)](https://www.codacy.com/app/Collonville/ImageFeatureExtractor?utm_source=github.com&utm_medium=referral&utm_content=Collonville/ImageFeatureExtractor&utm_campaign=Badge_Grade)
+
+## What is this?
+`IFE` is a package to get an image feature more easily for Python. It contains many kinds of feature extract algorithms.
+
+## 1. Features
+### Color Moment
+-   Mean, Median, Variance, Skewness, Kurtosis of `RGB, HSV, HSL, CMY`
+
+## 2. Examples
+Import the basic image reader of IFE.
+```python
+from ife.io.io import ImageReader
+```
+
+### 2.1 Get Moment
+Add a image file path to `read_from_single_file()`. This will return basic features class.
+
+And now! You can get a RGB color moment feature from image!!
+```python
+>>> features = ImageReader.read_from_single_file("ife/data/small_rgb.jpg")
+>>> features.moment()
+array([[ 0.57745098,  0.52156863,  0.55980392],
+       [ 0.58823529,  0.48823529,  0.54901961],
+       [ 0.15220588,  0.12136101,  0.12380911],
+       [-0.01944425,  0.18416571,  0.04508015],
+       [-1.94196824, -1.55209335, -1.75586748]])
+```
+
+Also, you can get an `flatten vector, dictionary, or pandas`
+```python
+>>> features.moment(output_type="one_col")
+array([ 0.57745098,  0.52156863,  0.55980392,  0.58823529,  0.48823529,
+        0.54901961,  0.15220588,  0.12136101,  0.12380911, -0.01944425,
+        0.18416571,  0.04508015, -1.94196824, -1.55209335, -1.75586748])
+
+>>> features.moment(output_type="dict")
+defaultdict(<class 'dict'>, {'mean': {'R': 0.57745098039215681, 'G': 0.52156862745098043, 'B': 0.55980392156862746}, 'median': {'R': 0.58823529411764708, 'G': 0.48823529411764705, 'B': 0.5490196078431373}, 'var': {'R': 0.15220588235294119, 'G': 0.12136101499423299, 'B': 0.12380911188004615}, 'skew': {'R': -0.019444250980856902, 'G': 0.18416570783012232, 'B': 0.045080152334687214}, 'kurtosis': {'R': -1.9419682406751135, 'G': -1.5520933544103905, 'B': -1.7558674751807395}})
+
+>>> features.moment(output_type="pandas")
+       mean    median       var      skew  kurtosis
+R  0.577451  0.588235  0.152206 -0.019444 -1.941968
+G  0.521569  0.488235  0.121361  0.184166 -1.552093
+B  0.559804  0.549020  0.123809  0.045080 -1.755867
+```
+
+> No! I want a HSV Color space feature :(
+
+It can set another color space! Default will be RGB.
+```python
+>>> features.moment(output_type="one_col", color_space="CMY")
+array([ 0.42254902,  0.47843137,  0.44019608,  0.41176471,  0.51176471,
+        0.45098039,  0.15220588,  0.12136101,  0.12380911,  0.01944425,
+       -0.18416571, -0.04508015, -1.94196824, -1.55209335, -1.75586748])
+       
+>>> features.moment(output_type="dict", color_space="HSL")
+defaultdict(<class 'dict'>, {'mean': {'H': 0.50798329143793874, 'S': 0.52775831413836383, 'L': 0.61421568627450984}, 'median': {'H': 0.51915637553935423, 'S': 0.62898601603182969, 'L': 0.52156862745098043}, 'var': {'H': 0.13290200013401141, 'S': 0.10239897927552907, 'L': 0.051550124951941563}, 'skew': {'H': -0.078898095002588917, 'S': -0.83203104238315984, 'L': 1.0202366337483093}, 'kurtosis': {'H': -1.2599104562470791, 'S': -0.87111810912637022, 'L': -0.7502836585891588}})
+
+>>> features.moment(output_type="pandas", color_space="HSV")
+       mean    median       var      skew  kurtosis
+H  0.507983  0.519156  0.132902 -0.078898 -1.259910
+S  0.595236  0.749543  0.122723 -1.028366 -0.768867
+V  0.855882  0.864706  0.013867 -0.155656 -1.498179
+```
+
+## 3. Future work
+### IO
+-   Read from URL links
+-   Read from Base64
+-   Sliding window
+-   Video files
+
+### Color space
+-   CMYK
+-   CIE Lab
+-   XYZ
+
+### Features
+-   Value normalize
+-   Average Gradient
+-   LBP
+-   Histogram
+-   Color harmony
+-   Entropy
+-   Brightness measure
+-   Contrast measure
+-   Saturation measure
+-   Colourfulness
+-   Naturalness
+-   Color fidelity metric
+-   Saliency map
+-   Fisher vector
+-   VGG16, 19 layer feature
+-   and more...
+
+## 4. Author
+@Collonville
+
+## 5. Licence
+BSD-3-Clause