transformer workflow implemented

Author: mbucchi

.appveyor.yml

@@ -1,6 +1,7 @@
 branches:
   only:
     - master
+    - dev
 
 environment:
   global:
@@ -18,11 +19,15 @@ install:
 build_script:
   - cibuildwheel --output-dir dist
 
-deploy_script:
-  - python -m pip install twine
-  # Remove for deployment to official PyPi repo
-  - "python -m twine upload --repository-url https://test.pypi.org/legacy/ --skip-existing dist\\*.whl"
-
 artifacts:
   - path: "dist\\*.whl"
-    name: Wheels
+    name: Wheels
+
+for:
+  - branches:
+      only:
+        - master
+    deploy_script:
+      - python -m pip install twine
+      # Remove for deployment to official PyPi repo
+      - "python -m twine upload --repository-url https://test.pypi.org/legacy/ --skip-existing dist\\*.whl"

.travis.yml

@@ -1,26 +1,34 @@
+branches:
+  only:
+    - master
+    - dev
 env:
   global:
-  - CIBW_SKIP="cp27-* cp33-* cp34-* cp35-* *-manylinux1_i686"
-  - CIBW_BEFORE_BUILD="python -m pip install -r requirements.txt"
-  - TWINE_USERNAME=mabucchi
-  - secure: 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
+    - CIBW_SKIP="cp27-* cp33-* cp34-* cp35-* *-manylinux1_i686"
+    - CIBW_BEFORE_BUILD="python -m pip install -r requirements.txt"
+    - TWINE_USERNAME=mabucchi
+    - secure: JvT4s6k9r7goUhxxeSwAjPHA/EQVKwYo838a6Ze4wm/SSuG2OLYqU29NTyJnQmJmU7ksF1YT5QK5NWqEvkGTjvmpiixbnVowd4iwcmFLgbu/AG+WxVbk0WW+f1yufjY49nq8RY4VeAhl+Rt10m1blbzFjUADxXVDVir8ujQzvCUj5rikQndjc3DzJPVZKuNK5NOPfx/K9TXXTgGmCdRGoSHkKbQRCGz/H7AOgxCtsSH3dfRBGgpqhDodMjsPmgWvPntxO74N2L9I/1gH1yYEDKo+k14BkJBdKFy12dUTE1NXjTeqrN1MrrDju94qCBdH1jHnI7CkZyslfmeA3QD4IiRc6YbQQgPqgjg8Db1dnJL0rpwH5A4dn+1Zl/z3IJZuAHUGC+1Rsqtv8O1zdV7b0+9SOdMq9U6VgT3TJs0+qYbZqpFvHD6UidfJMQ2XsQjbNg6r0gABd5TkLrZ6yFRjLDn3+WOCj6wFC9f3Cq5iZrH+kpGpS1Qu2BLPDWjN3IunAsg+NJ26xrInkTA4naS31tSJzppJTdIuICCNIV8HZgZyMs7vt1Z1zLBCSNbHr56TRho7av/uM2USu9CQH7h6CBt9cU5FqFZ31S2CbwEi6AuoA/zgI64J3aUMSFiXVM6RfKm1Qo1hdaej3LbvidBRTZNVrzsYcnRBclaQTYXsYGM=
 matrix:
   include:
-  - language: python
-    dist: xenial
-    sudo: required
-    python: '3.7'
-    services:
-    - docker
-    install:
-    - pip install --upgrade cibuildwheel twine
-    - touch .cibuildwheel
-  - os: osx
-    language: generic
-    install:
-    - brew upgrade python
-    - sudo python3 -m pip install --upgrade cibuildwheel twine
-    - touch .cibuildwheel
+    - language: python
+      dist: xenial
+      sudo: required
+      python: "3.7"
+      services:
+        - docker
+      install:
+        - pip install --upgrade cibuildwheel twine
+        - touch .cibuildwheel
+    - os: osx
+      language: generic
+      install:
+        - brew upgrade python
+        - sudo python3 -m pip install --upgrade cibuildwheel twine
+        - touch .cibuildwheel
+
 script:
-- cibuildwheel --output-dir dist
-- twine upload --repository-url https://test.pypi.org/legacy/ --skip-existing dist/*.whl
+  - cibuildwheel --output-dir dist
+  - |
+    if [ "$TRAVIS_BRANCH" == "master" ]; then 
+      twine upload --repository-url https://test.pypi.org/legacy/ --skip-existing dist/*.whl
+    fi

README.md

@@ -1,18 +1,34 @@
-pybalu
-============
+# pybalu
 
 [![Build Status](https://travis-ci.com/mbucchi/pybalu.svg?branch=master)](https://travis-ci.com/mbucchi/pybalu)
 [![Build status](https://ci.appveyor.com/api/projects/status/f010n1dwwyf5f2rk/branch/master?svg=true)](https://ci.appveyor.com/project/mbucchi/pybalu/branch/master)
 
-
 Python implementation for Balu, a computer vision, pattern recognition and image processing library. Originally implemented in matlab by Domingo Mery.
 
-## Setup for development and testing
+## Installing pybalu
 
 Python 3.6 or higher is required to use this package. In order to install, simply run
+
 ```bash
 $ pip install --index-url https://test.pypi.org/simple/ pybalu
 ```
 
+## Development and contributing
+
+If you would like to contribute:
+
+- Fork the repo
+- Create a new branch called `feature/<feature-desc>` or `fix/<fix-desc>` depending on the nature of your contribution
+- Perform a pull request and wait for your contribution to be accepted or rejected
+
+Possible and useful contributions:
+
+- Tests
+- More feature extraction, analysis and transformation funcitons
+- Fixes
+- Documentation
+- Examples
+
 ## Documentation
-_TODO_
+
+_TODO_

pybalu/IO/__init__.py

@@ -5,9 +5,8 @@
 from . import feature_selection
 from . import feature_transformation
 from . import img_processing
-from . import IO
+from . import io
 from . import misc
 from . import performance_eval
-from . import utils
 
-__version__ = '0.2.0'
+__version__ = '0.2.1'

pybalu/__init__.py

@@ -0,0 +1,75 @@
+from sklearn.base import BaseEstimator, TransformerMixin
+import tqdm
+from sklearn.pipeline import make_pipeline
+
+__all__ = ['FeatureExtractor', 'ImageProcessor']
+
+
+class FeatureExtractor(BaseEstimator, TransformerMixin):
+    """Base class for all feature extractors in PyBalu
+
+
+    Notes (from sklearn.base.BaseEstimator)
+    -----
+    All estimators should specify all the parameters that can be set
+    at the class level in their ``__init__`` as explicit keyword
+    arguments (no ``*args`` or ``**kwargs``).
+    """
+
+    def __init__(self):
+        self.show = False
+
+    def _get_iterator(self, X, *, desc=None):
+        if self.show:
+            if desc is not None:
+                desc = f'Extracting Features({desc})'
+            else:
+                desc = 'Extracting Features'
+            return tqdm.tqdm(X, desc=desc, total=len(X), unit_scale=True)
+        return iter(X)
+
+    def fit(self, X, y=None):
+        """Do nothing and return the estimator unchanged
+        This method is just there to implement the usual API and hence
+        work in pipelines.
+        Parameters
+        ----------
+        X : array-like, shape [n_samples, n_features]
+            Training data.
+        """
+        return self
+
+
+class ImageProcessor(BaseEstimator, TransformerMixin):
+    """Base class for all image transformers in PyBalu
+
+
+    Notes (from sklearn.base.BaseEstimator)
+    -----
+    All estimators should specify all the parameters that can be set
+    at the class level in their ``__init__`` as explicit keyword
+    arguments (no ``*args`` or ``**kwargs``).
+    """
+
+    def __init__(self):
+        self.show = False
+
+    def _get_iterator(self, X, *, desc=None):
+        if self.show:
+            if desc is not None:
+                desc = f'Processing Images({desc})'
+            else:
+                desc = 'Processing Images'
+            return tqdm.tqdm(X, desc=desc, total=len(X), unit_scale=True)
+        return iter(X)
+
+    def fit(self, X, y=None):
+        """Do nothing and return the estimator unchanged
+        This method is just there to implement the usual API and hence
+        work in pipelines.
+        Parameters
+        ----------
+        X : array-like, shape [n_samples, n_features]
+            Training data.
+        """
+        return self

pybalu/base.py

@@ -2,6 +2,7 @@
 
 import numpy as np
 
+
 def structure(classifier, *, train_data=None, test_data=None, train_classes=None, initialize=True,
               fit_method='fit', predict_method='predict', classifier_opts=None):
     '''\
@@ -57,7 +58,9 @@ def structure(classifier, *, train_data=None, test_data=None, train_classes=None
     '''
 
     if not hasattr(classifier, fit_method) or not hasattr(classifier, predict_method):
-        raise ValueError("`classifier` must define methods `fit` and `predict` in order to be considered a valid classifier")
+        raise ValueError(
+            f"`classifier` must define methods `{fit_method}` and `{predict_method}` in order to be considered a valid classifier"
+        )
 
     classifier_opts = classifier_opts or dict()
 
@@ -68,13 +71,15 @@ def structure(classifier, *, train_data=None, test_data=None, train_classes=None
 
     if train_data is not None:
         if train_classes is None:
-            raise ValueError("`train_features` given but no `classification` given to train classifier")
-        
+            raise ValueError(
+                "`train_features` given but no `classification` given to train classifier"
+            )
+
         classifier_instance = classifier(**classifier_opts)
         getattr(classifier_instance, fit_method)(train_data, train_classes)
 
     if test_data is not None:
         prediction = getattr(classifier_instance, predict_method)(test_data)
         return np.array(prediction), classifier_instance
-    
-    return np.empty(0), classifier_instance
+
+    return np.empty(0), classifier_instance

pybalu/classification/_structure.py

@@ -2,7 +2,6 @@
 from ._all import *
 from ._basic_geo import *
 from ._basic_int import *
-from ._feature_extractor import *
 from ._flusser import *
 from ._fourier import *
 from ._fourier_des import *
@@ -13,4 +12,4 @@
 from ._hog import *
 from ._hugeo import *
 from ._huint import *
-from ._lbp import *
+from ._lbp import *

pybalu/feature_extraction/__init__.py

@@ -1,4 +1,12 @@
-__all__ = ['all']
+import numpy as np
+from pybalu.base import FeatureExtractor
+__all__ = ['all', 'AllExtractor']
+
 
 def all(image):
-    return image.flatten()
+    return image.flatten()
+
+
+class AllExtractor(FeatureExtractor):
+    def transform(self, X):
+        return np.array([all(x) for x in self._get_iterator(X)])