.

AUTHORS.rst

@@ -0,0 +1,5 @@
+AUTHORS
+---------
+Copyright © 2013 SVAKSHA, https://github.com/svaksha . AllRightsReserved.
+~~~~~~~~~~~~~~~~~~~~~~~~~
+

chAya/__init__.py

@@ -0,0 +1,3 @@
+__version__ = "13.8.dev"
+
+import diagonalGrid

chAya/diagonalGrid.py

@@ -0,0 +1,70 @@
+#!/usr/bin/env python3.3
+###############################################################################
+# Copyright © 2012-Now, SVAKSHA (https://github.com/svaksha) AllRightsReserved.
+# License: AGPLv3 License <http://www.gnu.org/licenses/agpl.html>
+# All copies must retain this permission notice with the copyright notice.
+###############################################################################
+
+import numpy
+import numpy as np
+from numpy import array, newaxis
+from PIL import Image
+import glob, sys
+import os, os.path
+
+
+def imageBuddha(image_path):
+    pix = Image.open(image_path)
+    pix.show()
+    img = pix.convert('L')
+    imcropd = img.crop([0,0,5,5])
+    imcropd.size
+    return img
+
+
+def convFloat(imgcropd):
+    # converting the greyscale image into a floating type
+    # shades of gray are coded as unsigned one-byte integer values with 0
+    # corresponding to black and 255 corresponding to white.
+    bmap = np.array(imgcropd, dtype=float)
+    df = bmap/256       # converts my image to floating types between 0 to 1
+    print (df)
+    return df
+
+
+def diagonalMatrix(df, dist=5):
+    """
+    The distance can be increased or decreased for finer or coarser edge
+    detection.
+    """
+    topLeftbotRight = abs(np.subtract(df[0:-dist,0:-dist] , df[dist:,dist:]))
+    print ("topLeftbotRight", topLeftbotRight)
+    botLefttopRight = abs(np.subtract(df[0:-dist,dist:] , df[dist:,0:-dist]))
+    print ("botLefttopRight", botLefttopRight)
+    diaDD = topLeftbotRight + botLefttopRight
+    return diaDD
+
+
+if __name__ == '__main__':
+    # build paths to import modules via pathya.py
+    full_path = os.path.realpath(__file__)
+    dir_path, prog_file = os.path.split(full_path)
+    parent_root = os.path.abspath(os.path.join(dir_path, os.pardir))
+    label_daemon = 'daemon'
+    pathya_path = os.path.join(parent_root, label_daemon)
+    sys.path.append(pathya_path)
+    import pathya
+
+    for count in range(3):
+        label_images = 'images'
+        images_path = os.path.join(parent_root, label_images)
+        image_path = pathya.imagePath(images_path, count)
+        img = imageBuddha(image_path)
+        df = convFloat(img)
+        diaMatriX = diagonalMatrix(df, 5)
+        # diagonal computation output of a (n-1) X (n-1) matrix:
+        print ("Output of the diagonal MatriX", diaMatriX)
+
+        diaMatriX = Image.fromarray(diaMatriX*256)
+        diaMatriX.show()
+

chAya/pxl_2connectGrid.py

@@ -0,0 +1,108 @@
+#!/usr/bin/env python3.3
+###############################################################################
+# Copyright © 2012-Now, SVAKSHA (https://github.com/svaksha) AllRightsReserved.
+# License: AGPLv3 License <http://www.gnu.org/licenses/agpl.html>
+# All copies must retain this Copyright notice and this permission notice.
+###############################################################################
+
+import numpy
+import numpy as np
+from numpy import array, newaxis
+import Image
+import glob, sys
+import os, os.path
+import shutil as sh
+import pathya
+img_path = pathya.filePath()
+
+def imageBuddha(image_path):
+    pix = Image.open(image_path)
+    pix.show()
+    img = pix.convert('L')
+    imcropd = img.crop([0,0,5,5])
+    imcropd.size
+    return img
+
+def convFloat(imgcropd):
+    # converting the greyscale image into a floating type
+    # shades of gray are coded as unsigned one-byte integer values with 0
+    # corresponding to black and 255 corresponding to white.
+    bmap = np.array(imgcropd, dtype=float)
+    df = bmap/256       # converts my image to floating types between 0 to 1
+    print (df)
+    return df
+
+def diffRow():
+    newRow = np.array(imgcropd[:-1, :-1])    #last elem, lastElem
+    for row in range(len(newRow)):
+        for col in range(len(newRow)):
+            newRow[row][col] = imgcropd[row][col] - imgcropd[row+1][col]
+            continue
+    print ("printing newRow")
+    print (newRow)
+# post computation output of a (n-1) X (n-1) matrix for each ROW
+diffRow()
+print (np.shape(diffRow))
+
+def diffCol():
+    for row in range(len(a)):
+        for column in range(len(a[0])): #start from 0-th position
+            answer[row][column]=a[row][column]-a[row][column+1 ]
+
+    newCol = np.array(imgcropd[:-1, :-1]) #last elem, lastElem
+    for row in range(len(newCol)):
+        for col in range(len(newCol)):
+            newCol[row][col] = imgcropd[row][col] - imgcropd[row][col+1]
+            continue
+    print ("printing newCol")
+    print (newCol)
+diffCol() #post computation output of a (n-1) X (n-1) matrix for each COLUMN
+print (np.shape(diffRow[:,newaxis] + diffCol))
+
+
+def gridRowCol(diffCol, diffRow):
+    """
+    For a two-connected matrix, I'm adding the values of the two new arrays,
+    diffRow and diffCol to get a new grid, which will be the edge detected Picture.
+    """
+    print "111"
+    #gridRC = np.concatenate([diffRow(), diffCol()])
+    #gridRC = np.add(diffCol(), diffRow())
+    #return gridRC
+    for row in newRow():     #return the number of items in a sequence.
+        #newRow = np.array(bmfloat[:-1, :-1])
+        for col in diffRow(): #
+            # newaxis index operator inserts a new axis into a,
+            # making it a two-dimensional 4x1 array.
+            gridRC = diffRow[:,newaxis] + diffCol[:,newaxis]
+            continue
+        print ("gridRC", gridRC)
+
+gridRowCol(diffCol, diffRow)
+for index in np.ndindex(3, 2, 1):
+    print (index)
+
+
+if __name__ == '__main__':
+    # build paths to import modules via pathya.py
+    full_path = os.path.realpath(__file__)
+    dir_path, prog_file = os.path.split(full_path)
+    parent_root = os.path.abspath(os.path.join(dir_path, os.pardir))
+    label_daemon = 'daemon'
+    pathya_path = os.path.join(parent_root, label_daemon)
+    sys.path.append(pathya_path)
+    import pathya
+
+    for count in range(3):
+        label_images = 'images'
+        images_path = os.path.join(parent_root, label_images)
+        image_path = pathya.imagePath(images_path, count)
+        img = imageBuddha(image_path)
+        df = convFloat(img)
+        diaMatriX = diagonalMatrix(df, 5)
+        # diagonal computation output of a (n-1) X (n-1) matrix:
+        print ("Output of the diagonal MatriX", diaMatriX)
+
+        diaMatriX = Image.fromarray(diaMatriX*256)
+        diaMatriX.show()
+

ci/__init__.py

@@ -1,3 +1,3 @@
 __version__ = "13.8.dev"
 
-# from .diagonalEdge import *
+# from .diagonalGrid import *

daemon/pathya.py

@@ -2,13 +2,13 @@
 ###############################################################################
 # Copyright © 2012-Now, SVAKSHA (https://github.com/svaksha) AllRightsReserved.
 # License: AGPLv3 License <http://www.gnu.org/licenses/agpl.html>
-# All copies must retain this Copyright notice and this permission notice.
+# All copies must retain this permission notice with the copyright notice.
 ###############################################################################
 
 import glob, sys
 import os, os.path
 
-images_list = ['P1010214.png',
+image_list = ['P1010214.png',
               'P1010218.png',
               'P1010221.png',
               ];
@@ -23,7 +23,9 @@ def dirPath():
 
 
 def imagePath(dir_path, count):
-    image_dir = images_list[count]
+    image_dir = image_list[count]
     image_filepath = os.path.join(dir_path, image_dir)
     print (image_filepath)
     return image_filepath
+
+

setup.py

@@ -1,24 +1,44 @@
+#!/usr/bin/env python3.3
+
 from setuptools import setup, find_packages
-import os
+import os, sys
+import shutil
+import warnings
+
 import chaya
 
 def read():
     with open('README.rst') as f:
         return f.readfile()
 
-setup(name = 'chaya',
-      version = chaya.__version__,
-      author = 'SVAKSHA',
+PKGNAME = 'chaya',
+VERSION=chaya.__version__,
+AUTHOR = "SVAKSHA",
+AUTHOR_EMAIL = "svaksha@gmail.com",
+URL = 'https://github.com/svaksha/chaya',
+DESCRIPTION ='Learning computer vision, edge detection',
+LONG_DESCRIPTION=open('README.rst').read()
+PACKAGES=['chaya'],
+PACKAGE_DATA={'chaya': ['LICENSE.rst',
+                              'AUTHORS.rst',
+                              'MANIFEST.in',
+                              'README.rst',
+                              ]}
+
+setup(name=PKGNAME,
+      version=VERSION,
+      maintainer=AUTHOR,
       author_email = 'svaksha@gmail.com',
       url = 'https://github.com/svaksha/chaya',
       description ='Learn computer vision, edge detection',
       long_description = open('README.rst').read()
-      packages = ['chaya'],
-      package_data = {'chaya': ['LICENSE.rst',
-                                'AUTHORS.rst',
-                                'MANIFEST.in',
-                                'README.rst',
-                                ]},
+      license = ('AGPL'),
+      packages=['chaya'],
+      package_data={'chaya': ['LICENSE.rst',
+                              'AUTHORS.rst',
+                              'MANIFEST.in',
+                              'README.rst',
+                              ]},
       include_package_data = True,
       install_requires = ['Cython==0.19.1',
                           'Pillow==2.1.0',
@@ -31,6 +51,7 @@ def read():
                      'Topic :: Graphics :: Computer Vision',
                      ],
       packages = ['chaya',
+                  'chaya.chAya',
                   'chaya.tests',
                   ],   #TODO
       )