Main: including examples with various kernels

Homework_1/Problem1_4/MainConvolution.py

@@ -3,21 +3,40 @@
 import matplotlib.cm as cm #
 from scipy import misc
 
-import FnImConvolution
-
+from FnImConvolution import FnImConvol
 
 
 # Sample image
 TestImage1 = misc.lena()
 
-# Kernel: Sobel
-Kernel = 0.125 * np.array([ [-1.0, 0.0, 1.0], [-2.0, 0.0, 2.0], [-1.0, 0.0, 1.0]] )
+# Kernel
+Kernel_1 = 0.125 * np.array([ [-1.0, 0.0, 1.0], [-2.0, 0.0, 2.0], [-1.0, 0.0, 1.0]] ) # 3x3
+Kernel_2 = 1.0/256 * np.array( [ [1.0, 4.0, 6.0, 4.0, 1.0],
+                                [4.0, 16.0, 24.0, 16.0, 4.0],
+                                [6.0, 24.0, 36.0, 24.0, 6.0],
+                                [4.0, 16.0, 24.0, 16.0, 4.0],
+                                [1.0, 4.0, 6.0, 4.0, 1.0]])     # 5x5
+Kernel_3 = np.array( [  [-1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0],
+                        [-1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0],
+                        [-1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0],
+                        [-1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0],
+                        [-1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0],
+                        [-1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0],
+                        [-1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0],
+                        [-1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0] ] ) # 8x8
 
 # 2D Convolution
-print "Started!"
-Result = FnImConvolution.FnImConvol( TestImage1, Kernel, 'mirror' )
-print "Finished!"
+Result_1 = FnImConvol( TestImage1, Kernel_1, 'zero' )
+Result_2 = FnImConvol( TestImage1, Kernel_2, 'mirror' )
+Result_3 = FnImConvol( TestImage1, Kernel_3, 'wrap' )
 
 # Plot result
-plt.imshow(Result, cmap=cm.Greys_r)
+plt.figure('Kernel 1')
+plt.imshow(Result_1, cmap=cm.Greys_r)
+
+plt.figure('Kernel 2')
+plt.imshow(Result_2, cmap=cm.Greys_r)
+
+plt.figure('Kernel 3')
+plt.imshow(Result_3, cmap=cm.Greys_r)
 plt.show()