improc ass4: Updated usage of gauss.py.

improc/ass4/gauss.py

@@ -8,12 +8,6 @@ from scipy.ndimage import convolve, convolve1d
 from time import time
 from sys import argv, exit
 
-def exit_with_usage():
-    """Print an error message with the program's usage and exit the program."""
-    print 'Usage: python %s timer METHOD [ REPEAT ] | diff SCALE' \
-            ' | der SCALE IORDER JORDER' % argv[0]
-    exit(1)
-
 def Gauss(s):
     """Sample a two-dimensional Gaussian function of scale s."""
     size = int(ceil(3 * s))
@@ -80,13 +74,34 @@ def plot_kernel(W, ax):
     ax.set_ylabel('x')
     ax.set_zlabel('g(x, y)')
 
+def exit_with_usage():
+    """Print an error message with the program's usage and exit the program."""
+    print 'Usage: python %s ( 2d SCALE | 1d SCALE IORDER JORDER' \
+          ' | timer METHOD [ REPEAT ] )' % argv[0]
+    exit(1)
+
 if __name__ == '__main__':
     if len(argv) < 2:
         exit_with_usage()
 
     F = imread('cameraman.png')
 
-    if argv[1] == 'der':
+    if argv[1] == '2d':
+        # Calculate and plot the convolution of the given scale
+        if len(argv) < 3:
+            exit_with_usage()
+
+        s = float(argv[2])
+        W = Gauss(s)
+        G = convolve(F, W, mode='nearest')
+
+        # Show the original image, kernel and convoluted image respectively
+        subplot(131)
+        imshow(F, cmap='gray')
+        plot_kernel(W, subplot(132, projection='3d'))
+        subplot(133)
+        imshow(G, cmap='gray')
+    elif argv[1] == '1d':
         if len(argv) < 5:
             exit_with_usage()
 
@@ -96,10 +111,12 @@ if __name__ == '__main__':
         iorder = int(argv[3])
         jorder = int(argv[4])
 
+        G = gD(F, s, iorder, jorder)
+
+        # Create a 2D weight function for plotting purposes only
         Fy = matrix([Gauss1(s, iorder)])
         Fx = Fy if jorder == iorder else matrix([Gauss1(s, jorder)])
         W = Fy.T * Fx
-        G = gD(F, s, iorder, jorder)
 
         # Show the original image, kernel and convoluted image respectively
         subplot(131)
@@ -140,20 +157,7 @@ if __name__ == '__main__':
         xlabel('s')
         ylabel('time (s)')
         plot(S, times, 'o-')
-    elif argv[1] == 'diff':
-        # Calculate and plot the convolution of the given scale
-        if len(argv) < 3:
+    else:
         exit_with_usage()
 
-        s = float(argv[2])
-        W = Gauss(s)
-        G = convolve(F, W, mode='nearest')
-
-        # Show the original image, kernel and convoluted image respectively
-        subplot(131)
-        imshow(F, cmap='gray')
-        plot_kernel(W, subplot(132, projection='3d'))
-        subplot(133)
-        imshow(G, cmap='gray')
-
     show()

improc/ass4/report/report.tex

@@ -84,14 +84,14 @@ because the sum of the filter should be equal to 1, it is divided by its own
 sum.
 
 The result of the \texttt{Gauss} function is shown in figure
-\ref{fig:gauss-diff}. The subplots respectively show the original image, the
+\ref{fig:gauss-2d}. The subplots respectively show the original image, the
 Gaussian kernel and the convolved image.
 
 \begin{figure}[H]
-	\label{fig:gauss-diff}
+	\label{fig:gauss-2d}
 	\hspace{-5cm}
-	\includegraphics[scale=.6]{gauss_diff_5.pdf}
-	\caption{The result of \texttt{python gauss.py diff 5}.}
+	\includegraphics[scale=.6]{gauss_2d_5.pdf}
+	\caption{The result of \texttt{python gauss.py 2d 5}.}
 \end{figure}
 
 \subsection{Measuring Performance}