ImProc ass3: Added some debug lines.

improc/ass3/back_projection.py

@@ -3,33 +3,30 @@ from numpy import zeros
 from matplotlib.pyplot import imread, imshow, show
 from intersect import col2bin, domainIterator, colHist, histogramIntersect
 
-def D(image, radius, x, y):
-    """Get the average value of a circle around a pixel."""
-    disk_sum = 0.
-    pixels = 0
+def convolution(image, radius):
+    """Calculate the convolution of an image with a specified circle radius."""
+    c = zeros(image.shape)
     r_sq = radius ** 2
     w, h = image.shape[:2]
 
     # Loop to the square that surrounds the circle, and check if the pixel
     # is inside the disk
-    for dx in xrange(-radius, radius + 1):
-        for dy in xrange(-radius, radius + 1):
-            cx = x + dx
-            cy = y + dy
-
-            if cx >= 0 and cy >= 0 and cx < w and cy < h \
-                    and dx ** 2 + dy ** 2 < r_sq:
-                disk_sum += image[cx, cy]
-                pixels += 1
+    for x, y in domainIterator(image):
+        circle_sum = 0.
+        pixels = 0
 
-    return disk_sum / pixels if pixels else 0
+        for dx in xrange(-radius, radius + 1):
+            for dy in xrange(-radius, radius + 1):
+                cx = x + dx
+                cy = y + dy
 
-def convolution(image, radius):
-    """Calculate the convolution of an image with a specified disk radius."""
-    c = zeros(image.shape)
+                if cx >= 0 and cy >= 0 and cx < w and cy < h \
+                        and dx ** 2 + dy ** 2 < r_sq:
+                    circle_sum += image[cx, cy]
+                    pixels += 1
 
-    for x, y in domainIterator(image):
-        c[x, y] = D(image, radius, x, y)
+        if pixels:
+            c[x, y] = circle_sum / pixels
 
     return c
 
@@ -37,11 +34,11 @@ def hbp(image, environment, bins, model, radius):
     """Create the histogram back projection of two images."""
     # Create image histograms
     print 'Creating histograms...'
-    M = colHist(image, bins, 'rgb')
-    I = colHist(environment, bins, 'rgb')
+    M = colHist(image, bins, model)
+    I = colHist(environment, bins, model)
 
     # Create ratio histogram
-    R = zeros(I.shape)
+    R = zeros(bins)
 
     for c in domainIterator(R, 3):
         if (I[c] != 0).all():
@@ -49,8 +46,8 @@ def hbp(image, environment, bins, model, radius):
 
     # Create back projection
     print 'Creating back projection...'
-    b = zeros(environment.shape)
-    use = environment * bins
+    b = zeros(environment.shape[:2])
+    use = environment.astype(float) * bins
 
     if model == 'rgb':
         use /= 255
@@ -63,9 +60,10 @@ def hbp(image, environment, bins, model, radius):
 
     # Create convolution to create a peak value
     print 'Creating convolution...'
-    return convolution(b, radius)
+    return b
+    #return convolution(b, radius)
 
-def loc(x, y):
+def loc(image, color):
     pass
 
 def find_image(image, environment, bins, model, radius):
@@ -79,9 +77,18 @@ if __name__ == '__main__':
     waldo = imread('waldo.tiff')
     env = imread('waldo_env.tiff')
 
-    p = hbp(waldo, env, [8] * 3, 'rgb', 5)
+    b = hbp(waldo, env, [8] * 3, 'rgb', 8)
+    imshow(b, cmap='gray', origin='lower')
+    show()
+    import sys
+    sys.exit(0)
+    print 'Mapping projection over original image...'
+    result = env.copy()
+    for p in domainIterator(result):
+        result[p] *= b[p]
     print 'done'
-    imshow(p, cmap='gray')
+    imshow(result, origin='lower')
+    #imshow(b * env)
 
     # Draw a rectangle around the found center pixel
     #x, y = find_image(waldo, env, [8] * 3, 'rgb')

improc/ass3/intersect.py

@@ -4,7 +4,8 @@ from matplotlib.pyplot import imread
 
 def col2bin(color):
     """Get the histogram bin coordinates of a color."""
-    return tuple(map(lambda x: round(x - 1), color))
+    #return tuple(map(lambda x: round(x - 1), color))
+    return tuple(color.astype(int) - 1)
 
 def domainIterator(image, dim=2):
     """Pixel iterator for arrays of with 2 or 3 dimensions."""
@@ -20,11 +21,13 @@ def domainIterator(image, dim=2):
 
 def colHist(image, bins, model):
     """Create the color histogram of an image."""
-    h = zeros(tuple(bins))
+    h = zeros(bins)
     use = image.astype(float) * bins
 
     if model == 'rgb':
         use /= 255
+    elif model == 'rgba':
+        pass
     elif model == 'hsv':
         # TODO: implement HSV color model
         pass