1 """Image filters module.
3 All filters return a filtered copy of the image, the original image is
7 from PIL import Image, ImageFilter
12 def color_enhance(image):
13 """Stretch all color channels to their full range."""
14 image_l = image.load()
15 min_r, min_g, min_b = 999, 999, 999
16 max_r, max_g, max_b = -1, -1, -1
18 for x in xrange(image.size[0]):
19 for y in xrange(image.size[1]):
20 min_r = min(min_r, image_l[x, y][0])
21 max_r = max(max_r, image_l[x, y][0])
22 min_g = min(min_g, image_l[x, y][1])
23 max_g = max(max_g, image_l[x, y][1])
24 min_b = min(min_b, image_l[x, y][2])
25 max_b = max(max_b, image_l[x, y][2])
27 new_image = Image.new('RGB', image.size)
28 new_image_l = new_image.load()
29 for x in xrange(image.size[0]):
30 for y in xrange(image.size[1]):
31 r, g, b = image_l[x, y]
32 r = (r - min_r) * 255 / (max_r - min_r)
33 g = (g - min_g) * 255 / (max_g - min_g)
34 b = (b - min_b) * 255 / (max_b - min_b)
35 new_image_l[x, y] = (r, g, b)
39 def edge_detection(image):
40 """Edge detection (on BW images)."""
41 new_image = image.filter(ImageFilter.GaussianBlur())
42 # GaussianBlur is undocumented class, it might not work in future versions
44 new_image = Image.fromstring('L', image.size,
45 pcf.edge(image.size, image.tostring()))
49 """Peak filter (on BW images)."""
50 image_l = image.load()
51 new_image = Image.new('L', image.size)
52 new_image_l = new_image.load()
53 for x in range(2, image.size[0] - 2):
54 for y in range(2, image.size[1] - 2):
57 for b in range(y - 2, y + 3)])
58 for a in range(x - 2, x + 3)])
59 + (17 * image_l[x, y]))
64 new_image_l[x, y] = pix
67 def high_pass(image, height):
68 """High pass filter (on BW images)."""
69 image_l = image.load()
70 new_image = Image.new('L', image.size)
71 new_image_l = new_image.load()
73 for x in xrange(image.size[0]):
74 for y in xrange(image.size[1]):
75 if image_l[x, y] < height:
78 new_image_l[x, y] = image_l[x, y]
82 def components(image, diameter):
85 image_l = image.load()
86 new_image_l = np.zeros(image.size, dtype=np.int)
92 for y in xrange(1, image.size[1] - 1):
93 for x in xrange(1, image.size[0] - 1):
96 s.add(new_image_l[x - 1, y - 1])
97 s.add(new_image_l[x, y - 1])
98 s.add(new_image_l[x + 1, y - 1])
99 s.add(new_image_l[x - 1, y])
101 components.append(set())
102 new_image_l[x, y] = comp_counter
103 components[comp_counter].add((x, y))
108 new_image_l[x, y] = c
109 components[c].add((x, y))
112 c1, c2 = s.pop(), s.pop()
113 components[c2].add((x, y))
114 for (x1, y1) in components[c2]:
115 new_image_l[x1, y1] = c1
116 components[c1] = components[c1] | components[c2]
117 components[c2] = None
119 for y in xrange(2, image.size[1] - 2):
120 for x in xrange(2, image.size[0] - 2):
124 for (a, b) in [(a,b) for a in range(x - 2, x + 3)
125 for b in range(y - 2, y + 1)]:
126 if not (b == y and a >= x):
127 s.add(new_image_l[a, b])
130 components.append(set())
131 new_image_l[x, y] = comp_counter
132 components[comp_counter].add((x, y))
137 new_image_l[x, y] = c
139 components[c].add((x, y))
140 except AttributeError:
146 components[c1].add((x, y))
147 new_image_l[x, y] = c1
149 for (x1, y1) in components[c2]:
150 new_image_l[x1, y1] = c1
151 components[c1] = components[c1] | components[c2]
152 components[c2] = None
157 new_image = Image.new('L', image.size)
158 new_image_l = new_image.load()
160 for component in components:
165 for (x, y) in component:
169 new_image_l[int(round(float(x_c)/c)), int(round(float(y_c)/c))] = 255