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@@ -1,5 +1,15 @@
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-from pylab import imread, figure, show, imshow
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+from pylab import imread, figure, show, imshow, zeros, axis
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+def to_grayscale(image):
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+ """Turn a RGB image to a grayscale image."""
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+ result = zeros(image.shape[:2])
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+
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+ for x in xrange(len(image)):
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+ for y in xrange(len(image[0])):
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+ result[x][y] = image[x][y].sum() / 3
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+
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+ return result
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+
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# Divide the examined window to cells (e.g. 16x16 pixels for each cell).
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# For each pixel in a cell, compare the pixel to each of its 8 neighbors
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@@ -18,7 +28,9 @@ from pylab import imread, figure, show, imshow
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# cells. This gives the feature vector for the window.
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image = imread("../images/test.png")
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+image = to_grayscale(image)
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figure()
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-imshow(image)
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+imshow(image, cmap='gray')
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+axis('off')
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show()
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