Commit aa0dbb3f authored by Taddeüs Kroes's avatar Taddeüs Kroes

ImProc ass3: Added some debug lines.

parent 45ce1a1b
......@@ -3,15 +3,18 @@ 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 x, y in domainIterator(image):
circle_sum = 0.
pixels = 0
for dx in xrange(-radius, radius + 1):
for dy in xrange(-radius, radius + 1):
cx = x + dx
......@@ -19,17 +22,11 @@ def D(image, radius, x, y):
if cx >= 0 and cy >= 0 and cx < w and cy < h \
and dx ** 2 + dy ** 2 < r_sq:
disk_sum += image[cx, cy]
circle_sum += image[cx, cy]
pixels += 1
return disk_sum / pixels if pixels else 0
def convolution(image, radius):
"""Calculate the convolution of an image with a specified disk radius."""
c = zeros(image.shape)
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')
......
......@@ -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
......
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