def find_nearest_floss(block):
# This way searches full blown sum of squared error for best color
#error = [block.color_error(floss['rgb']) for floss in dmc_flosses.flosses]
# This way does a jenky averaged color search
average_point = [average(coord) for coord in zip(*block.points)]
error = [sum_squared_error(average_point, Pixel.FromRGB(floss['rgb']).get_Lab()) for floss in dmc_flosses.flosses]
best_error = min(error)
idx = error.index(best_error)
return dmc_flosses.flosses[idx]
def find_nearest_floss(region_point):
error = [
sum_squared_error(region_point,
Pixel.FromRGB(floss['rgb']).get_Lab())
for floss in dmc_flosses.flosses
]
best_error = min(error)
idx = error.index(best_error)
return dmc_flosses.flosses[idx]
def floss_image(image, color_map):
x, y = image.size
pixel_data = image.load()
flossed_image = Image.new('RGB', (x, y), None)
flossed_pixels = flossed_image.load()
for r in range(x):
for c in range(y):
value = Pixel.FromRGB(pixel_data[r,c]).get_Lab()
possible_flosses = [floss for block, floss in color_map.iteritems() if value in block]
# FIXME: I may be doing something weird because I seem to have pixels that can fall into multiple blocks
#assert len(possible_flosses) == 1
flossed_pixels[r,c] = possible_flosses[0]['rgb']
# save debug image
flossed_image.save(os.path.join(options.output_dir, 'floss.bmp'), 'BMP')
return flossed_image
def flossit(resized_image, median_cut_options):
global options
options = median_cut_options
assert options.num_colors > 0
if not options.strategy:
options.strategy = 'random'
elif options.strategy not in seed_strategies.keys():
print '[Lloyd\'s] Unknown seeding strategy "%s" -- falling back to random seeds!' % options.strategy
options.strategy = 'random'
print '[Lloyd\'s] Enumerating the pixel data in the resized image...'
all_points = [
Pixel.FromRGB(rgb).get_Lab() for rgb in get_image_points(resized_image)
]
print '[Lloyd\'s] Setting initial seed regions...'
regions = seed_strategies[options.strategy](all_points, options.num_colors)
region_kd_tree = kdtree(regions)
print '[Lloyd\'s] Finding initial point assignments...'
assignments = [
closest_region(point, regions, region_kd_tree) for point in all_points
]
iteration = 1
last_assignments = []
while last_assignments != assignments:
print '[Lloyd\'s] Iterating regions (%s)...' % iteration
populated_regions = [k for k, g in groupby(sorted(assignments))]
regions = [
central_point(
compress(all_points,
[assignment == region for assignment in assignments]))
for region in populated_regions
]
region_kd_tree = kdtree(regions)
iteration += 1
last_assignments = assignments
assignments = [
closest_region(point, regions, region_kd_tree)
for point in all_points
]
print '[Lloyd\'s] Assigning floss colors to regions...'
colors = [find_nearest_floss(region) for region in regions]
print '[Lloyd\'s] Flossing image...'
return floss_image(resized_image, regions, colors)
def flossit(resized_image, median_cut_options):
global options
options = median_cut_options
assert options.num_colors > 0
if not options.strategy:
options.strategy = 'size'
elif options.strategy not in division_strategies.keys():
print '[Median Cut] Unknown division strategy "%s" -- falling back to size-based cuts!' % options.strategy
options.strategy = 'size'
print '[Median Cut] Enumerating the pixel data in the resized image...'
all_points = [Pixel.FromRGB(rgb).get_Lab() for rgb in get_image_points(resized_image)]
print '[Median Cut] Breaking image into %s discrete color groups...' % options.num_colors
color_blocks = subdivide(all_points)
print '[Median Cut] Finding best matching floss colors for each region...'
color_map = map_blocks_to_floss(color_blocks)
print '[Median Cut] Rendering image using appropriate floss colors...'
return floss_image(resized_image, color_map)
def floss_image(image, region_points, region_colors):
x, y = image.size
pixel_data = image.load()
flossed_image = Image.new('RGB', (x, y), None)
flossed_pixels = flossed_image.load()
for r in range(x):
for c in range(y):
pixel = Pixel.FromRGB(pixel_data[r, c]).get_Lab()
error = [
sum_squared_error(pixel, region_point)
for region_point in region_points
]
best_error = min(error)
idx = error.index(best_error)
flossed_pixels[r, c] = region_colors[idx]['rgb']
# save debug image
flossed_image.save(os.path.join(options.output_dir, 'floss.bmp'), 'BMP')
return flossed_image
