Progress on different distance algorithms (current broken due to sketchy python)
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README.md
16
README.md
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@ -6,3 +6,19 @@ Includes Python application for prototyping and C++ application for
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building a self-contained binary.
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building a self-contained binary.
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```bash
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python pallete.py ~/Desktop/Ohuhu_50_pallete_card_printed_scaled.png
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```
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```bash
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python separator.py ~/Desktop/look.png 6 ./palletes/printed_pallete.json ./
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```
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### TODO
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* Fix (?) BGR and RGB closest color match
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* Order colors before matching
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* Match brightest color to white and skip
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* Re-assemble image with patched colors
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* Scripts for running `stipple_gen` on each layer
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38
py/common.py
38
py/common.py
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@ -1,5 +1,6 @@
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import cv2
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import cv2
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import numpy as np
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import numpy as np
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from math import sqrt
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def convert_color (color, color_space_a, color_space_b) :
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def convert_color (color, color_space_a, color_space_b) :
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pixel = np.zeros([1, 1, 3], dtype=np.uint8)
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pixel = np.zeros([1, 1, 3], dtype=np.uint8)
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@ -62,6 +63,34 @@ def closest_color (colors, color):
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smallest_distance = colors[index_of_smallest]
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smallest_distance = colors[index_of_smallest]
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return smallest_distance[0]
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return smallest_distance[0]
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# Works for RGB, BGR, LAB and HSV(?)
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def closest_color_pythagorean (colors, color) :
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mDist = float('inf')
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mIdx = -1
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for idx, comp in enumerate(colors) :
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dist = pythagorean_distance(comp[0], comp[1], comp[2], color[0], color[1], color[2])
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if dist < mDist :
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mDist = dist
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mIds = idx
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return color[mIdx], mDist
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def closest_color_weighted_pythagorean (colors, color, space) :
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mDist = float('inf')
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mIdx = -1
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for idx, comp in enumerate(colors) :
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if space == 'BGR' :
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dist = weighed_pythagorean_distance(comp[2], comp[1], comp[0], color[2], color[1], color[1])
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elif space == 'RGB' :
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dist = weighed_pythagorean_distance(comp[0], comp[1], comp[2], color[0], color[1], color[2])
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else :
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raise Exception(f'closest_color_weighted_pythagorean does not support color space {space}')
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break
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if dist < mDist :
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mDist = dist
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mIds = idx
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return color[mIdx], mDist
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def create_colored_image (width, height, bgr_color):
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def create_colored_image (width, height, bgr_color):
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image = np.zeros((height, width, 3), np.uint8)
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image = np.zeros((height, width, 3), np.uint8)
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image[:] = bgr_color
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image[:] = bgr_color
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@ -79,3 +108,12 @@ def list_match (a, b) :
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if a[i] != b[i] :
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if a[i] != b[i] :
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return False
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return False
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return True
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return True
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def pythagorean_distance (r1, g1, b1, r2, g2, b2) :
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return sqrt(pow(r1-r2, 2) + pow(g1-g2, 2) + pow(b1-b2, 2))
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def weighted_pythagorean_distance (r1, g1, b1, r2, g2, b2) :
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R = 0.30
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G = 0.59
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B = 0.11
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return sqrt(pow((r1-r2) * R, 2) + pow((g1-g2) * G, 2) + pow((b1-b2) * B, 2))
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@ -1,7 +1,7 @@
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import cv2
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import cv2
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import numpy as np
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import numpy as np
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from pallete_schema import PalleteSchema
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from pallete_schema import PalleteSchema
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from common import convert_color, closest_color, create_colored_image, remove_from_list
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from common import convert_color, closest_color, create_colored_image, remove_from_list, closest_color_pythagorean, closest_color_weighted_pythagorean
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class ComparisonComparison:
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class ComparisonComparison:
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def __init__ (self) :
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def __init__ (self) :
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@ -39,7 +39,7 @@ class ComparisonComparison:
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for cc in comp_colors :
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for cc in comp_colors :
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cccompare = convert_color(cc, 'RGB', space)
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cccompare = convert_color(cc, 'RGB', space)
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print(cccompare)
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print(cccompare)
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closest = closest_color(colors, cccompare)
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closest = closest_color_pythagorean(colors, cccompare)
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print(closest)
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print(closest)
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colors = remove_from_list(colors, closest)
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colors = remove_from_list(colors, closest)
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