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@@ -2,6 +2,11 @@
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import csv
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from collections import defaultdict
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+# closeness coefficient
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+closeness = 2
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+# step size within RGB color space
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+step = 8
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+
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data = []
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with open("database.csv") as infile:
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for name, *nums in csv.reader(infile, delimiter=",", quotechar="'"):
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@@ -17,14 +22,13 @@ try:
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except:
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pass # file not found, assume no prior results
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-step = 8
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for r in range(0, 256, step):
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for g in range(0, 256, step):
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for b in range(0, 256, step):
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if (known := results.get((r, g, b), None)) is not None:
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counts[known[0]] += 1
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continue
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- best_score, best_name = min((x - r * yr - g * yg - b * yb, name) for name, x, yr, yg, yb in data)
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+ best_score, best_name = min((x - closeness * (r * yr - g * yg - b * yb), name) for name, x, yr, yg, yb in data)
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results[(r, g, b)] = (best_name, best_score)
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counts[best_name] += 1
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