TeaCrab
1b0d0d29ce
The way equalize_clahe() function's parameters being auto generated based on image size was resulting in errors. Issue seems to be some kind of dimensional mismatch which was required to be the same by the kornia function. Reverting back to a working method. Plus some minor fixes.
44 lines
1.2 KiB
Python
44 lines
1.2 KiB
Python
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from math import ceil, floor, log
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debouncer = set()
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def po2(value, fill=False) -> int:
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func = ceil if fill else floor
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return pow(2, func(log(value)/log(2)))
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def pixel_approx(primary, secondary, total=1024, ratio=1.0,
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threshold=0.125, _inc=1024, calculate_inc=True) -> tuple:
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global debouncer
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if calculate_inc:
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debouncer.clear()
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total *= total
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ratio = secondary / primary
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primary = po2(primary)
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secondary = primary * ratio
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_inc = primary / 4
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elif total * 3 > int(primary * secondary) > total * 0.333:
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if abs(_inc) >= 64: _inc /= 2
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# print(f"Action: {_inc}")
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count = round(primary) * round(secondary)
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# print(round(primary), round(secondary), count)
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_recurse = False
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if count > total:
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_inc = abs(_inc) * -1
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elif count < total:
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_inc = abs(_inc)
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if not (total * (1+threshold) > count > total * (1-threshold)) and total not in debouncer:
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debouncer.add(count)
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_recurse = True
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if _recurse:
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primary += _inc
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secondary = primary * ratio
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primary, secondary = pixel_approx(primary, secondary, total, ratio, threshold, _inc, False)
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return (int(primary), int(secondary))
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