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[feat, wip]: FixRects.connect_broken
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assets/fix_rects/broken.jpg
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assets/fix_rects/broken.jpg
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assets/fix_rects/broken_masked.jpg
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assets/fix_rects/broken_masked.jpg
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assets/fix_rects/broken_rects.jpg
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assets/fix_rects/broken_rects.jpg
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@ -1,5 +1,6 @@
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import math
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from typing import Tuple
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from copy import deepcopy
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from typing import Optional, Sequence, Tuple
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import cv2
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import numpy as np
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@ -10,12 +11,63 @@ from .mask import mask_byd, mask_ftr, mask_prs, mask_pst
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from .types import Mat, cv2_ml_KNearest
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__all__ = [
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"FixRects",
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"preprocess_hog",
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"ocr_digits_by_contour_get_samples",
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"ocr_digits_by_contour_knn",
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]
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class FixRects:
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@staticmethod
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def connect_broken(
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rects: Sequence[Tuple[int, int, int, int]],
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img_width: int,
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img_height: int,
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tolerance: Optional[int] = None,
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):
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# for a "broken" digit, please refer to
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# /assets/fix_rects/broken_masked.jpg
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# the larger "5" in the image is a "broken" digit
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if tolerance is None:
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tolerance = math.ceil(img_width * 0.08)
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new_rects = []
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consumed_rects = []
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for rect in rects:
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x, y, w, h = rect
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# grab those small rects
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if not img_height * 0.1 <= h <= img_height * 0.6:
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continue
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group = []
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# see if there's other rects that have near left & right borders
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for other_rect in rects:
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if rect == other_rect:
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continue
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ox, oy, ow, oh = other_rect
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if abs(x - ox) < tolerance and abs((x + w) - (ox + ow)) < tolerance:
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group.append(other_rect)
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if group:
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group.append(rect)
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consumed_rects.extend(group)
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# calculate the new rect
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new_x = min(r[0] for r in group)
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new_y = min(r[1] for r in group)
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new_right = max(r[0] + r[2] for r in group)
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new_bottom = max(r[1] + r[3] for r in group)
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new_w = new_right - new_x
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new_h = new_bottom - new_y
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new_rects.append((new_x, new_y, new_w, new_h))
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return_rects = deepcopy(rects)
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return_rects = [r for r in return_rects if r not in consumed_rects]
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return_rects.extend(new_rects)
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return return_rects
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def resize_fill_sqaure(img, target: int = 20):
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h, w = img.shape[:2]
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if h > w:
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