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contour matching for deskewed image: ensure matches for both sides

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Robert Sachunsky 2025-11-15 14:32:22 +01:00
parent 3c15c4f7d4
commit 5a778003fd
1 changed files with 33 additions and 9 deletions
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36
src/eynollah/eynollah.py
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@ -4461,7 +4461,7 @@ class Eynollah:
dists[i] = np.linalg.norm(centers[:, i:i + 1] - centers_d, axis=0)
corresp = np.zeros(dists.shape, dtype=bool)
# keep searching next-closest until at least one correspondence on each side
while not np.all(corresp.sum(axis=1)) and not np.all(corresp.sum(axis=0)):
while not np.all(corresp.sum(axis=1)) or not np.all(corresp.sum(axis=0)):
idx = np.nanargmin(dists)
i, j = np.unravel_index(idx, dists.shape)
dists[i, j] = np.nan
@ -4472,7 +4472,7 @@ class Eynollah:
# img1 = np.zeros(text_only_d.shape[:2], dtype=np.uint8)
# for i in range(len(contours_only_text_parent)):
# cv2.fillPoly(img1, pts=[contours_only_text_parent_d_ordered[i]], color=i + 1)
# plt.subplot(2, 2, 1, title="direct corresp contours")
# plt.subplot(1, 4, 1, title="direct corresp contours")
# plt.imshow(img1)
# img2 = np.zeros(text_only_d.shape[:2], dtype=np.uint8)
# join deskewed regions mapping to single original ones
@ -4485,13 +4485,13 @@ class Eynollah:
contour_d = polygon2contour(join_polygons(polygons_d))
contours_only_text_parent_d_ordered[i] = contour_d
# cv2.fillPoly(img2, pts=[contour_d], color=i + 1)
# plt.subplot(2, 2, 3, title="joined contours")
# plt.subplot(1, 4, 2, title="joined contours")
# plt.imshow(img2)
# img3 = np.zeros(text_only_d.shape[:2], dtype=np.uint8)
# split deskewed regions mapping to multiple original ones
def deskew(polygon):
polygon = shapely.affinity.rotate(polygon, -slope_deskew, origin=center)
polygon = shapely.affinity.translate(polygon, *offset.squeeze())
#polygon = shapely.affinity.translate(polygon, *offset.squeeze())
return polygon
for j in range(len(contours_only_text_parent_d)):
if np.count_nonzero(corresp[:, j]) > 1:
@ -4509,14 +4509,38 @@ class Eynollah:
if polygon_d]
contours_only_text_parent_d_ordered[indices] = contours_d
# cv2.fillPoly(img3, pts=contours_d, color=j + 1)
# plt.subplot(2, 2, 4, title="split contours")
# plt.subplot(1, 4, 3, title="split contours")
# plt.imshow(img3)
# img4 = np.zeros(text_only_d.shape[:2], dtype=np.uint8)
# for i in range(len(contours_only_text_parent)):
# cv2.fillPoly(img4, pts=[contours_only_text_parent_d_ordered[i]], color=i + 1)
# plt.subplot(2, 2, 2, title="result contours")
# plt.subplot(1, 4, 4, title="result contours")
# plt.imshow(img4)
# plt.show()
# from matplotlib import patches as ptchs
# plt.subplot(1, 2, 1, title="undeskewed")
# plt.imshow(text_only)
# centers = np.stack(find_center_of_contours(contours_only_text_parent)) # [2, N]
# for i in range(len(contours_only_text_parent)):
# cnt = contours_only_text_parent[i]
# ctr = centers[:, i]
# plt.gca().add_patch(ptchs.Polygon(cnt[:, 0], closed=False, fill=False, color='blue'))
# plt.gca().scatter(ctr[0], ctr[1], 20, c='blue', marker='x')
# plt.gca().text(ctr[0], ctr[1], str(i), c='blue')
# plt.subplot(1, 2, 2, title="deskewed")
# plt.imshow(text_only_d)
# centers_d = np.stack(find_center_of_contours(contours_only_text_parent_d_ordered)) # [2, N]
# for i in range(len(contours_only_text_parent)):
# cnt = contours_only_text_parent[i]
# cnt = polygon2contour(deskew(contour2polygon(cnt)))
# plt.gca().add_patch(ptchs.Polygon(cnt[:, 0], closed=False, fill=False, color='blue'))
# for i in range(len(contours_only_text_parent_d_ordered)):
# cnt = contours_only_text_parent_d_ordered[i]
# ctr = centers_d[:, i]
# plt.gca().add_patch(ptchs.Polygon(cnt[:, 0], closed=False, fill=False, color='red'))
# plt.gca().scatter(ctr[0], ctr[1], 20, c='red', marker='x')
# plt.gca().text(ctr[0], ctr[1], str(i), c='red')
# plt.show()
if not len(contours_only_text_parent):
# stop early