From 29fcc75c0b64a904fc997d204e194619a1d13f7d Mon Sep 17 00:00:00 2001 From: Robert Sachunsky Date: Sun, 5 Oct 2025 02:45:01 +0200 Subject: [PATCH] matching deskewed text region contours with predicted: improve - when matching undeskewed and new contours, do not just pick the closest centers, respectively, but also of similar size (by making the contour area the 3rd dimension of the vector norm in the distance calculation) --- src/eynollah/eynollah.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/src/eynollah/eynollah.py b/src/eynollah/eynollah.py index a30e08e..db7e59f 100644 --- a/src/eynollah/eynollah.py +++ b/src/eynollah/eynollah.py @@ -4608,7 +4608,11 @@ class Eynollah: for i in range(len(contours_only_text_parent)): p = np.dot(M_22, centers[:, i:i+1]) # [2, 1] p -= offset - dists = np.linalg.norm(p - centers_d, axis=0) + # add dimension for area + #dists = np.linalg.norm(p - centers_d, axis=0) + diffs = (np.append(p, [[areas_cnt_text_parent[i]]], axis=0) - + np.append(centers_d, areas_cnt_text_d[np.newaxis], axis=0)) + dists = np.linalg.norm(diffs, axis=0) contours_only_text_parent_d_ordered.append( contours_only_text_parent_d[np.argmin(dists)]) # cv2.fillPoly(img2, pts=[contours_only_text_parent_d[np.argmin(dists)]], color=i + 1)