.github/workflows/pypi.yml

@@ -1,24 +0,0 @@
-name: PyPI CD
-
-on:
-  release:
-    types: [published]
-  workflow_dispatch:
-
-jobs:
-  pypi-publish:
-    name: upload release to PyPI
-    runs-on: ubuntu-latest
-    permissions:
-      # IMPORTANT: this permission is mandatory for Trusted Publishing
-      id-token: write
-    steps:
-      - uses: actions/checkout@v4
-      - name: Set up Python
-        uses: actions/setup-python@v4
-      - name: Build package
-        run: make build
-      - name: Publish package distributions to PyPI
-        uses: pypa/gh-action-pypi-publish@release/v1
-        with:
-          verbose: true

CHANGELOG.md

@@ -5,10 +5,6 @@ Versioned according to [Semantic Versioning](http://semver.org/).
 
 ## Unreleased
 
-Fixed:
-
-  * restoring the contour in the original image caused an error due to an empty tuple
-
 ## [0.4.0] - 2025-04-07
 
 Fixed:

src/eynollah/utils/contour.py

@@ -230,6 +230,7 @@ def get_textregion_contours_in_org_image_light_old(cnts, img, slope_first):
 def do_back_rotation_and_get_cnt_back(contour_par, index_r_con, img, slope_first, confidence_matrix):
     img_copy = np.zeros(img.shape)
     img_copy = cv2.fillPoly(img_copy, pts=[contour_par], color=(1, 1, 1))
+    
     confidence_matrix_mapped_with_contour = confidence_matrix * img_copy[:,:,0]
     confidence_contour = np.sum(confidence_matrix_mapped_with_contour) / float(np.sum(img_copy[:,:,0]))
 
@@ -238,13 +239,9 @@ def do_back_rotation_and_get_cnt_back(contour_par, index_r_con, img, slope_first
     ret, thresh = cv2.threshold(imgray, 0, 255, 0)
 
     cont_int, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
-    if len(cont_int)==0:
+    cont_int[0][:, 0, 0] = cont_int[0][:, 0, 0] + np.abs(img_copy.shape[1] - img.shape[1])
-        cont_int = []
+    cont_int[0][:, 0, 1] = cont_int[0][:, 0, 1] + np.abs(img_copy.shape[0] - img.shape[0])
-        cont_int.append(contour_par)
+    # print(np.shape(cont_int[0]))
-        confidence_contour = 0
-    else:
-        cont_int[0][:, 0, 0] = cont_int[0][:, 0, 0] + np.abs(img_copy.shape[1] - img.shape[1])
-        cont_int[0][:, 0, 1] = cont_int[0][:, 0, 1] + np.abs(img_copy.shape[0] - img.shape[0])
     return cont_int[0], index_r_con, confidence_contour
 
 def get_textregion_contours_in_org_image_light(cnts, img, slope_first, confidence_matrix, map=map):