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textline_contours_postprocessing: do not catch arbitrary exceptions

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Robert Sachunsky 2025-10-06 16:53:59 +02:00
parent fe603188f4
commit 6e57ab3741
1 changed files with 33 additions and 35 deletions
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68
src/eynollah/utils/separate_lines.py
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@ -1344,51 +1344,49 @@ def textline_contours_postprocessing(textline_mask, slope,
textline_mask = cv2.morphologyEx(textline_mask, cv2.MORPH_CLOSE, kernel) textline_mask = cv2.morphologyEx(textline_mask, cv2.MORPH_CLOSE, kernel)
textline_mask = cv2.erode(textline_mask, kernel, iterations=2) textline_mask = cv2.erode(textline_mask, kernel, iterations=2)
# textline_mask = cv2.erode(textline_mask, kernel, iterations=1) # textline_mask = cv2.erode(textline_mask, kernel, iterations=1)
try:
x_help = 30
y_help = 2
textline_mask_help = np.zeros((textline_mask.shape[0] + int(2 * y_help), x_help = 30
textline_mask.shape[1] + int(2 * x_help))) y_help = 2
textline_mask_help[y_help : y_help + textline_mask.shape[0],
x_help : x_help + textline_mask.shape[1]] = np.copy(textline_mask[:, :])
dst = rotate_image(textline_mask_help, slope) textline_mask_help = np.zeros((textline_mask.shape[0] + int(2 * y_help),
dst[dst != 0] = 1 textline_mask.shape[1] + int(2 * x_help)))
textline_mask_help[y_help : y_help + textline_mask.shape[0],
x_help : x_help + textline_mask.shape[1]] = np.copy(textline_mask[:, :])
# if np.abs(slope)>.5 and textline_mask.shape[0]/float(textline_mask.shape[1])>3: dst = rotate_image(textline_mask_help, slope)
# plt.imshow(dst) dst[dst != 0] = 1
# plt.show()
contour_text_copy = contour_text_interest.copy() # if np.abs(slope)>.5 and textline_mask.shape[0]/float(textline_mask.shape[1])>3:
contour_text_copy[:, 0, 0] = contour_text_copy[:, 0, 0] - box_ind[0] # plt.imshow(dst)
contour_text_copy[:, 0, 1] = contour_text_copy[:, 0, 1] - box_ind[1] # plt.show()
img_contour = np.zeros((box_ind[3], box_ind[2])) contour_text_copy = contour_text_interest.copy()
img_contour = cv2.fillPoly(img_contour, pts=[contour_text_copy], color=255) contour_text_copy[:, 0, 0] = contour_text_copy[:, 0, 0] - box_ind[0]
contour_text_copy[:, 0, 1] = contour_text_copy[:, 0, 1] - box_ind[1]
img_contour_help = np.zeros((img_contour.shape[0] + int(2 * y_help), img_contour = np.zeros((box_ind[3], box_ind[2]))
img_contour.shape[1] + int(2 * x_help))) img_contour = cv2.fillPoly(img_contour, pts=[contour_text_copy], color=255)
img_contour_help[y_help : y_help + img_contour.shape[0],
x_help : x_help + img_contour.shape[1]] = np.copy(img_contour[:, :])
img_contour_rot = rotate_image(img_contour_help, slope) img_contour_help = np.zeros((img_contour.shape[0] + int(2 * y_help),
img_contour.shape[1] + int(2 * x_help)))
img_contour_help[y_help : y_help + img_contour.shape[0],
x_help : x_help + img_contour.shape[1]] = np.copy(img_contour[:, :])
_, threshrot = cv2.threshold(img_contour_rot, 0, 255, 0) img_contour_rot = rotate_image(img_contour_help, slope)
contours_text_rot, _ = cv2.findContours(threshrot.astype(np.uint8), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
len_con_text_rot = [len(contours_text_rot[ib]) for ib in range(len(contours_text_rot))] _, threshrot = cv2.threshold(img_contour_rot, 0, 255, 0)
ind_big_con = np.argmax(len_con_text_rot) contours_text_rot, _ = cv2.findContours(threshrot.astype(np.uint8), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
if abs(slope) > 45: len_con_text_rot = [len(contours_text_rot[ib]) for ib in range(len(contours_text_rot))]
_, contours_rotated_clean = separate_lines_vertical_cont( ind_big_con = np.argmax(len_con_text_rot)
textline_mask, contours_text_rot[ind_big_con], box_ind, slope,
add_boxes_coor_into_textlines=add_boxes_coor_into_textlines) if abs(slope) > 45:
else: _, contours_rotated_clean = separate_lines_vertical_cont(
_, contours_rotated_clean = separate_lines( textline_mask, contours_text_rot[ind_big_con], box_ind, slope,
dst, contours_text_rot[ind_big_con], slope, x_help, y_help) add_boxes_coor_into_textlines=add_boxes_coor_into_textlines)
except: else:
contours_rotated_clean = [] _, contours_rotated_clean = separate_lines(
dst, contours_text_rot[ind_big_con], slope, x_help, y_help)
return contours_rotated_clean return contours_rotated_clean