qurator-spk/eynollah
1
0
Fork 0
mirror of https://github.com/qurator-spk/eynollah.git synced 2026-04-30 19:22:03 +02:00
Code Issues Projects Releases Wiki Activity

do_work_of_slopes_new_curved (if angle <45°): simplify, improve…

Browse source 
- use relative images, cropped to parent bbox (faster)
- no `scale` parameter (unused)
- use largest textline contours by area instead of first
- simplify
This commit is contained in:
Robert Sachunsky 2026-04-23 20:38:45 +02:00
parent 0dce1f24d2
commit d257869d83
1 changed files with 16 additions and 31 deletions
Download patch file Download diff file Expand all files Collapse all files

47
src/eynollah/utils/separate_lines.py
View file

@ -1662,44 +1662,29 @@ def do_work_of_slopes_new_curved(
# print(slope, slope_deskew)
crop_coor = box2rect(box_text)
if abs(slope) < 45:
mask_parent = np.zeros((h, w), dtype=np.uint8)
mask_parent = cv2.fillPoly(mask_parent, pts=[contour_par - [x, y]], color=1)
mask_parent_textline = mask_parent * textline_mask_tot_ea[y : y + h, x : x + w]
if abs(slope_for_all) < 45:
textline_region_in_image = np.zeros(textline_mask_tot_ea.shape)
x, y, w, h = cv2.boundingRect(contour_par)
mask_biggest = np.zeros(textline_mask_tot_ea.shape)
mask_biggest = cv2.fillPoly(mask_biggest, pts=[contour_par], color=(1, 1, 1))
mask_region_in_patch_region = mask_biggest[y : y + h, x : x + w]
textline_biggest_region = mask_biggest * textline_mask_tot_ea
textline_rotated_separated = separate_lines_new2(textline_biggest_region[y: y+h, x: x+w], 0,
num_col, slope_for_all,
mask_textlines_separated_d = separate_lines_new2(mask_parent_textline, 0,
num_col, slope,
logger=logger, plotter=plotter)
#mask_textlines_separated_d[mask_parent != 1] = 0
textline_rotated_separated[mask_region_in_patch_region[:, :] != 1] = 0
textline_region_in_image[y : y + h, x : x + w] = textline_rotated_separated
pixel_img = 1
cnt_textlines_in_image = return_contours_of_interested_textline(textline_region_in_image, pixel_img)
textline_contours = return_contours_of_interested_textline(mask_textlines_separated_d, 1)
textlines_cnt_per_region = []
for jjjj in range(len(cnt_textlines_in_image)):
mask_biggest2 = np.zeros(textline_mask_tot_ea.shape)
mask_biggest2 = cv2.fillPoly(mask_biggest2, pts=[cnt_textlines_in_image[jjjj]], color=(1, 1, 1))
if num_col + 1 == 1:
mask_biggest2 = cv2.dilate(mask_biggest2, KERNEL, iterations=5)
else:
mask_biggest2 = cv2.dilate(mask_biggest2, KERNEL, iterations=4)
for contour in textline_contours:
mask_line = np.zeros_like(mask_parent)
mask_line = cv2.fillPoly(mask_line, pts=[contour], color=1)
mask_line = cv2.dilate(mask_line, KERNEL, iterations=5 if num_col == 0 else 4)
pixel_img = 1
mask_biggest2 = resize_image(mask_biggest2,
int(mask_biggest2.shape[0] * scale_par),
int(mask_biggest2.shape[1] * scale_par))
cnt_textlines_in_image_ind = return_contours_of_interested_textline(mask_biggest2, pixel_img)
textline_contours2 = return_contours_of_interested_textline(mask_line, 1)
textline_areas2 = np.array(list(map(cv2.contourArea, textline_contours2)))
try:
textlines_cnt_per_region.append(cnt_textlines_in_image_ind[0])
contour2 = textline_contours2[np.argmax(textline_areas2)]
textlines_cnt_per_region.append(contour2 + [x, y])
except Exception as why:
logger.error(why)
else: