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kba 2025-11-27 11:30:00 +01:00
parent 177d555ded
commit 4aa9543a7d
2 changed files with 2 additions and 48 deletions
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44
src/eynollah/eynollah.py
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@ -1512,52 +1512,10 @@ class Eynollah:
img_width_h = img.shape[1] img_width_h = img.shape[1]
model_region = self.model_zoo.get("region_fl") if patches else self.model_zoo.get("region_fl_np") model_region = self.model_zoo.get("region_fl") if patches else self.model_zoo.get("region_fl_np")
if not patches:
img = otsu_copy_binary(img)
img = img.astype(np.uint8)
prediction_regions2 = None
elif cols:
if cols == 1:
img_height_new = int(img_height_h * 0.7)
img_width_new = int(img_width_h * 0.7)
elif cols == 2:
img_height_new = int(img_height_h * 0.4)
img_width_new = int(img_width_h * 0.4)
else:
img_height_new = int(img_height_h * 0.3)
img_width_new = int(img_width_h * 0.3)
img2 = otsu_copy_binary(img)
img2 = img2.astype(np.uint8)
img2 = resize_image(img2, img_height_new, img_width_new)
prediction_regions2 = self.do_prediction(patches, img2, model_region, marginal_of_patch_percent=0.1)
prediction_regions2 = resize_image(prediction_regions2, img_height_h, img_width_h)
img = otsu_copy_binary(img).astype(np.uint8)
if cols == 1:
img = resize_image(img, int(img_height_h * 0.5), int(img_width_h * 0.5)).astype(np.uint8)
elif cols == 2 and img_width_h >= 2000:
img = resize_image(img, int(img_height_h * 0.9), int(img_width_h * 0.9)).astype(np.uint8)
elif cols == 3 and ((self.scale_x == 1 and img_width_h > 3000) or
(self.scale_x != 1 and img_width_h > 2800)):
img = resize_image(img, 2800 * img_height_h // img_width_h, 2800).astype(np.uint8)
elif cols == 4 and ((self.scale_x == 1 and img_width_h > 4000) or
(self.scale_x != 1 and img_width_h > 3700)):
img = resize_image(img, 3700 * img_height_h // img_width_h, 3700).astype(np.uint8)
elif cols == 4:
img = resize_image(img, int(img_height_h * 0.9), int(img_width_h * 0.9)).astype(np.uint8)
elif cols == 5 and self.scale_x == 1 and img_width_h > 5000:
img = resize_image(img, int(img_height_h * 0.7), int(img_width_h * 0.7)).astype(np.uint8)
elif cols == 5:
img = resize_image(img, int(img_height_h * 0.9), int(img_width_h * 0.9)).astype(np.uint8)
elif img_width_h > 5600:
img = resize_image(img, 5600 * img_height_h // img_width_h, 5600).astype(np.uint8)
else:
img = resize_image(img, int(img_height_h * 0.9), int(img_width_h * 0.9)).astype(np.uint8)
prediction_regions = self.do_prediction(patches, img, model_region, marginal_of_patch_percent=0.1) prediction_regions = self.do_prediction(patches, img, model_region, marginal_of_patch_percent=0.1)
prediction_regions = resize_image(prediction_regions, img_height_h, img_width_h) prediction_regions = resize_image(prediction_regions, img_height_h, img_width_h)
self.logger.debug("exit extract_text_regions") self.logger.debug("exit extract_text_regions")
return prediction_regions, prediction_regions2 return prediction_regions, None
def get_textlines_of_a_textregion_sorted(self, textlines_textregion, cx_textline, cy_textline, w_h_textline): def get_textlines_of_a_textregion_sorted(self, textlines_textregion, cx_textline, cy_textline, w_h_textline):
N = len(cy_textline) N = len(cy_textline)

6
src/eynollah/writer.py
View file

@ -72,13 +72,9 @@ class EynollahXmlWriter:
point = point[0] point = point[0]
point_x = point[0] + page_coord[2] point_x = point[0] + page_coord[2]
point_y = point[1] + page_coord[0] point_y = point[1] + page_coord[0]
# FIXME: or actually... not self.curved_line or np.abs(slopes[region_idx]) > 45?
if not (self.curved_line and np.abs(slopes[region_idx]) <= 45):
point_x += region_bboxes[2]
point_y += region_bboxes[0]
point_x = max(0, int(point_x / self.scale_x)) point_x = max(0, int(point_x / self.scale_x))
point_y = max(0, int(point_y / self.scale_y)) point_y = max(0, int(point_y / self.scale_y))
points_co += str(point_x) + ',' + str(point_y) + ' ' points_co += f'{point_x},{point_y} '
coords.set_points(points_co[:-1]) coords.set_points(points_co[:-1])
def write_pagexml(self, pcgts): def write_pagexml(self, pcgts):