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(`skip_layout_and_reading_order` is already an attr)
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Robert Sachunsky 2025-10-09 23:05:50 +02:00
parent ecb53056f2
commit c4cb16c2a8
1 changed files with 102 additions and 103 deletions
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205
src/eynollah/eynollah.py
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@ -2155,7 +2155,7 @@ class Eynollah:
page_coord,
cont_page)
def get_regions_light_v(self,img,is_image_enhanced, num_col_classifier, skip_layout_and_reading_order=False):
def get_regions_light_v(self,img,is_image_enhanced, num_col_classifier):
self.logger.debug("enter get_regions_light_v")
t_in = time.time()
erosion_hurts = False
@ -2221,110 +2221,110 @@ class Eynollah:
#plt.imshwo(self.image_page_org_size)
#plt.show()
if not skip_layout_and_reading_order:
#print("inside 2 ", time.time()-t_in)
if num_col_classifier == 1 or num_col_classifier == 2:
if self.image_org.shape[0]/self.image_org.shape[1] > 2.5:
self.logger.debug("resized to %dx%d for %d cols",
img_resized.shape[1], img_resized.shape[0], num_col_classifier)
prediction_regions_org, confidence_matrix = self.do_prediction_new_concept(
True, img_resized, self.model_region_1_2, n_batch_inference=1,
thresholding_for_some_classes_in_light_version=True,
threshold_art_class_layout=self.threshold_art_class_layout)
else:
prediction_regions_org = np.zeros((self.image_org.shape[0], self.image_org.shape[1], 3))
confidence_matrix = np.zeros((self.image_org.shape[0], self.image_org.shape[1]))
prediction_regions_page, confidence_matrix_page = self.do_prediction_new_concept(
False, self.image_page_org_size, self.model_region_1_2, n_batch_inference=1,
thresholding_for_artificial_class_in_light_version=True,
threshold_art_class_layout=self.threshold_art_class_layout)
ys = slice(*self.page_coord[0:2])
xs = slice(*self.page_coord[2:4])
prediction_regions_org[ys, xs] = prediction_regions_page
confidence_matrix[ys, xs] = confidence_matrix_page
else:
new_h = (900+ (num_col_classifier-3)*100)
img_resized = resize_image(img_bin, int(new_h * img_bin.shape[0] /img_bin.shape[1]), new_h)
self.logger.debug("resized to %dx%d (new_h=%d) for %d cols",
img_resized.shape[1], img_resized.shape[0], new_h, num_col_classifier)
prediction_regions_org, confidence_matrix = self.do_prediction_new_concept(
True, img_resized, self.model_region_1_2, n_batch_inference=2,
thresholding_for_some_classes_in_light_version=True,
threshold_art_class_layout=self.threshold_art_class_layout)
###prediction_regions_org = self.do_prediction(True, img_bin, self.model_region,
###n_batch_inference=3,
###thresholding_for_some_classes_in_light_version=True)
#print("inside 3 ", time.time()-t_in)
#plt.imshow(prediction_regions_org[:,:,0])
#plt.show()
prediction_regions_org = resize_image(prediction_regions_org, img_height_h, img_width_h )
confidence_matrix = resize_image(confidence_matrix, img_height_h, img_width_h )
img_bin = resize_image(img_bin, img_height_h, img_width_h )
prediction_regions_org=prediction_regions_org[:,:,0]
mask_lines_only = (prediction_regions_org[:,:] ==3)*1
mask_texts_only = (prediction_regions_org[:,:] ==1)*1
mask_texts_only = mask_texts_only.astype('uint8')
##if num_col_classifier == 1 or num_col_classifier == 2:
###mask_texts_only = cv2.erode(mask_texts_only, KERNEL, iterations=1)
##mask_texts_only = cv2.dilate(mask_texts_only, KERNEL, iterations=1)
mask_texts_only = cv2.dilate(mask_texts_only, kernel=np.ones((2,2), np.uint8), iterations=1)
mask_images_only=(prediction_regions_org[:,:] ==2)*1
polygons_seplines, hir_seplines = return_contours_of_image(mask_lines_only)
test_khat = np.zeros(prediction_regions_org.shape)
test_khat = cv2.fillPoly(test_khat, pts=polygons_seplines, color=(1,1,1))
#plt.imshow(test_khat[:,:])
#plt.show()
#for jv in range(1):
#print(jv, hir_seplines[0][232][3])
#test_khat = np.zeros(prediction_regions_org.shape)
#test_khat = cv2.fillPoly(test_khat, pts = [polygons_seplines[232]], color=(1,1,1))
#plt.imshow(test_khat[:,:])
#plt.show()
polygons_seplines = filter_contours_area_of_image(
mask_lines_only, polygons_seplines, hir_seplines, max_area=1, min_area=0.00001, dilate=1)
test_khat = np.zeros(prediction_regions_org.shape)
test_khat = cv2.fillPoly(test_khat, pts = polygons_seplines, color=(1,1,1))
#plt.imshow(test_khat[:,:])
#plt.show()
#sys.exit()
polygons_of_only_texts = return_contours_of_interested_region(mask_texts_only,1,0.00001)
##polygons_of_only_texts = dilate_textregion_contours(polygons_of_only_texts)
polygons_of_only_lines = return_contours_of_interested_region(mask_lines_only,1,0.00001)
text_regions_p_true = np.zeros(prediction_regions_org.shape)
text_regions_p_true = cv2.fillPoly(text_regions_p_true, pts=polygons_of_only_lines, color=(3,3,3))
text_regions_p_true[:,:][mask_images_only[:,:] == 1] = 2
text_regions_p_true = cv2.fillPoly(text_regions_p_true, pts = polygons_of_only_texts, color=(1,1,1))
textline_mask_tot_ea[(text_regions_p_true==0) | (text_regions_p_true==4) ] = 0
#plt.imshow(textline_mask_tot_ea)
#plt.show()
#print("inside 4 ", time.time()-t_in)
self.logger.debug("exit get_regions_light_v")
return (text_regions_p_true,
erosion_hurts,
polygons_seplines,
polygons_of_only_texts,
textline_mask_tot_ea,
img_bin,
confidence_matrix)
else:
if self.skip_layout_and_reading_order:
img_bin = resize_image(img_bin,img_height_h, img_width_h )
self.logger.debug("exit get_regions_light_v")
return None, erosion_hurts, None, None, textline_mask_tot_ea, img_bin, None
#print("inside 2 ", time.time()-t_in)
if num_col_classifier == 1 or num_col_classifier == 2:
if self.image_org.shape[0]/self.image_org.shape[1] > 2.5:
self.logger.debug("resized to %dx%d for %d cols",
img_resized.shape[1], img_resized.shape[0], num_col_classifier)
prediction_regions_org, confidence_matrix = self.do_prediction_new_concept(
True, img_resized, self.model_region_1_2, n_batch_inference=1,
thresholding_for_some_classes_in_light_version=True,
threshold_art_class_layout=self.threshold_art_class_layout)
else:
prediction_regions_org = np.zeros((self.image_org.shape[0], self.image_org.shape[1], 3))
confidence_matrix = np.zeros((self.image_org.shape[0], self.image_org.shape[1]))
prediction_regions_page, confidence_matrix_page = self.do_prediction_new_concept(
False, self.image_page_org_size, self.model_region_1_2, n_batch_inference=1,
thresholding_for_artificial_class_in_light_version=True,
threshold_art_class_layout=self.threshold_art_class_layout)
ys = slice(*self.page_coord[0:2])
xs = slice(*self.page_coord[2:4])
prediction_regions_org[ys, xs] = prediction_regions_page
confidence_matrix[ys, xs] = confidence_matrix_page
else:
new_h = (900+ (num_col_classifier-3)*100)
img_resized = resize_image(img_bin, int(new_h * img_bin.shape[0] /img_bin.shape[1]), new_h)
self.logger.debug("resized to %dx%d (new_h=%d) for %d cols",
img_resized.shape[1], img_resized.shape[0], new_h, num_col_classifier)
prediction_regions_org, confidence_matrix = self.do_prediction_new_concept(
True, img_resized, self.model_region_1_2, n_batch_inference=2,
thresholding_for_some_classes_in_light_version=True,
threshold_art_class_layout=self.threshold_art_class_layout)
###prediction_regions_org = self.do_prediction(True, img_bin, self.model_region,
###n_batch_inference=3,
###thresholding_for_some_classes_in_light_version=True)
#print("inside 3 ", time.time()-t_in)
#plt.imshow(prediction_regions_org[:,:,0])
#plt.show()
prediction_regions_org = resize_image(prediction_regions_org, img_height_h, img_width_h )
confidence_matrix = resize_image(confidence_matrix, img_height_h, img_width_h )
img_bin = resize_image(img_bin, img_height_h, img_width_h )
prediction_regions_org=prediction_regions_org[:,:,0]
mask_lines_only = (prediction_regions_org[:,:] ==3)*1
mask_texts_only = (prediction_regions_org[:,:] ==1)*1
mask_texts_only = mask_texts_only.astype('uint8')
##if num_col_classifier == 1 or num_col_classifier == 2:
###mask_texts_only = cv2.erode(mask_texts_only, KERNEL, iterations=1)
##mask_texts_only = cv2.dilate(mask_texts_only, KERNEL, iterations=1)
mask_texts_only = cv2.dilate(mask_texts_only, kernel=np.ones((2,2), np.uint8), iterations=1)
mask_images_only=(prediction_regions_org[:,:] ==2)*1
polygons_seplines, hir_seplines = return_contours_of_image(mask_lines_only)
test_khat = np.zeros(prediction_regions_org.shape)
test_khat = cv2.fillPoly(test_khat, pts=polygons_seplines, color=(1,1,1))
#plt.imshow(test_khat[:,:])
#plt.show()
#for jv in range(1):
#print(jv, hir_seplines[0][232][3])
#test_khat = np.zeros(prediction_regions_org.shape)
#test_khat = cv2.fillPoly(test_khat, pts = [polygons_seplines[232]], color=(1,1,1))
#plt.imshow(test_khat[:,:])
#plt.show()
polygons_seplines = filter_contours_area_of_image(
mask_lines_only, polygons_seplines, hir_seplines, max_area=1, min_area=0.00001, dilate=1)
test_khat = np.zeros(prediction_regions_org.shape)
test_khat = cv2.fillPoly(test_khat, pts = polygons_seplines, color=(1,1,1))
#plt.imshow(test_khat[:,:])
#plt.show()
#sys.exit()
polygons_of_only_texts = return_contours_of_interested_region(mask_texts_only,1,0.00001)
##polygons_of_only_texts = dilate_textregion_contours(polygons_of_only_texts)
polygons_of_only_lines = return_contours_of_interested_region(mask_lines_only,1,0.00001)
text_regions_p_true = np.zeros(prediction_regions_org.shape)
text_regions_p_true = cv2.fillPoly(text_regions_p_true, pts=polygons_of_only_lines, color=(3,3,3))
text_regions_p_true[:,:][mask_images_only[:,:] == 1] = 2
text_regions_p_true = cv2.fillPoly(text_regions_p_true, pts = polygons_of_only_texts, color=(1,1,1))
textline_mask_tot_ea[(text_regions_p_true==0) | (text_regions_p_true==4) ] = 0
#plt.imshow(textline_mask_tot_ea)
#plt.show()
#print("inside 4 ", time.time()-t_in)
self.logger.debug("exit get_regions_light_v")
return (text_regions_p_true,
erosion_hurts,
polygons_seplines,
polygons_of_only_texts,
textline_mask_tot_ea,
img_bin,
confidence_matrix)
def get_regions_from_xy_2models(self,img,is_image_enhanced, num_col_classifier):
self.logger.debug("enter get_regions_from_xy_2models")
erosion_hurts = False
@ -4226,8 +4226,7 @@ class Eynollah:
self.logger.info("Skipping layout analysis and reading order detection")
_ ,_, _, _, textline_mask_tot_ea, img_bin_light, _ = \
self.get_regions_light_v(img_res, is_image_enhanced, num_col_classifier,
skip_layout_and_reading_order=self.skip_layout_and_reading_order)
self.get_regions_light_v(img_res, is_image_enhanced, num_col_classifier,)
page_coord, image_page, textline_mask_tot_ea, img_bin_light, cont_page = \
self.run_graphics_and_columns_without_layout(textline_mask_tot_ea, img_bin_light)