qurator-spk
/
eynollah
mirror of https://github.com/qurator-spk/eynollah.git
1
0
Fork 0
Code Issues Projects Releases Wiki Activity

eliminate more unused vars

Browse Source
pull/19/head
Konstantin Baierer 4 years ago
parent 6637eff3e7
commit cb6bc17ce1
1 changed files with 10 additions and 15 deletions
Show Stats Download Patch File Download Diff File

25
sbb_newspapers_org_image/eynollah.py
Unescape Escape View File

@ -161,11 +161,10 @@ class eynollah:
def predict_enhancement(self, img): def predict_enhancement(self, img):
self.logger.debug("enter predict_enhancement") self.logger.debug("enter predict_enhancement")
model_enhancement, session_enhancemnet = self.start_new_session_and_model(self.model_dir_of_enhancemnet) model_enhancement, _ = self.start_new_session_and_model(self.model_dir_of_enhancemnet)
img_height_model = model_enhancement.layers[len(model_enhancement.layers) - 1].output_shape[1] img_height_model = model_enhancement.layers[len(model_enhancement.layers) - 1].output_shape[1]
img_width_model = model_enhancement.layers[len(model_enhancement.layers) - 1].output_shape[2] img_width_model = model_enhancement.layers[len(model_enhancement.layers) - 1].output_shape[2]
# n_classes = model_enhancement.layers[len(model_enhancement.layers) - 1].output_shape[3]
if img.shape[0] < img_height_model: if img.shape[0] < img_height_model:
img = cv2.resize(img, (img.shape[1], img_width_model), interpolation=cv2.INTER_NEAREST) img = cv2.resize(img, (img.shape[1], img_width_model), interpolation=cv2.INTER_NEAREST)
@ -180,7 +179,6 @@ class eynollah:
img_w = img.shape[1] img_w = img.shape[1]
prediction_true = np.zeros((img_h, img_w, 3)) prediction_true = np.zeros((img_h, img_w, 3))
mask_true = np.zeros((img_h, img_w))
nxf = img_w / float(width_mid) nxf = img_w / float(width_mid)
nyf = img_h / float(height_mid) nyf = img_h / float(height_mid)
@ -344,7 +342,7 @@ class eynollah:
K.clear_session() K.clear_session()
gc.collect() gc.collect()
img_new, num_column_is_classified = self.calculate_width_height_by_columns(img, num_col, width_early, label_p_pred) img_new, _ = self.calculate_width_height_by_columns(img, num_col, width_early, label_p_pred)
if img_new.shape[1] > img.shape[1]: if img_new.shape[1] > img.shape[1]:
img_new = self.predict_enhancement(img_new) img_new = self.predict_enhancement(img_new)
@ -355,7 +353,7 @@ class eynollah:
def resize_and_enhance_image_with_column_classifier(self): def resize_and_enhance_image_with_column_classifier(self):
self.logger.debug("enter resize_and_enhance_image_with_column_classifier") self.logger.debug("enter resize_and_enhance_image_with_column_classifier")
dpi = check_dpi(self.image_filename) dpi = check_dpi(self.image_filename)
self.logger.info("Detected %s DPI" % dpi) self.logger.info("Detected %s DPI", dpi)
img = self.imread() img = self.imread()
_, page_coord = self.early_page_for_num_of_column_classification() _, page_coord = self.early_page_for_num_of_column_classification()
@ -459,8 +457,6 @@ class eynollah:
img_height_model = model.layers[len(model.layers) - 1].output_shape[1] img_height_model = model.layers[len(model.layers) - 1].output_shape[1]
img_width_model = model.layers[len(model.layers) - 1].output_shape[2] img_width_model = model.layers[len(model.layers) - 1].output_shape[2]
n_classes = model.layers[len(model.layers) - 1].output_shape[3]
if not patches: if not patches:
img_h_page = img.shape[0] img_h_page = img.shape[0]
@ -1891,7 +1887,7 @@ class eynollah:
def run_textline(self, image_page): def run_textline(self, image_page):
scaler_h_textline = 1 # 1.2#1.2 scaler_h_textline = 1 # 1.2#1.2
scaler_w_textline = 1 # 0.9#1 scaler_w_textline = 1 # 0.9#1
textline_mask_tot_ea, textline_mask_tot_long_shot = self.textline_contours(image_page, True, scaler_h_textline, scaler_w_textline) textline_mask_tot_ea, _ = self.textline_contours(image_page, True, scaler_h_textline, scaler_w_textline)
K.clear_session() K.clear_session()
gc.collect() gc.collect()
@ -1900,7 +1896,7 @@ class eynollah:
# plt.show() # plt.show()
if self.plotter: if self.plotter:
self.plotter.save_plot_of_textlines(textline_mask_tot_ea, image_page) self.plotter.save_plot_of_textlines(textline_mask_tot_ea, image_page)
return textline_mask_tot_ea, textline_mask_tot_long_shot return textline_mask_tot_ea
def run_deskew(self, textline_mask_tot_ea): def run_deskew(self, textline_mask_tot_ea):
sigma = 2 sigma = 2
@ -2105,7 +2101,7 @@ class eynollah:
return return
t1 = time.time() t1 = time.time()
textline_mask_tot_ea, textline_mask_tot_long_shot = self.run_textline(image_page) textline_mask_tot_ea = self.run_textline(image_page)
self.logger.info("textline detection took %ss", str(time.time() - t1)) self.logger.info("textline detection took %ss", str(time.time() - t1))
t1 = time.time() t1 = time.time()
@ -2246,7 +2242,7 @@ class eynollah:
if not self.curved_line: if not self.curved_line:
slopes, all_found_texline_polygons, boxes_text, txt_con_org, contours_only_text_parent, all_box_coord, index_by_text_par_con = self.get_slopes_and_deskew_new(txt_con_org, contours_only_text_parent, textline_mask_tot_ea, image_page_rotated, boxes_text, slope_deskew) slopes, all_found_texline_polygons, boxes_text, txt_con_org, contours_only_text_parent, all_box_coord, index_by_text_par_con = self.get_slopes_and_deskew_new(txt_con_org, contours_only_text_parent, textline_mask_tot_ea, image_page_rotated, boxes_text, slope_deskew)
slopes_marginals, all_found_texline_polygons_marginals, boxes_marginals, _, polygons_of_marginals, all_box_coord_marginals, index_by_text_par_con_marginal = self.get_slopes_and_deskew_new(polygons_of_marginals, polygons_of_marginals, textline_mask_tot_ea, image_page_rotated, boxes_marginals, slope_deskew) slopes_marginals, all_found_texline_polygons_marginals, boxes_marginals, _, polygons_of_marginals, all_box_coord_marginals, _ = self.get_slopes_and_deskew_new(polygons_of_marginals, polygons_of_marginals, textline_mask_tot_ea, image_page_rotated, boxes_marginals, slope_deskew)
else: else:
scale_param = 1 scale_param = 1
@ -2255,7 +2251,6 @@ class eynollah:
all_found_texline_polygons_marginals, boxes_marginals, _, polygons_of_marginals, all_box_coord_marginals, index_by_text_par_con_marginal, slopes_marginals = self.get_slopes_and_deskew_new_curved(polygons_of_marginals, polygons_of_marginals, cv2.erode(textline_mask_tot_ea, kernel=self.kernel, iterations=1), image_page_rotated, boxes_marginals, text_only, num_col_classifier, scale_param, slope_deskew) all_found_texline_polygons_marginals, boxes_marginals, _, polygons_of_marginals, all_box_coord_marginals, index_by_text_par_con_marginal, slopes_marginals = self.get_slopes_and_deskew_new_curved(polygons_of_marginals, polygons_of_marginals, cv2.erode(textline_mask_tot_ea, kernel=self.kernel, iterations=1), image_page_rotated, boxes_marginals, text_only, num_col_classifier, scale_param, slope_deskew)
all_found_texline_polygons_marginals = small_textlines_to_parent_adherence2(all_found_texline_polygons_marginals, textline_mask_tot_ea, num_col_classifier) all_found_texline_polygons_marginals = small_textlines_to_parent_adherence2(all_found_texline_polygons_marginals, textline_mask_tot_ea, num_col_classifier)
index_of_vertical_text_contours = np.array(range(len(slopes)))[(abs(np.array(slopes)) > 60)] index_of_vertical_text_contours = np.array(range(len(slopes)))[(abs(np.array(slopes)) > 60)]
contours_text_vertical = [contours_only_text_parent[i] for i in index_of_vertical_text_contours]
K.clear_session() K.clear_session()
gc.collect() gc.collect()
@ -2264,7 +2259,7 @@ class eynollah:
if self.full_layout: if self.full_layout:
if np.abs(slope_deskew) >= SLOPE_THRESHOLD: if np.abs(slope_deskew) >= SLOPE_THRESHOLD:
contours_only_text_parent_d_ordered = list(np.array(contours_only_text_parent_d_ordered)[index_by_text_par_con]) contours_only_text_parent_d_ordered = list(np.array(contours_only_text_parent_d_ordered)[index_by_text_par_con])
text_regions_p, contours_only_text_parent, contours_only_text_parent_h, all_box_coord, all_box_coord_h, all_found_texline_polygons, all_found_texline_polygons_h, slopes, slopes_h, contours_only_text_parent_d_ordered, contours_only_text_parent_h_d_ordered = check_any_text_region_in_model_one_is_main_or_header(text_regions_p, regions_fully, contours_only_text_parent, all_box_coord, all_found_texline_polygons, slopes, contours_only_text_parent_d_ordered) text_regions_p, contours_only_text_parent, contours_only_text_parent_h, all_box_coord, all_box_coord_h, all_found_texline_polygons, all_found_texline_polygons_h, slopes, _, contours_only_text_parent_d_ordered, contours_only_text_parent_h_d_ordered = check_any_text_region_in_model_one_is_main_or_header(text_regions_p, regions_fully, contours_only_text_parent, all_box_coord, all_found_texline_polygons, slopes, contours_only_text_parent_d_ordered)
else: else:
contours_only_text_parent_d_ordered = None contours_only_text_parent_d_ordered = None
text_regions_p, contours_only_text_parent, contours_only_text_parent_h, all_box_coord, all_box_coord_h, all_found_texline_polygons, all_found_texline_polygons_h, slopes, slopes_h, contours_only_text_parent_d_ordered, contours_only_text_parent_h_d_ordered = check_any_text_region_in_model_one_is_main_or_header(text_regions_p, regions_fully, contours_only_text_parent, all_box_coord, all_found_texline_polygons, slopes, contours_only_text_parent_d_ordered) text_regions_p, contours_only_text_parent, contours_only_text_parent_h, all_box_coord, all_box_coord_h, all_found_texline_polygons, all_found_texline_polygons_h, slopes, slopes_h, contours_only_text_parent_d_ordered, contours_only_text_parent_h_d_ordered = check_any_text_region_in_model_one_is_main_or_header(text_regions_p, regions_fully, contours_only_text_parent, all_box_coord, all_found_texline_polygons, slopes, contours_only_text_parent_d_ordered)
@ -2286,9 +2281,9 @@ class eynollah:
if not self.headers_off: if not self.headers_off:
if np.abs(slope_deskew) < SLOPE_THRESHOLD: if np.abs(slope_deskew) < SLOPE_THRESHOLD:
num_col, peaks_neg_fin, matrix_of_lines_ch, spliter_y_new, _ = find_number_of_columns_in_document(np.repeat(text_regions_p[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines, contours_only_text_parent_h) num_col, _, matrix_of_lines_ch, spliter_y_new, _ = find_number_of_columns_in_document(np.repeat(text_regions_p[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines, contours_only_text_parent_h)
else: else:
num_col_d, peaks_neg_fin_d, matrix_of_lines_ch_d, spliter_y_new_d, _ = find_number_of_columns_in_document(np.repeat(text_regions_p_1_n[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines, contours_only_text_parent_h_d_ordered) _, _, matrix_of_lines_ch_d, spliter_y_new_d, _ = find_number_of_columns_in_document(np.repeat(text_regions_p_1_n[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines, contours_only_text_parent_h_d_ordered)
elif self.headers_off: elif self.headers_off:
if np.abs(slope_deskew) < SLOPE_THRESHOLD: if np.abs(slope_deskew) < SLOPE_THRESHOLD:
num_col, peaks_neg_fin, matrix_of_lines_ch, spliter_y_new, _ = find_number_of_columns_in_document(np.repeat(text_regions_p[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines) num_col, peaks_neg_fin, matrix_of_lines_ch, spliter_y_new, _ = find_number_of_columns_in_document(np.repeat(text_regions_p[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines)

Write Preview
Loading…
Cancel
Save