functionality checked

pull/19/head
vahidrezanezhad 4 years ago committed by GitHub
parent ef3ccd0d5f
commit 0a92543245
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@ -2125,7 +2125,7 @@ class eynollah:
return self.do_order_of_regions_full_layout(*args, **kwargs) return self.do_order_of_regions_full_layout(*args, **kwargs)
return self.do_order_of_regions_no_full_layout(*args, **kwargs) return self.do_order_of_regions_no_full_layout(*args, **kwargs)
def run_graphics_and_columns(self, text_regions_p_1, num_column_is_classified): def run_graphics_and_columns(self, text_regions_p_1, num_col_classifier, num_column_is_classified):
img_g = cv2.imread(self.image_filename, cv2.IMREAD_GRAYSCALE) img_g = cv2.imread(self.image_filename, cv2.IMREAD_GRAYSCALE)
img_g = img_g.astype(np.uint8) img_g = img_g.astype(np.uint8)
@ -2154,19 +2154,20 @@ class eynollah:
img_only_regions_with_sep = img_only_regions_with_sep.astype(np.uint8) img_only_regions_with_sep = img_only_regions_with_sep.astype(np.uint8)
img_only_regions = cv2.erode(img_only_regions_with_sep[:, :], self.kernel, iterations=6) img_only_regions = cv2.erode(img_only_regions_with_sep[:, :], self.kernel, iterations=6)
num_col_classifier = None
try: try:
num_col, peaks_neg_fin = find_num_col(img_only_regions, multiplier=6.0) num_col, peaks_neg_fin = find_num_col(img_only_regions, multiplier=6.0)
if not num_column_is_classified: if not num_column_is_classified:
num_col_classifier = num_col + 1 num_col_classifier = num_col + 1
except: except:
num_col = None num_col = None
peaks_neg_fin = [] peaks_neg_fin = []
return num_col, num_col_classifier, img_only_regions, page_coord, image_page, mask_images, mask_lines return num_col+1, num_col_classifier, img_only_regions, page_coord, image_page, mask_images, mask_lines, text_regions_p_1
def run_enhancement(self): def run_enhancement(self):
self.logger.info("resize and enhance image") self.logger.info("resize and enhance image")
is_image_enhanced, img_org, img_res, _, num_column_is_classified = self.resize_and_enhance_image_with_column_classifier() is_image_enhanced, img_org, img_res, num_col_classifier, num_column_is_classified = self.resize_and_enhance_image_with_column_classifier()
self.logger.info("Image is %senhanced", '' if is_image_enhanced else 'not ') self.logger.info("Image is %senhanced", '' if is_image_enhanced else 'not ')
K.clear_session() K.clear_session()
scale = 1 scale = 1
@ -2185,7 +2186,7 @@ class eynollah:
if self.allow_scaling: if self.allow_scaling:
img_org, img_res, is_image_enhanced = self.resize_image_with_column_classifier(is_image_enhanced) img_org, img_res, is_image_enhanced = self.resize_image_with_column_classifier(is_image_enhanced)
self.get_image_and_scales_after_enhancing(img_org, img_res) self.get_image_and_scales_after_enhancing(img_org, img_res)
return img_res, is_image_enhanced, num_column_is_classified return img_res, is_image_enhanced, num_col_classifier, num_column_is_classified
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
@ -2228,6 +2229,8 @@ class eynollah:
try: try:
regions_without_seperators = (text_regions_p[:, :] == 1) * 1 regions_without_seperators = (text_regions_p[:, :] == 1) * 1
regions_without_seperators = regions_without_seperators.astype(np.uint8) regions_without_seperators = regions_without_seperators.astype(np.uint8)
text_regions_p = get_marginals(rotate_image(regions_without_seperators, slope_deskew), text_regions_p, num_col_classifier, slope_deskew, kernel=self.kernel) text_regions_p = get_marginals(rotate_image(regions_without_seperators, slope_deskew), text_regions_p, num_col_classifier, slope_deskew, kernel=self.kernel)
except: except:
pass pass
@ -2249,6 +2252,12 @@ class eynollah:
regions_without_seperators_d = (text_regions_p_1_n[:, :] == 1) * 1 regions_without_seperators_d = (text_regions_p_1_n[:, :] == 1) * 1
regions_without_seperators = (text_regions_p[:, :] == 1) * 1 # ( (text_regions_p[:,:]==1) | (text_regions_p[:,:]==2) )*1 #self.return_regions_without_seperators_new(text_regions_p[:,:,0],img_only_regions) regions_without_seperators = (text_regions_p[:, :] == 1) * 1 # ( (text_regions_p[:,:]==1) | (text_regions_p[:,:]==2) )*1 #self.return_regions_without_seperators_new(text_regions_p[:,:,0],img_only_regions)
if np.abs(slope_deskew) < SLOPE_THRESHOLD:
text_regions_p_1_n = None
textline_mask_tot_d = None
regions_without_seperators_d = None
pixel_lines = 3 pixel_lines = 3
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, seperators_closeup_n = 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, seperators_closeup_n = find_number_of_columns_in_document(np.repeat(text_regions_p[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines)
@ -2280,9 +2289,13 @@ class eynollah:
t1 = time.time() t1 = time.time()
if np.abs(slope_deskew) < SLOPE_THRESHOLD: if np.abs(slope_deskew) < SLOPE_THRESHOLD:
boxes = return_boxes_of_images_by_order_of_reading_new(spliter_y_new, regions_without_seperators, matrix_of_lines_ch, num_col_classifier) boxes = return_boxes_of_images_by_order_of_reading_new(spliter_y_new, regions_without_seperators, matrix_of_lines_ch, num_col_classifier)
boxes_d = None
self.logger.debug("len(boxes): %s", len(boxes))
else: else:
boxes_d = return_boxes_of_images_by_order_of_reading_new(spliter_y_new_d, regions_without_seperators_d, matrix_of_lines_ch_d, num_col_classifier) boxes_d = return_boxes_of_images_by_order_of_reading_new(spliter_y_new_d, regions_without_seperators_d, matrix_of_lines_ch_d, num_col_classifier)
self.logger.debug("len(boxes): %s", len(boxes)) boxes = None
self.logger.debug("len(boxes): %s", len(boxes_d))
self.logger.info("detecting boxes took %ss", str(time.time() - t1)) self.logger.info("detecting boxes took %ss", str(time.time() - t1))
img_revised_tab = text_regions_p[:, :] img_revised_tab = text_regions_p[:, :]
polygons_of_images = return_contours_of_interested_region(img_revised_tab, 2) polygons_of_images = return_contours_of_interested_region(img_revised_tab, 2)
@ -2291,7 +2304,7 @@ class eynollah:
# plt.show() # plt.show()
K.clear_session() K.clear_session()
self.logger.debug('exit run_boxes_no_full_layout') self.logger.debug('exit run_boxes_no_full_layout')
return polygons_of_images, img_revised_tab, text_regions_p_1_n, textline_mask_tot_d, regions_without_seperators_d return polygons_of_images, img_revised_tab, text_regions_p_1_n, textline_mask_tot_d, regions_without_seperators_d, boxes, boxes_d
def run_boxes_full_layout(self, image_page, textline_mask_tot, text_regions_p, slope_deskew, num_col_classifier, img_only_regions): def run_boxes_full_layout(self, image_page, textline_mask_tot, text_regions_p, slope_deskew, num_col_classifier, img_only_regions):
self.logger.debug('enter run_boxes_full_layout') self.logger.debug('enter run_boxes_full_layout')
@ -2361,6 +2374,13 @@ class eynollah:
regions_fully_n = resize_image(regions_fully_n, text_regions_p.shape[0], text_regions_p.shape[1]) regions_fully_n = resize_image(regions_fully_n, text_regions_p.shape[0], text_regions_p.shape[1])
regions_without_seperators_d = (text_regions_p_1_n[:, :] == 1) * 1 regions_without_seperators_d = (text_regions_p_1_n[:, :] == 1) * 1
else:
text_regions_p_1_n = None
textline_mask_tot_d = None
regions_without_seperators_d = None
regions_without_seperators = (text_regions_p[:, :] == 1) * 1 # ( (text_regions_p[:,:]==1) | (text_regions_p[:,:]==2) )*1 #self.return_regions_without_seperators_new(text_regions_p[:,:,0],img_only_regions) regions_without_seperators = (text_regions_p[:, :] == 1) * 1 # ( (text_regions_p[:,:]==1) | (text_regions_p[:,:]==2) )*1 #self.return_regions_without_seperators_new(text_regions_p[:,:,0],img_only_regions)
K.clear_session() K.clear_session()
@ -2369,7 +2389,7 @@ class eynollah:
pixel_img = 5 pixel_img = 5
polygons_of_images = return_contours_of_interested_region(img_revised_tab, pixel_img) polygons_of_images = return_contours_of_interested_region(img_revised_tab, pixel_img)
self.logger.debug('exit run_boxes_full_layout') self.logger.debug('exit run_boxes_full_layout')
return polygons_of_images, img_revised_tab, text_regions_p_1_n, textline_mask_tot_d, regions_without_seperators_d, regions_fully return polygons_of_images, img_revised_tab, text_regions_p_1_n, textline_mask_tot_d, regions_without_seperators_d, regions_fully, regions_without_seperators
def run(self): def run(self):
""" """
@ -2378,7 +2398,7 @@ class eynollah:
self.logger.debug("enter run") self.logger.debug("enter run")
t1 = time.time() t1 = time.time()
img_res, is_image_enhanced, num_column_is_classified = self.run_enhancement() img_res, is_image_enhanced, num_col_classifier, num_column_is_classified = self.run_enhancement()
self.logger.info("Enhancing took %ss ", str(time.time() - t1)) self.logger.info("Enhancing took %ss ", str(time.time() - t1))
t1 = time.time() t1 = time.time()
@ -2386,10 +2406,11 @@ class eynollah:
self.logger.info("Textregion detection took %ss ", str(time.time() - t1)) self.logger.info("Textregion detection took %ss ", str(time.time() - t1))
t1 = time.time() t1 = time.time()
num_col, num_col_classifier, img_only_regions, page_coord, image_page, mask_images, mask_lines = \ num_col, num_col_classifier, img_only_regions, page_coord, image_page, mask_images, mask_lines, text_regions_p_1 = \
self.run_graphics_and_columns(text_regions_p_1, num_column_is_classified) self.run_graphics_and_columns(text_regions_p_1, num_col_classifier, num_column_is_classified)
self.logger.info("Graphics detection took %ss ", str(time.time() - t1)) self.logger.info("Graphics detection took %ss ", str(time.time() - t1))
if not num_col: if not num_col:
self.logger.info("No columns detected, outputting an empty PAGE-XML") self.logger.info("No columns detected, outputting an empty PAGE-XML")
self.write_into_page_xml([], page_coord, self.dir_out, [], [], [], [], [], [], [], [], self.curved_line, [], []) self.write_into_page_xml([], page_coord, self.dir_out, [], [], [], [], [], [], [], [], self.curved_line, [], [])
@ -2410,14 +2431,14 @@ class eynollah:
t1 = time.time() t1 = time.time()
if not self.full_layout: if not self.full_layout:
polygons_of_images, img_revised_tab, text_regions_p_1_n, textline_mask_tot_d, regions_without_seperators_d = self.run_boxes_no_full_layout(image_page, textline_mask_tot, text_regions_p, slope_deskew, num_col_classifier) polygons_of_images, img_revised_tab, text_regions_p_1_n, textline_mask_tot_d, regions_without_seperators_d, boxes, boxes_d = self.run_boxes_no_full_layout(image_page, textline_mask_tot, text_regions_p, slope_deskew, num_col_classifier)
pixel_img = 4 pixel_img = 4
min_area_mar = 0.00001 min_area_mar = 0.00001
polygons_of_marginals = return_contours_of_interested_region(text_regions_p, pixel_img, min_area_mar) polygons_of_marginals = return_contours_of_interested_region(text_regions_p, pixel_img, min_area_mar)
if self.full_layout: if self.full_layout:
polygons_of_images, img_revised_tab, text_regions_p_1_n, textline_mask_tot_d, regions_without_seperators_d, regions_fully = self.run_boxes_full_layout(image_page, textline_mask_tot, text_regions_p, slope_deskew, num_col_classifier, img_only_regions) polygons_of_images, img_revised_tab, text_regions_p_1_n, textline_mask_tot_d, regions_without_seperators_d, regions_fully, regions_without_seperators = self.run_boxes_full_layout(image_page, textline_mask_tot, text_regions_p, slope_deskew, num_col_classifier, img_only_regions)
# plt.imshow(img_revised_tab) # plt.imshow(img_revised_tab)
# plt.show() # plt.show()

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