mirror of
https://github.com/qurator-spk/eynollah.git
synced 2025-06-09 20:29:55 +02:00
passing number of columns as an argument
This commit is contained in:
vahidrezanezhad
parent
2c93904985
commit
1b18ae874b
2 changed files with 91 additions and 25 deletions
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@ -191,6 +191,16 @@ def machine_based_reading_order(dir_xml, dir_out_modal_image, dir_out_classes, i
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is_flag=True,
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help="if this parameter set to true, this tool will try to do ocr",
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)
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@click.option(
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"--num_col_upper",
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"-ncu",
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help="lower limit of columns in document image",
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)
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@click.option(
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"--num_col_lower",
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"-ncl",
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help="upper limit of columns in document image",
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)
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@click.option(
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"--log_level",
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"-l",
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@ -198,7 +208,7 @@ def machine_based_reading_order(dir_xml, dir_out_modal_image, dir_out_classes, i
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help="Override log level globally to this",
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)
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def layout(image, out, dir_in, model, save_images, save_layout, save_deskewed, save_all, save_page, enable_plotting, allow_enhancement, curved_line, textline_light, full_layout, tables, right2left, input_binary, allow_scaling, headers_off, light_version, reading_order_machine_based, do_ocr, ignore_page_extraction, log_level):
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def layout(image, out, dir_in, model, save_images, save_layout, save_deskewed, save_all, save_page, enable_plotting, allow_enhancement, curved_line, textline_light, full_layout, tables, right2left, input_binary, allow_scaling, headers_off, light_version, reading_order_machine_based, do_ocr, num_col_upper, num_col_lower, ignore_page_extraction, log_level):
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if log_level:
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setOverrideLogLevel(log_level)
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initLogging()
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@ -235,6 +245,8 @@ def layout(image, out, dir_in, model, save_images, save_layout, save_deskewed, s
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ignore_page_extraction=ignore_page_extraction,
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reading_order_machine_based=reading_order_machine_based,
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do_ocr=do_ocr,
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num_col_upper=num_col_upper,
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num_col_lower=num_col_lower,
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)
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if dir_in:
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eynollah.run()
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@ -178,6 +178,8 @@ class Eynollah:
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ignore_page_extraction=False,
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reading_order_machine_based=False,
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do_ocr=False,
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num_col_upper=None,
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num_col_lower=None,
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override_dpi=None,
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logger=None,
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pcgts=None,
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@ -212,6 +214,14 @@ class Eynollah:
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self.headers_off = headers_off
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self.ignore_page_extraction = ignore_page_extraction
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self.ocr = do_ocr
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if num_col_upper:
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self.num_col_upper = int(num_col_upper)
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else:
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self.num_col_upper = num_col_upper
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if num_col_lower:
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self.num_col_lower = int(num_col_lower)
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else:
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self.num_col_lower = num_col_lower
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self.pcgts = pcgts
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if not dir_in:
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self.plotter = None if not enable_plotting else EynollahPlotter(
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@ -598,35 +608,79 @@ class Eynollah:
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img = self.imread()
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img_bin = None
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width_early = img.shape[1]
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t1 = time.time()
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_, page_coord = self.early_page_for_num_of_column_classification(img_bin)
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if not self.dir_in:
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model_num_classifier, session_col_classifier = self.start_new_session_and_model(self.model_dir_of_col_classifier)
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if self.input_binary:
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img_in = np.copy(img)
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width_early = img_in.shape[1]
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img_in = img_in / 255.0
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img_in = cv2.resize(img_in, (448, 448), interpolation=cv2.INTER_NEAREST)
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img_in = img_in.reshape(1, 448, 448, 3)
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if self.num_col_upper and not self.num_col_lower:
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num_col = self.num_col_upper
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label_p_pred = [np.ones(6)]
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elif self.num_col_lower and not self.num_col_upper:
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num_col = self.num_col_lower
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label_p_pred = [np.ones(6)]
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elif (not self.num_col_upper and not self.num_col_lower):
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if self.input_binary:
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img_in = np.copy(img)
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img_in = img_in / 255.0
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img_in = cv2.resize(img_in, (448, 448), interpolation=cv2.INTER_NEAREST)
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img_in = img_in.reshape(1, 448, 448, 3)
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else:
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img_1ch = self.imread(grayscale=True)
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width_early = img_1ch.shape[1]
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img_1ch = img_1ch[page_coord[0] : page_coord[1], page_coord[2] : page_coord[3]]
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img_1ch = img_1ch / 255.0
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img_1ch = cv2.resize(img_1ch, (448, 448), interpolation=cv2.INTER_NEAREST)
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img_in = np.zeros((1, img_1ch.shape[0], img_1ch.shape[1], 3))
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img_in[0, :, :, 0] = img_1ch[:, :]
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img_in[0, :, :, 1] = img_1ch[:, :]
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img_in[0, :, :, 2] = img_1ch[:, :]
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if self.dir_in:
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label_p_pred = self.model_classifier.predict(img_in, verbose=0)
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else:
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label_p_pred = model_num_classifier.predict(img_in, verbose=0)
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num_col = np.argmax(label_p_pred[0]) + 1
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elif (self.num_col_upper and self.num_col_lower) and (self.num_col_upper!=self.num_col_lower):
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if self.input_binary:
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img_in = np.copy(img)
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img_in = img_in / 255.0
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img_in = cv2.resize(img_in, (448, 448), interpolation=cv2.INTER_NEAREST)
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img_in = img_in.reshape(1, 448, 448, 3)
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else:
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img_1ch = self.imread(grayscale=True)
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width_early = img_1ch.shape[1]
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img_1ch = img_1ch[page_coord[0] : page_coord[1], page_coord[2] : page_coord[3]]
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img_1ch = img_1ch / 255.0
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img_1ch = cv2.resize(img_1ch, (448, 448), interpolation=cv2.INTER_NEAREST)
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img_in = np.zeros((1, img_1ch.shape[0], img_1ch.shape[1], 3))
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img_in[0, :, :, 0] = img_1ch[:, :]
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img_in[0, :, :, 1] = img_1ch[:, :]
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img_in[0, :, :, 2] = img_1ch[:, :]
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if self.dir_in:
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label_p_pred = self.model_classifier.predict(img_in, verbose=0)
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else:
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label_p_pred = model_num_classifier.predict(img_in, verbose=0)
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num_col = np.argmax(label_p_pred[0]) + 1
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if num_col > self.num_col_upper:
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num_col = self.num_col_upper
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label_p_pred = [np.ones(6)]
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if num_col < self.num_col_lower:
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num_col = self.num_col_lower
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label_p_pred = [np.ones(6)]
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else:
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img_1ch = self.imread(grayscale=True)
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width_early = img_1ch.shape[1]
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img_1ch = img_1ch[page_coord[0] : page_coord[1], page_coord[2] : page_coord[3]]
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num_col = self.num_col_upper
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label_p_pred = [np.ones(6)]
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img_1ch = img_1ch / 255.0
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img_1ch = cv2.resize(img_1ch, (448, 448), interpolation=cv2.INTER_NEAREST)
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img_in = np.zeros((1, img_1ch.shape[0], img_1ch.shape[1], 3))
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img_in[0, :, :, 0] = img_1ch[:, :]
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img_in[0, :, :, 1] = img_1ch[:, :]
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img_in[0, :, :, 2] = img_1ch[:, :]
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if self.dir_in:
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label_p_pred = self.model_classifier.predict(img_in, verbose=0)
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else:
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label_p_pred = model_num_classifier.predict(img_in, verbose=0)
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num_col = np.argmax(label_p_pred[0]) + 1
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self.logger.info("Found %d columns (%s)", num_col, np.around(label_p_pred, decimals=5))
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