diff --git a/qurator/eynollah/cli.py b/qurator/eynollah/cli.py index 99bf5ac..390a762 100644 --- a/qurator/eynollah/cli.py +++ b/qurator/eynollah/cli.py @@ -2,6 +2,7 @@ import sys import click from ocrd_utils import getLogger, initLogging, setOverrideLogLevel from qurator.eynollah.eynollah import Eynollah +from qurator.eynollah.utils.dirs import EynollahDirs @click.command() @@ -176,16 +177,18 @@ def main( print('Error: You used -tll to enable light textline detection but -light is not enabled') sys.exit(1) eynollah = Eynollah( - model, + EynollahDirs( + dir_models=model, + dir_out=out, + dir_in=dir_in, + dir_of_cropped_images=save_images, + dir_of_layout=save_layout, + dir_of_deskewed=save_deskewed, + dir_of_all=save_all, + dir_save_page=save_page, + ), getLogger('Eynollah'), image_filename=image, - dir_out=out, - dir_in=dir_in, - dir_of_cropped_images=save_images, - dir_of_layout=save_layout, - dir_of_deskewed=save_deskewed, - dir_of_all=save_all, - dir_save_page=save_page, enable_plotting=enable_plotting, allow_enhancement=allow_enhancement, curved_line=curved_line, diff --git a/qurator/eynollah/eynollah.py b/qurator/eynollah/eynollah.py index cf4642c..d219df5 100644 --- a/qurator/eynollah/eynollah.py +++ b/qurator/eynollah/eynollah.py @@ -7,6 +7,7 @@ document layout analysis (segmentation) with output in PAGE-XML """ from logging import Logger +from dataclasses import dataclass import math from os import listdir from os.path import join @@ -21,6 +22,8 @@ import numpy as np from scipy.signal import find_peaks from scipy.ndimage import gaussian_filter1d +from .utils.dirs import EynollahDirs + from .utils.tf import ( PatchEncoder, Patches, @@ -85,17 +88,10 @@ class Eynollah(): def __init__( self, - dir_models : str, + dirs : EynollahDirs, logger : Logger, - image_filename : Optional[str] = None, image_pil : Optional[Image] = None, - dir_out : Optional[str] = None, - dir_in : Optional[str] = None, - dir_of_cropped_images : Optional[str] = None, - dir_of_layout : Optional[str] = None, - dir_of_deskewed : Optional[str] = None, - dir_of_all : Optional[str] = None, - dir_save_page : Optional[str] = None, + image_filename : Optional[str] = None, enable_plotting : bool = False, allow_enhancement : bool = False, curved_line : bool = False, @@ -111,7 +107,9 @@ class Eynollah(): override_dpi : Optional[int] = None, pcgts : Optional[OcrdPage] = None, ): - if not dir_in: + self.dirs = dirs + self.logger = logger + if not dirs.dir_in: if image_pil: self._imgs = self._cache_images(image_pil=image_pil) else: @@ -119,14 +117,6 @@ class Eynollah(): if override_dpi: self.dpi = override_dpi self.image_filename = image_filename - self.dir_out = dir_out - self.dir_in = dir_in - self.dir_of_all = dir_of_all - self.dir_save_page = dir_save_page - self.dir_of_deskewed = dir_of_deskewed - self.dir_of_deskewed = dir_of_deskewed - self.dir_of_cropped_images=dir_of_cropped_images - self.dir_of_layout=dir_of_layout self.enable_plotting = enable_plotting self.allow_enhancement = allow_enhancement self.curved_line = curved_line @@ -140,43 +130,37 @@ class Eynollah(): self.light_version = light_version self.ignore_page_extraction = ignore_page_extraction self.pcgts = pcgts - if not dir_in: - self.plotter = None if not enable_plotting else EynollahPlotter( - dir_out=self.dir_out, - dir_of_all=dir_of_all, - dir_save_page=dir_save_page, - dir_of_deskewed=dir_of_deskewed, - dir_of_cropped_images=dir_of_cropped_images, - dir_of_layout=dir_of_layout, - image_filename_stem=Path(Path(image_filename).name).stem) + # self.batch_mode = bool(self.dirs.dir_in) + if not dirs.dir_in: + assert self.image_filename + self.plotter = None if not self.enable_plotting else EynollahPlotter(self.dirs, image_filename_stem=Path(Path(image_filename).name).stem) self.writer = EynollahXmlWriter( - dir_out=self.dir_out, + dir_out=self.dirs.dir_out, image_filename=self.image_filename, curved_line=self.curved_line, textline_light = self.textline_light, pcgts=pcgts) - self.logger = logger - self.dir_models = dir_models - - self.model_dir_of_enhancement = dir_models + "/eynollah-enhancement_20210425" - self.model_dir_of_binarization = dir_models + "/eynollah-binarization_20210425" - self.model_dir_of_col_classifier = dir_models + "/eynollah-column-classifier_20210425" - self.model_region_dir_p = dir_models + "/eynollah-main-regions-aug-scaling_20210425" - self.model_region_dir_p2 = dir_models + "/eynollah-main-regions-aug-rotation_20210425" - self.model_region_dir_fully_np = dir_models + "/eynollah-full-regions-1column_20210425" - self.model_region_dir_fully = dir_models + "/eynollah-full-regions-3+column_20210425" - self.model_page_dir = dir_models + "/eynollah-page-extraction_20210425" - self.model_region_dir_p_ens = dir_models + "/eynollah-main-regions-ensembled_20210425" - self.model_region_dir_p_ens_light = dir_models + "/eynollah-main-regions_20220314" + + + self.model_dir_of_enhancement = dirs.dir_models + "/eynollah-enhancement_20210425" + self.model_dir_of_binarization = dirs.dir_models + "/eynollah-binarization_20210425" + self.model_dir_of_col_classifier = dirs.dir_models + "/eynollah-column-classifier_20210425" + self.model_region_dir_p = dirs.dir_models + "/eynollah-main-regions-aug-scaling_20210425" + self.model_region_dir_p2 = dirs.dir_models + "/eynollah-main-regions-aug-rotation_20210425" + self.model_region_dir_fully_np = dirs.dir_models + "/eynollah-full-regions-1column_20210425" + self.model_region_dir_fully = dirs.dir_models + "/eynollah-full-regions-3+column_20210425" + self.model_page_dir = dirs.dir_models + "/eynollah-page-extraction_20210425" + self.model_region_dir_p_ens = dirs.dir_models + "/eynollah-main-regions-ensembled_20210425" + self.model_region_dir_p_ens_light = dirs.dir_models + "/eynollah-main-regions_20220314" if self.textline_light: - self.model_textline_dir = dir_models + "/eynollah-textline_light_20210425" + self.model_textline_dir = dirs.dir_models + "/eynollah-textline_light_20210425" else: - self.model_textline_dir = dir_models + "/eynollah-textline_20210425" - self.model_tables = dir_models + "/eynollah-tables_20210319" + self.model_textline_dir = dirs.dir_models + "/eynollah-textline_20210425" + self.model_tables = dirs.dir_models + "/eynollah-tables_20210319" self.models : dict[str, tf.keras.Model] = {} - if dir_in and light_version: + if self.dirs.dir_in and light_version: config = tf.compat.v1.ConfigProto() config.gpu_options.allow_growth = True session = tf.compat.v1.Session(config=config) @@ -190,9 +174,9 @@ class Eynollah(): self.model_region_fl_np = self.our_load_model(self.model_region_dir_fully_np) self.model_region_fl = self.our_load_model(self.model_region_dir_fully) - self.ls_imgs = listdir(self.dir_in) + self.ls_imgs = listdir(self.dirs.dir_in) - if dir_in and not light_version: + if self.dirs.dir_in and not light_version: config = tf.compat.v1.ConfigProto() config.gpu_options.allow_growth = True session = tf.compat.v1.Session(config=config) @@ -208,7 +192,7 @@ class Eynollah(): self.model_region_fl = self.our_load_model(self.model_region_dir_fully) self.model_enhancement = self.our_load_model(self.model_dir_of_enhancement) - self.ls_imgs = listdir(self.dir_in) + self.ls_imgs = listdir(self.dirs.dir_in) def _cache_images(self, image_filename=None, image_pil=None): @@ -228,21 +212,14 @@ class Eynollah(): self._imgs = self._cache_images(image_filename=image_filename) self.image_filename = image_filename - self.plotter = None if not self.enable_plotting else EynollahPlotter( - dir_out=self.dir_out, - dir_of_all=self.dir_of_all, - dir_save_page=self.dir_save_page, - dir_of_deskewed=self.dir_of_deskewed, - dir_of_cropped_images=self.dir_of_cropped_images, - dir_of_layout=self.dir_of_layout, - image_filename_stem=Path(Path(image_filename).name).stem) - + self.plotter = None if not self.enable_plotting else EynollahPlotter(self.dirs, image_filename_stem=Path(Path(image_filename).name).stem) self.writer = EynollahXmlWriter( - dir_out=self.dir_out, + dir_out=self.dirs.dir_out, image_filename=self.image_filename, curved_line=self.curved_line, textline_light = self.textline_light, pcgts=self.pcgts) + def imread(self, grayscale=False, uint8=True): key = 'img' if grayscale: @@ -415,7 +392,7 @@ class Eynollah(): img = self.imread() _, page_coord = self.early_page_for_num_of_column_classification(img) - if not self.dir_in: + if not self.dirs.dir_in: model_num_classifier = self.load_model(self.model_dir_of_col_classifier) if self.input_binary: img_in = np.copy(img) @@ -439,7 +416,7 @@ class Eynollah(): img_in[0, :, :, 1] = img_1ch[:, :] img_in[0, :, :, 2] = img_1ch[:, :] - if not self.dir_in: + if not self.dirs.dir_in: label_p_pred = model_num_classifier.predict(img_in, verbose=0) else: label_p_pred = self.model_classifier.predict(img_in, verbose=0) @@ -462,7 +439,7 @@ class Eynollah(): self.logger.info("Detected %s DPI", dpi) if self.input_binary: img = self.imread() - if self.dir_in: + if self.dirs.dir_in: prediction_bin = self.do_prediction(True, img, self.model_bin) else: @@ -484,7 +461,7 @@ class Eynollah(): t1 = time.time() _, page_coord = self.early_page_for_num_of_column_classification(img_bin) - if not self.dir_in: + if not self.dirs.dir_in: model_num_classifier = self.load_model(self.model_dir_of_col_classifier) if self.input_binary: @@ -506,7 +483,7 @@ class Eynollah(): img_in[0, :, :, 2] = img_1ch[:, :] - if self.dir_in: + if self.dirs.dir_in: label_p_pred = self.model_classifier.predict(img_in, verbose=0) else: label_p_pred = model_num_classifier.predict(img_in, verbose=0) @@ -896,10 +873,10 @@ class Eynollah(): if not self.ignore_page_extraction: img = cv2.GaussianBlur(self.image, (5, 5), 0) - if not self.dir_in: + if not self.dirs.dir_in: model_page = self.load_model(self.model_page_dir) - if not self.dir_in: + if not self.dirs.dir_in: img_page_prediction = self.do_prediction(False, img, model_page) else: img_page_prediction = self.do_prediction(False, img, self.model_page) @@ -944,11 +921,11 @@ class Eynollah(): img = img.astype(np.uint8) else: img = self.imread() - if not self.dir_in: + if not self.dirs.dir_in: model_page = self.load_model(self.model_page_dir) img = cv2.GaussianBlur(img, (5, 5), 0) - if self.dir_in: + if self.dirs.dir_in: img_page_prediction = self.do_prediction(False, img, self.model_page) else: img_page_prediction = self.do_prediction(False, img, model_page) @@ -977,7 +954,7 @@ class Eynollah(): self.logger.debug("enter extract_text_regions") img_height_h = img.shape[0] img_width_h = img.shape[1] - if not self.dir_in: + if not self.dirs.dir_in: model_region = self.load_model(self.model_region_dir_fully if patches else self.model_region_dir_fully_np) else: model_region = self.model_region_fl if patches else self.model_region_fl_np @@ -1444,19 +1421,19 @@ class Eynollah(): def textline_contours(self, img, patches, scaler_h, scaler_w): self.logger.debug('enter textline_contours') - if not self.dir_in: + if not self.dirs.dir_in: model_textline = self.load_model(self.model_textline_dir if patches else self.model_textline_dir_np) img = img.astype(np.uint8) img_org = np.copy(img) img_h = img_org.shape[0] img_w = img_org.shape[1] img = resize_image(img_org, int(img_org.shape[0] * scaler_h), int(img_org.shape[1] * scaler_w)) - if not self.dir_in: + if not self.dirs.dir_in: prediction_textline = self.do_prediction(patches, img, model_textline) else: prediction_textline = self.do_prediction(patches, img, self.model_textline) prediction_textline = resize_image(prediction_textline, img_h, img_w) - if not self.dir_in: + if not self.dirs.dir_in: prediction_textline_longshot = self.do_prediction(False, img, model_textline) else: prediction_textline_longshot = self.do_prediction(False, img, self.model_textline) @@ -1502,6 +1479,7 @@ class Eynollah(): q.put(slopes_sub) poly.put(poly_sub) box_sub.put(boxes_sub_new) + def get_regions_light_v(self,img,is_image_enhanced, num_col_classifier): self.logger.debug("enter get_regions_light_v") erosion_hurts = False @@ -1536,7 +1514,7 @@ class Eynollah(): img_h_new = int(img_org.shape[0] / float(img_org.shape[1]) * img_w_new) img_resized = resize_image(img,img_h_new, img_w_new ) - if not self.dir_in: + if not self.dirs.dir_in: model_bin = self.load_model(self.model_dir_of_binarization) prediction_bin = self.do_prediction(True, img_resized, model_bin) else: @@ -1555,7 +1533,7 @@ class Eynollah(): textline_mask_tot_ea = self.run_textline(img_bin) - if not self.dir_in: + if not self.dirs.dir_in: model_region = self.load_model(self.model_region_dir_p_ens_light) prediction_regions_org = self.do_prediction_new_concept(True, img_bin, model_region) else: @@ -1600,14 +1578,14 @@ class Eynollah(): img_height_h = img_org.shape[0] img_width_h = img_org.shape[1] - if not self.dir_in: + if not self.dirs.dir_in: model_region = self.load_model(self.model_region_dir_p_ens) ratio_y=1.3 ratio_x=1 img = resize_image(img_org, int(img_org.shape[0]*ratio_y), int(img_org.shape[1]*ratio_x)) - if not self.dir_in: + if not self.dirs.dir_in: prediction_regions_org_y = self.do_prediction(True, img, model_region) else: prediction_regions_org_y = self.do_prediction(True, img, self.model_region) @@ -1629,7 +1607,7 @@ class Eynollah(): img = resize_image(img_org, int(img_org.shape[0]), int(img_org.shape[1]*(1.2 if is_image_enhanced else 1))) - if self.dir_in: + if self.dirs.dir_in: prediction_regions_org = self.do_prediction(True, img, self.model_region) else: prediction_regions_org = self.do_prediction(True, img, model_region) @@ -1639,12 +1617,12 @@ class Eynollah(): prediction_regions_org[(prediction_regions_org[:,:]==1) & (mask_zeros_y[:,:]==1)]=0 - if not self.dir_in: + if not self.dirs.dir_in: model_region = self.load_model(self.model_region_dir_p2) img = resize_image(img_org, int(img_org.shape[0]), int(img_org.shape[1])) - if self.dir_in: + if self.dirs.dir_in: prediction_regions_org2 = self.do_prediction(True, img, self.model_region_p2, 0.2) else: prediction_regions_org2 = self.do_prediction(True, img, model_region, 0.2) @@ -1678,7 +1656,7 @@ class Eynollah(): if self.input_binary: prediction_bin = np.copy(img_org) else: - if not self.dir_in: + if not self.dirs.dir_in: model_bin = self.load_model(self.model_dir_of_binarization) prediction_bin = self.do_prediction(True, img_org, model_bin) else: @@ -1691,7 +1669,7 @@ class Eynollah(): prediction_bin =np.repeat(prediction_bin[:, :, np.newaxis], 3, axis=2) - if not self.dir_in: + if not self.dirs.dir_in: model_region = self.load_model(self.model_region_dir_p_ens) ratio_y=1 ratio_x=1 @@ -1699,7 +1677,7 @@ class Eynollah(): img = resize_image(prediction_bin, int(img_org.shape[0]*ratio_y), int(img_org.shape[1]*ratio_x)) - if not self.dir_in: + if not self.dirs.dir_in: prediction_regions_org = self.do_prediction(True, img, model_region) else: prediction_regions_org = self.do_prediction(True, img, self.model_region) @@ -1731,7 +1709,7 @@ class Eynollah(): if self.input_binary: prediction_bin = np.copy(img_org) - if not self.dir_in: + if not self.dirs.dir_in: model_bin = self.load_model(self.model_dir_of_binarization) prediction_bin = self.do_prediction(True, img_org, model_bin) else: @@ -1746,7 +1724,7 @@ class Eynollah(): prediction_bin =np.repeat(prediction_bin[:, :, np.newaxis], 3, axis=2) - if not self.dir_in: + if not self.dirs.dir_in: model_region = self.load_model(self.model_region_dir_p_ens) else: @@ -1756,7 +1734,7 @@ class Eynollah(): img = resize_image(prediction_bin, int(img_org.shape[0]*ratio_y), int(img_org.shape[1]*ratio_x)) - if not self.dir_in: + if not self.dirs.dir_in: prediction_regions_org = self.do_prediction(True, img, model_region) else: prediction_regions_org = self.do_prediction(True, img, self.model_region) @@ -2755,13 +2733,13 @@ class Eynollah(): t0_tot = time.time() - if not self.dir_in: + if not self.dirs.dir_in: self.ls_imgs = [1] for img_name in self.ls_imgs: t0 = time.time() - if self.dir_in: - self.reset_file_name_dir(join(self.dir_in,img_name)) + if self.dirs.dir_in: + self.reset_file_name_dir(join(self.dirs.dir_in,img_name)) img_res, is_image_enhanced, num_col_classifier, num_column_is_classified = self.run_enhancement(self.light_version) self.logger.info("Enhancing took %.1fs ", time.time() - t0) @@ -2789,7 +2767,7 @@ class Eynollah(): self.logger.info("No columns detected, outputting an empty PAGE-XML") pcgts = self.writer.build_pagexml_no_full_layout([], page_coord, [], [], [], [], [], [], [], [], [], [], cont_page, [], []) self.logger.info("Job done in %.1fs", time.time() - t1) - if self.dir_in: + if self.dirs.dir_in: self.writer.write_pagexml(pcgts) continue else: @@ -3017,7 +2995,7 @@ class Eynollah(): pcgts = self.writer.build_pagexml_full_layout(contours_only_text_parent, contours_only_text_parent_h, page_coord, order_text_new, id_of_texts_tot, all_found_textline_polygons, all_found_textline_polygons_h, all_box_coord, all_box_coord_h, polygons_of_images, contours_tables, polygons_of_drop_capitals, polygons_of_marginals, all_found_textline_polygons_marginals, all_box_coord_marginals, slopes, slopes_h, slopes_marginals, cont_page, polygons_lines_xml) self.logger.info("Job done in %.1fs", time.time() - t0) - if not self.dir_in: + if not self.dirs.dir_in: return pcgts else: contours_only_text_parent_h = None @@ -3028,11 +3006,11 @@ class Eynollah(): order_text_new, id_of_texts_tot = self.do_order_of_regions(contours_only_text_parent_d_ordered, contours_only_text_parent_h, boxes_d, textline_mask_tot_d) pcgts = self.writer.build_pagexml_no_full_layout(txt_con_org, page_coord, order_text_new, id_of_texts_tot, all_found_textline_polygons, all_box_coord, polygons_of_images, polygons_of_marginals, all_found_textline_polygons_marginals, all_box_coord_marginals, slopes, slopes_marginals, cont_page, polygons_lines_xml, contours_tables) self.logger.info("Job done in %.1fs", time.time() - t0) - if not self.dir_in: + if not self.dirs.dir_in: return pcgts - if self.dir_in: + if self.dirs.dir_in: self.writer.write_pagexml(pcgts) #self.logger.info("Job done in %.1fs", time.time() - t0) - if self.dir_in: + if self.dirs.dir_in: self.logger.info("All jobs done in %.1fs", time.time() - t0_tot) diff --git a/qurator/eynollah/plot.py b/qurator/eynollah/plot.py index b01fc04..1f7a304 100644 --- a/qurator/eynollah/plot.py +++ b/qurator/eynollah/plot.py @@ -8,6 +8,7 @@ from scipy.ndimage import gaussian_filter1d from .utils import crop_image_inside_box from .utils.rotate import rotate_image_different from .utils.resize import resize_image +from .utils.dirs import EynollahDirs class EynollahPlotter(): """ @@ -17,23 +18,13 @@ class EynollahPlotter(): def __init__( self, *, - dir_out, - dir_of_all, - dir_save_page, - dir_of_deskewed, - dir_of_layout, - dir_of_cropped_images, + dirs : EynollahDirs, image_filename_stem, image_org=None, scale_x=1, scale_y=1, ): - self.dir_out = dir_out - self.dir_of_all = dir_of_all - self.dir_save_page = dir_save_page - self.dir_of_layout = dir_of_layout - self.dir_of_cropped_images = dir_of_cropped_images - self.dir_of_deskewed = dir_of_deskewed + self.dirs = dirs self.image_filename_stem = image_filename_stem # XXX TODO hacky these cannot be set at init time self.image_org = image_org @@ -41,7 +32,7 @@ class EynollahPlotter(): self.scale_y = scale_y def save_plot_of_layout_main(self, text_regions_p, image_page): - if self.dir_of_layout is not None: + if self.dirs.dir_of_layout is not None: values = np.unique(text_regions_p[:, :]) # pixels=['Background' , 'Main text' , 'Heading' , 'Marginalia' ,'Drop capitals' , 'Images' , 'Seperators' , 'Tables', 'Graphics'] pixels=['Background' , 'Main text' , 'Image' , 'Separator','Marginalia'] @@ -52,11 +43,11 @@ class EynollahPlotter(): colors = [im.cmap(im.norm(value)) for value in values] patches = [mpatches.Patch(color=colors[np.where(values == i)[0][0]], label="{l}".format(l=pixels[int(np.where(values_indexes == i)[0][0])])) for i in values] plt.legend(handles=patches, bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.0, fontsize=40) - plt.savefig(os.path.join(self.dir_of_layout, self.image_filename_stem + "_layout_main.png")) + plt.savefig(os.path.join(self.dirs.dir_of_layout, self.image_filename_stem + "_layout_main.png")) def save_plot_of_layout_main_all(self, text_regions_p, image_page): - if self.dir_of_all is not None: + if self.dirs.dir_of_all is not None: values = np.unique(text_regions_p[:, :]) # pixels=['Background' , 'Main text' , 'Heading' , 'Marginalia' ,'Drop capitals' , 'Images' , 'Seperators' , 'Tables', 'Graphics'] pixels=['Background' , 'Main text' , 'Image' , 'Separator','Marginalia'] @@ -70,10 +61,10 @@ class EynollahPlotter(): colors = [im.cmap(im.norm(value)) for value in values] patches = [mpatches.Patch(color=colors[np.where(values == i)[0][0]], label="{l}".format(l=pixels[int(np.where(values_indexes == i)[0][0])])) for i in values] plt.legend(handles=patches, bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.0, fontsize=60) - plt.savefig(os.path.join(self.dir_of_all, self.image_filename_stem + "_layout_main_and_page.png")) + plt.savefig(os.path.join(self.dirs.dir_of_all, self.image_filename_stem + "_layout_main_and_page.png")) def save_plot_of_layout(self, text_regions_p, image_page): - if self.dir_of_layout is not None: + if self.dirs.dir_of_layout is not None: values = np.unique(text_regions_p[:, :]) # pixels=['Background' , 'Main text' , 'Heading' , 'Marginalia' ,'Drop capitals' , 'Images' , 'Seperators' , 'Tables', 'Graphics'] pixels = ["Background", "Main text", "Header", "Marginalia", "Drop capital", "Image", "Separator", "Tables"] @@ -84,10 +75,10 @@ class EynollahPlotter(): colors = [im.cmap(im.norm(value)) for value in values] patches = [mpatches.Patch(color=colors[np.where(values == i)[0][0]], label="{l}".format(l=pixels[int(np.where(values_indexes == i)[0][0])])) for i in values] plt.legend(handles=patches, bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.0, fontsize=40) - plt.savefig(os.path.join(self.dir_of_layout, self.image_filename_stem + "_layout.png")) + plt.savefig(os.path.join(self.dirs.dir_of_layout, self.image_filename_stem + "_layout.png")) def save_plot_of_layout_all(self, text_regions_p, image_page): - if self.dir_of_all is not None: + if self.dirs.dir_of_all is not None: values = np.unique(text_regions_p[:, :]) # pixels=['Background' , 'Main text' , 'Heading' , 'Marginalia' ,'Drop capitals' , 'Images' , 'Seperators' , 'Tables', 'Graphics'] pixels = ["Background", "Main text", "Header", "Marginalia", "Drop capital", "Image", "Separator", "Tables"] @@ -101,10 +92,10 @@ class EynollahPlotter(): colors = [im.cmap(im.norm(value)) for value in values] patches = [mpatches.Patch(color=colors[np.where(values == i)[0][0]], label="{l}".format(l=pixels[int(np.where(values_indexes == i)[0][0])])) for i in values] plt.legend(handles=patches, bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.0, fontsize=60) - plt.savefig(os.path.join(self.dir_of_all, self.image_filename_stem + "_layout_and_page.png")) + plt.savefig(os.path.join(self.dirs.dir_of_all, self.image_filename_stem + "_layout_and_page.png")) def save_plot_of_textlines(self, textline_mask_tot_ea, image_page): - if self.dir_of_all is not None: + if self.dirs.dir_of_all is not None: values = np.unique(textline_mask_tot_ea[:, :]) pixels = ["Background", "Textlines"] values_indexes = [0, 1] @@ -117,25 +108,25 @@ class EynollahPlotter(): colors = [im.cmap(im.norm(value)) for value in values] patches = [mpatches.Patch(color=colors[np.where(values == i)[0][0]], label="{l}".format(l=pixels[int(np.where(values_indexes == i)[0][0])])) for i in values] plt.legend(handles=patches, bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.0, fontsize=60) - plt.savefig(os.path.join(self.dir_of_all, self.image_filename_stem + "_textline_and_page.png")) + plt.savefig(os.path.join(self.dirs.dir_of_all, self.image_filename_stem + "_textline_and_page.png")) def save_deskewed_image(self, slope_deskew): - if self.dir_of_all is not None: - cv2.imwrite(os.path.join(self.dir_of_all, self.image_filename_stem + "_org.png"), self.image_org) - if self.dir_of_deskewed is not None: + if self.dirs.dir_of_all is not None: + cv2.imwrite(os.path.join(self.dirs.dir_of_all, self.image_filename_stem + "_org.png"), self.image_org) + if self.dirs.dir_of_deskewed is not None: img_rotated = rotate_image_different(self.image_org, slope_deskew) - cv2.imwrite(os.path.join(self.dir_of_deskewed, self.image_filename_stem + "_deskewed.png"), img_rotated) + cv2.imwrite(os.path.join(self.dirs.dir_of_deskewed, self.image_filename_stem + "_deskewed.png"), img_rotated) def save_page_image(self, image_page): - if self.dir_of_all is not None: - cv2.imwrite(os.path.join(self.dir_of_all, self.image_filename_stem + "_page.png"), image_page) - if self.dir_save_page is not None: - cv2.imwrite(os.path.join(self.dir_save_page, self.image_filename_stem + "_page.png"), image_page) + if self.dirs.dir_of_all is not None: + cv2.imwrite(os.path.join(self.dirs.dir_of_all, self.image_filename_stem + "_page.png"), image_page) + if self.dirs.dir_save_page is not None: + cv2.imwrite(os.path.join(self.dirs.dir_save_page, self.image_filename_stem + "_page.png"), image_page) def save_enhanced_image(self, img_res): - cv2.imwrite(os.path.join(self.dir_out, self.image_filename_stem + "_enhanced.png"), img_res) + cv2.imwrite(os.path.join(self.dirs.dir_out, self.image_filename_stem + "_enhanced.png"), img_res) def save_plot_of_textline_density(self, img_patch_org): - if self.dir_of_all is not None: + if self.dirs.dir_of_all is not None: plt.figure(figsize=(80,40)) plt.rcParams['font.size']='50' plt.subplot(1,2,1) @@ -146,10 +137,10 @@ class EynollahPlotter(): plt.ylabel('Height',fontsize=60) plt.yticks([0,len(gaussian_filter1d(img_patch_org.sum(axis=1), 3))]) plt.gca().invert_yaxis() - plt.savefig(os.path.join(self.dir_of_all, self.image_filename_stem+'_density_of_textline.png')) + plt.savefig(os.path.join(self.dirs.dir_of_all, self.image_filename_stem+'_density_of_textline.png')) def save_plot_of_rotation_angle(self, angels, var_res): - if self.dir_of_all is not None: + if self.dirs.dir_of_all is not None: plt.figure(figsize=(60,30)) plt.rcParams['font.size']='50' plt.plot(angels,np.array(var_res),'-o',markersize=25,linewidth=4) @@ -157,10 +148,10 @@ class EynollahPlotter(): plt.ylabel('variance of sum of rotated textline in direction of x axis',fontsize=50) plt.plot(angels[np.argmax(var_res)],var_res[np.argmax(np.array(var_res))] ,'*',markersize=50,label='Angle of deskewing=' +str("{:.2f}".format(angels[np.argmax(var_res)]))+r'$\degree$') plt.legend(loc='best') - plt.savefig(os.path.join(self.dir_of_all, self.image_filename_stem+'_rotation_angle.png')) + plt.savefig(os.path.join(self.dirs.dir_of_all, self.image_filename_stem+'_rotation_angle.png')) def write_images_into_directory(self, img_contours, image_page): - if self.dir_of_cropped_images is not None: + if self.dirs.dir_of_cropped_images is not None: index = 0 for cont_ind in img_contours: x, y, w, h = cv2.boundingRect(cont_ind) @@ -169,7 +160,7 @@ class EynollahPlotter(): croped_page = resize_image(croped_page, int(croped_page.shape[0] / self.scale_y), int(croped_page.shape[1] / self.scale_x)) - path = os.path.join(self.dir_of_cropped_images, self.image_filename_stem + "_" + str(index) + ".jpg") + path = os.path.join(self.dirs.dir_of_cropped_images, self.image_filename_stem + "_" + str(index) + ".jpg") cv2.imwrite(path, croped_page) index += 1 diff --git a/qurator/eynollah/processor.py b/qurator/eynollah/processor.py index 304524a..97ad61b 100644 --- a/qurator/eynollah/processor.py +++ b/qurator/eynollah/processor.py @@ -3,6 +3,8 @@ from ocrd.processor.ocrd_page_result import OcrdPageResult from ocrd_models import OcrdPage from ocrd import Processor +from qurator.eynollah.utils.dirs import EynollahDirs + from .eynollah import Eynollah class EynollahProcessor(Processor): @@ -20,7 +22,9 @@ class EynollahProcessor(Processor): # page_image, _, _ = self.workspace.image_from_page(page, page_id, feature_filter='binarized') image_filename = self.workspace.download_file(next(self.workspace.mets.find_files(local_filename=page.imageFilename))).local_filename Eynollah( - self.resolve_resource(self.parameter['models']), + EynollahDirs( + dir_models=self.resolve_resource(self.parameter['models']), + ), self.logger, allow_enhancement=self.parameter['allow_enhancement'], curved_line=self.parameter['curved_line'], diff --git a/qurator/eynollah/utils/dirs.py b/qurator/eynollah/utils/dirs.py new file mode 100644 index 0000000..a6d10bf --- /dev/null +++ b/qurator/eynollah/utils/dirs.py @@ -0,0 +1,19 @@ +from dataclasses import dataclass +from typing import Optional + + +@dataclass() +class EynollahDirs(): + """ + Wrapper for all the dir_ kwargs everywhere + """ + dir_models : str + dir_out : Optional[str] = None + dir_in : Optional[str] = None + dir_of_cropped_images : Optional[str] = None + dir_of_layout : Optional[str] = None + dir_of_deskewed : Optional[str] = None + dir_of_all : Optional[str] = None + dir_save_page : Optional[str] = None + + diff --git a/qurator/eynollah/writer.py b/qurator/eynollah/writer.py index f537f65..72d9280 100644 --- a/qurator/eynollah/writer.py +++ b/qurator/eynollah/writer.py @@ -2,6 +2,9 @@ # pylint: disable=import-error from pathlib import Path import os.path +from typing import Optional + +from ocrd_models import OcrdPage from .utils.xml import create_page_xml, xml_reading_order from .utils.counter import EynollahIdCounter @@ -22,7 +25,15 @@ import numpy as np class EynollahXmlWriter(): - def __init__(self, *, dir_out, image_filename, curved_line,textline_light, pcgts=None): + def __init__( + self, + *, + image_filename : str, + dir_out : Optional[str], + curved_line : bool, + textline_light : bool, + pcgts : Optional[OcrdPage] = None + ): self.logger = getLogger('eynollah.writer') self.counter = EynollahIdCounter() self.dir_out = dir_out