more code formatting

eynollah/eynollah/cli.py

@@ -199,8 +199,9 @@ def main(
         ignore_page_extraction=ignore_page_extraction,
     )
     eynollah.run()
-    #pcgts = eynollah.run()
-    ##eynollah.writer.write_pagexml(pcgts)
+    # pcgts = eynollah.run()
+    # eynollah.writer.write_pagexml(pcgts)
+
 
 if __name__ == "__main__":
     main()

eynollah/eynollah/ocrd_cli.py

@@ -2,10 +2,12 @@
 from click import command
 from ocrd.decorators import ocrd_cli_options, ocrd_cli_wrap_processor
 
+
 @command()
 @ocrd_cli_options
 def main(*args, **kwargs):
     return ocrd_cli_wrap_processor(EynollahProcessor, *args, **kwargs)
 
+
 if __name__ == '__main__':
     main()

eynollah/eynollah/plot.py

@@ -9,24 +9,25 @@
 from .utils.rotate import rotate_image_different
 from .utils.resize import resize_image
 
+
 class EynollahPlotter():
     """
     Class collecting all the plotting and image writing methods
     """
 
     def __init__(
-        self,
-        *,
-        dir_out,
-        dir_of_all,
-        dir_save_page,
-        dir_of_deskewed,
-        dir_of_layout,
-        dir_of_cropped_images,
-        image_filename_stem,
-        image_org=None,
-        scale_x=1,
-        scale_y=1,
+            self,
+            *,
+            dir_out,
+            dir_of_all,
+            dir_save_page,
+            dir_of_deskewed,
+            dir_of_layout,
+            dir_of_cropped_images,
+            image_filename_stem,
+            image_org=None,
+            scale_x=1,
+            scale_y=1,
     ):
         self.dir_out = dir_out
         self.dir_of_all = dir_of_all
@@ -44,22 +45,23 @@ def save_plot_of_layout_main(self, text_regions_p, image_page):
         if self.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']
+            pixels = ['Background', 'Main text', 'Image', 'Separator', 'Marginalia']
             values_indexes = [0, 1, 2, 3, 4]
             plt.figure(figsize=(40, 40))
             plt.rcParams["font.size"] = "40"
             im = plt.imshow(text_regions_p[:, :])
             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]
+            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"))
-
 
     def save_plot_of_layout_main_all(self, text_regions_p, image_page):
         if self.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']
+            pixels = ['Background', 'Main text', 'Image', 'Separator', 'Marginalia']
             values_indexes = [0, 1, 2, 3, 4]
             plt.figure(figsize=(80, 40))
             plt.rcParams["font.size"] = "40"
@@ -68,7 +70,9 @@ def save_plot_of_layout_main_all(self, text_regions_p, image_page):
             plt.subplot(1, 2, 2)
             im = plt.imshow(text_regions_p[:, :])
             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]
+            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"))
 
@@ -82,7 +86,9 @@ def save_plot_of_layout(self, text_regions_p, image_page):
             plt.rcParams["font.size"] = "40"
             im = plt.imshow(text_regions_p[:, :])
             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]
+            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"))
 
@@ -99,7 +105,9 @@ def save_plot_of_layout_all(self, text_regions_p, image_page):
             plt.subplot(1, 2, 2)
             im = plt.imshow(text_regions_p[:, :])
             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]
+            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"))
 
@@ -115,7 +123,9 @@ def save_plot_of_textlines(self, textline_mask_tot_ea, image_page):
             plt.subplot(1, 2, 2)
             im = plt.imshow(textline_mask_tot_ea[:, :])
             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]
+            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"))
 
@@ -131,33 +141,36 @@ def save_page_image(self, image_page):
             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)
+
     def save_enhanced_image(self, img_res):
         cv2.imwrite(os.path.join(self.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:
-            plt.figure(figsize=(80,40))
-            plt.rcParams['font.size']='50'
-            plt.subplot(1,2,1)
+            plt.figure(figsize=(80, 40))
+            plt.rcParams['font.size'] = '50'
+            plt.subplot(1, 2, 1)
             plt.imshow(img_patch_org)
-            plt.subplot(1,2,2)
-            plt.plot(gaussian_filter1d(img_patch_org.sum(axis=1), 3),np.array(range(len(gaussian_filter1d(img_patch_org.sum(axis=1), 3)))),linewidth=8)
-            plt.xlabel('Density of textline prediction in direction of X axis',fontsize=60)
-            plt.ylabel('Height',fontsize=60)
-            plt.yticks([0,len(gaussian_filter1d(img_patch_org.sum(axis=1), 3))])
+            plt.subplot(1, 2, 2)
+            plt.plot(gaussian_filter1d(img_patch_org.sum(axis=1), 3),
+                     np.array(range(len(gaussian_filter1d(img_patch_org.sum(axis=1), 3)))), linewidth=8)
+            plt.xlabel('Density of textline prediction in direction of X axis', fontsize=60)
+            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.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:
-            plt.figure(figsize=(60,30))
-            plt.rcParams['font.size']='50'
-            plt.plot(angels,np.array(var_res),'-o',markersize=25,linewidth=4)
-            plt.xlabel('angle',fontsize=50)
-            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.figure(figsize=(60, 30))
+            plt.rcParams['font.size'] = '50'
+            plt.plot(angels, np.array(var_res), '-o', markersize=25, linewidth=4)
+            plt.xlabel('angle', fontsize=50)
+            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.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:
@@ -167,9 +180,9 @@ def write_images_into_directory(self, img_contours, image_page):
                 box = [x, y, w, h]
                 croped_page, page_coord = crop_image_inside_box(box, image_page)
 
-                croped_page = resize_image(croped_page, int(croped_page.shape[0] / self.scale_y), int(croped_page.shape[1] / self.scale_x))
+                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")
                 cv2.imwrite(path, croped_page)
                 index += 1
-

eynollah/eynollah/processor.py

@@ -22,6 +22,7 @@
 
 OCRD_TOOL = loads(resource_string(__name__, 'ocrd-tool.json').decode('utf8'))
 
+
 class EynollahProcessor(Processor):
 
     def __init__(self, *args, **kwargs):

eynollah/eynollah/train/build_model_load_pretrained_weights_and_save.py

@@ -1,33 +1,29 @@
 import os
 import sys
 import tensorflow as tf
-import keras , warnings
+import keras, warnings
 from keras.optimizers import *
 from sacred import Experiment
 from models import *
 from utils import *
 from metrics import *
 
 
-
-
 def configuration():
     gpu_options = tf.compat.v1.GPUOptions(allow_growth=True)
     session = tf.compat.v1.Session(config=tf.compat.v1.ConfigProto(gpu_options=gpu_options))
 
 
-if __name__=='__main__':
+if __name__ == '__main__':
     n_classes = 2
     input_height = 224
     input_width = 448
     weight_decay = 1e-6
     pretraining = False
     dir_of_weights = 'model_bin_sbb_ens.h5'
-    
-    #configuration()
-    
-    model = resnet50_unet(n_classes,  input_height, input_width,weight_decay,pretraining)
+
+    # configuration()
+
+    model = resnet50_unet(n_classes, input_height, input_width, weight_decay, pretraining)
     model.load_weights(dir_of_weights)
     model.save('./name_in_another_python_version.h5')
-
-