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	🐛 typo: comment{,s}, fix #8
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					 2 changed files with 8 additions and 4 deletions
				
			
		|  | @ -57,7 +57,7 @@ class SbbBinarizeProcessor(Processor): | ||||||
| 
 | 
 | ||||||
|         oplevel = self.parameter['operation_level'] |         oplevel = self.parameter['operation_level'] | ||||||
|         model_path = self.parameter['model'] # pylint: disable=attribute-defined-outside-init |         model_path = self.parameter['model'] # pylint: disable=attribute-defined-outside-init | ||||||
|         binarizer = SbbBinarizer(model_dir=model_path) |         binarizer = SbbBinarizer(model_dir=model_path, logger=LOG) | ||||||
| 
 | 
 | ||||||
|         for n, input_file in enumerate(self.input_files): |         for n, input_file in enumerate(self.input_files): | ||||||
|             file_id = make_file_id(input_file, self.output_file_grp) |             file_id = make_file_id(input_file, self.output_file_grp) | ||||||
|  | @ -77,7 +77,7 @@ class SbbBinarizeProcessor(Processor): | ||||||
|                         file_id + '.IMG-BIN', |                         file_id + '.IMG-BIN', | ||||||
|                         page_id=input_file.pageId, |                         page_id=input_file.pageId, | ||||||
|                         file_grp=self.output_file_grp) |                         file_grp=self.output_file_grp) | ||||||
|                 page.add_AlternativeImage(AlternativeImageType(filename=bin_image_path, comment='%s,binarized' % page_xywh['features'])) |                 page.add_AlternativeImage(AlternativeImageType(filename=bin_image_path, comments='%s,binarized' % page_xywh['features'])) | ||||||
| 
 | 
 | ||||||
|             elif oplevel == 'region': |             elif oplevel == 'region': | ||||||
|                 regions = page.get_AllRegions(['Text', 'Table'], depth=1) |                 regions = page.get_AllRegions(['Text', 'Table'], depth=1) | ||||||
|  |  | ||||||
|  | @ -17,13 +17,16 @@ from keras.models import load_model | ||||||
| sys.stderr = stderr | sys.stderr = stderr | ||||||
| import tensorflow as tf | import tensorflow as tf | ||||||
| 
 | 
 | ||||||
|  | import logging | ||||||
|  | 
 | ||||||
| def resize_image(img_in, input_height, input_width): | def resize_image(img_in, input_height, input_width): | ||||||
|     return cv2.resize(img_in, (input_width, input_height), interpolation=cv2.INTER_NEAREST) |     return cv2.resize(img_in, (input_width, input_height), interpolation=cv2.INTER_NEAREST) | ||||||
| 
 | 
 | ||||||
| class SbbBinarizer: | class SbbBinarizer: | ||||||
| 
 | 
 | ||||||
|     def __init__(self, model_dir): |     def __init__(self, model_dir, logger=None): | ||||||
|         self.model_dir = model_dir |         self.model_dir = model_dir | ||||||
|  |         self.log = logger if logger else logging.getLogger('SbbBinarizer') | ||||||
| 
 | 
 | ||||||
|     def start_new_session(self): |     def start_new_session(self): | ||||||
|         config = tf.ConfigProto() |         config = tf.ConfigProto() | ||||||
|  | @ -193,7 +196,8 @@ class SbbBinarizer: | ||||||
|         self.start_new_session() |         self.start_new_session() | ||||||
|         list_of_model_files = listdir(self.model_dir) |         list_of_model_files = listdir(self.model_dir) | ||||||
|         img_last = 0 |         img_last = 0 | ||||||
|         for model_in in list_of_model_files: |         for n, model_in in enumerate(list_of_model_files): | ||||||
|  |             self.log.info('Predicting with model %s [%s/%s]' % (model_in, n + 1, len(list_of_model_files))) | ||||||
| 
 | 
 | ||||||
|             res = self.predict(model_in, image, use_patches) |             res = self.predict(model_in, image, use_patches) | ||||||
| 
 | 
 | ||||||
|  |  | ||||||
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