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	🎨 Rename input_channels variable to network_input_channels
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					 1 changed files with 4 additions and 4 deletions
				
			
		|  | @ -48,10 +48,10 @@ class CalamariRecognize(Processor): | |||
|         checkpoints = glob(self.parameter['checkpoint']) | ||||
|         self.predictor = MultiPredictor(checkpoints=checkpoints) | ||||
| 
 | ||||
|         self.input_channels = self.predictor.predictors[0].network.input_channels | ||||
|         #self.input_channels = self.predictor.predictors[0].network_params.channels # not used! | ||||
|         self.network_input_channels = self.predictor.predictors[0].network.input_channels | ||||
|         #self.network_input_channels = self.predictor.predictors[0].network_params.channels # not used! | ||||
|         # binarization = self.predictor.predictors[0].model_params.data_preprocessor.binarization # not used! | ||||
|         # self.features = ('' if self.input_channels != 1 else | ||||
|         # self.features = ('' if self.network_input_channels != 1 else | ||||
|         #                  'binarized' if binarization != 'GRAY' else | ||||
|         #                  'grayscale_normalized') | ||||
|         self.features = '' | ||||
|  | @ -91,7 +91,7 @@ class CalamariRecognize(Processor): | |||
|                     log.debug("Recognizing line '%s' in region '%s'", line.id, region.id) | ||||
| 
 | ||||
|                     line_image, line_coords = self.workspace.image_from_segment(line, region_image, region_coords, feature_selector=self.features) | ||||
|                     if ('binarized' not in line_coords['features'] and 'grayscale_normalized' not in line_coords['features'] and self.input_channels == 1): | ||||
|                     if ('binarized' not in line_coords['features'] and 'grayscale_normalized' not in line_coords['features'] and self.network_input_channels == 1): | ||||
|                         # We cannot use a feature selector for this since we don't | ||||
|                         # know whether the model expects (has been trained on) | ||||
|                         # binarized or grayscale images; but raw images are likely | ||||
|  |  | |||
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