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	cnnrnn Ocr: width of input textline image can not be zero!
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					 1 changed files with 5 additions and 1 deletions
				
			
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					@ -4981,7 +4981,7 @@ class Eynollah_ocr:
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            self.model_ocr.to(self.device)
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					            self.model_ocr.to(self.device)
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        else:
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					        else:
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            self.model_ocr_dir = dir_models + "/model_step_50000_ocr"#"/model_0_ocr_cnnrnn"#"/model_23_ocr_cnnrnn"
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					            self.model_ocr_dir = dir_models + "/model_step_150000_ocr"#"/model_0_ocr_cnnrnn"#"/model_23_ocr_cnnrnn"
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            model_ocr = load_model(self.model_ocr_dir , compile=False)
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					            model_ocr = load_model(self.model_ocr_dir , compile=False)
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            self.prediction_model = tf.keras.models.Model(
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					            self.prediction_model = tf.keras.models.Model(
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					@ -5125,11 +5125,15 @@ class Eynollah_ocr:
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    def preprocess_and_resize_image_for_ocrcnn_model(self, img, image_height, image_width):
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					    def preprocess_and_resize_image_for_ocrcnn_model(self, img, image_height, image_width):
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        ratio = image_height /float(img.shape[0])
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					        ratio = image_height /float(img.shape[0])
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        w_ratio = int(ratio * img.shape[1])
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					        w_ratio = int(ratio * img.shape[1])
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        if w_ratio <= image_width:
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					        if w_ratio <= image_width:
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            width_new = w_ratio
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					            width_new = w_ratio
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        else:
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					        else:
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            width_new = image_width
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					            width_new = image_width
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					        if width_new == 0:
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					            width_new = img.shape[1]
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        img = resize_image(img, image_height, width_new)
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					        img = resize_image(img, image_height, width_new)
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        img_fin = np.ones((image_height, image_width, 3))*255
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					        img_fin = np.ones((image_height, image_width, 3))*255
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        img_fin[:,:+width_new,:] = img[:,:,:]
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					        img_fin[:,:+width_new,:] = img[:,:,:]
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