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								changed the criteria for the best weight file ( #356 )  
							
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							* changed the criteria for the best weight file
changed the criteria for the best weight file from loss to mAP
I trained the model on my custom dataset. But I failed to get a good results when I load the weight file that has the lowest loss on test dataset. 
I thought that the loss used in YOLO is not proper criteria for detection performance. So I changed the criteria from loss to mAP.
what do you think of this?
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								update parse_model_cfg() ( #350 )  
							
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							Removing the two lines for adding batch_normalize key to convolutional layers causes the parsing of the model to break when parsing it in models.py 
							
						 
						
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								cleanup- delete a variable "yolo_layer_count" ( #347 )  
							
							
							
						 
						
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