|  |  |  | @ -20,7 +20,8 @@ def test(data, | 
			
		
	
		
			
				
					|  |  |  |  |          model=None, | 
			
		
	
		
			
				
					|  |  |  |  |          dataloader=None, | 
			
		
	
		
			
				
					|  |  |  |  |          fast=False, | 
			
		
	
		
			
				
					|  |  |  |  |          verbose=False): | 
			
		
	
		
			
				
					|  |  |  |  |          verbose=False, | 
			
		
	
		
			
				
					|  |  |  |  |          save_dir='.'): | 
			
		
	
		
			
				
					|  |  |  |  |     # Initialize/load model and set device | 
			
		
	
		
			
				
					|  |  |  |  |     if model is None: | 
			
		
	
		
			
				
					|  |  |  |  |         training = False | 
			
		
	
	
		
			
				
					|  |  |  | @ -28,7 +29,7 @@ def test(data, | 
			
		
	
		
			
				
					|  |  |  |  |         half = device.type != 'cpu'  # half precision only supported on CUDA | 
			
		
	
		
			
				
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 | 
			
		
	
		
			
				
					|  |  |  |  |         # Remove previous | 
			
		
	
		
			
				
					|  |  |  |  |         for f in glob.glob('test_batch*.jpg'): | 
			
		
	
		
			
				
					|  |  |  |  |         for f in glob.glob(f'{save_dir}/test_batch*.jpg'): | 
			
		
	
		
			
				
					|  |  |  |  |             os.remove(f) | 
			
		
	
		
			
				
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 | 
			
		
	
		
			
				
					|  |  |  |  |         # Load model | 
			
		
	
	
		
			
				
					|  |  |  | @ -177,9 +178,9 @@ def test(data, | 
			
		
	
		
			
				
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					|  |  |  |  |         # Plot images | 
			
		
	
		
			
				
					|  |  |  |  |         if batch_i < 1: | 
			
		
	
		
			
				
					|  |  |  |  |             f = 'test_batch%g_gt.jpg' % batch_i  # filename | 
			
		
	
		
			
				
					|  |  |  |  |             f = os.path.join(save_dir, 'test_batch%g_gt.jpg' % batch_i)  # filename | 
			
		
	
		
			
				
					|  |  |  |  |             plot_images(img, targets, paths, f, names)  # ground truth | 
			
		
	
		
			
				
					|  |  |  |  |             f = 'test_batch%g_pred.jpg' % batch_i | 
			
		
	
		
			
				
					|  |  |  |  |             f = os.path.join(save_dir,'test_batch%g_pred.jpg' % batch_i) | 
			
		
	
		
			
				
					|  |  |  |  |             plot_images(img, output_to_target(output, width, height), paths, f, names)  # predictions | 
			
		
	
		
			
				
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					|  |  |  |  |     # Compute statistics | 
			
		
	
	
		
			
				
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