Spaces:
				
			
			
	
			
			
		Runtime error
		
	
	
	
			
			
	
	
	
	
		
		
		Runtime error
		
	Commit 
							
							Β·
						
						63317d7
	
1
								Parent(s):
							
							8b2e89d
								
Update app.py
Browse files
    	
        app.py
    CHANGED
    
    | @@ -11,20 +11,17 @@ model = from_pretrained_keras("Harveenchadha/low-light-image-enhancement", compi | |
| 11 |  | 
| 12 |  | 
| 13 | 
             
            def infer(original_image):
         | 
| 14 | 
            -
                
         | 
| 15 | 
             
                image = keras.preprocessing.image.img_to_array(original_image)
         | 
| 16 | 
             
                image = image.astype("float32") / 255.0
         | 
| 17 | 
             
                image = np.expand_dims(image, axis=0)
         | 
| 18 | 
            -
                
         | 
| 19 | 
             
                output = model.predict(image)
         | 
| 20 | 
            -
                # print(len(output))
         | 
| 21 | 
            -
                # print([len(a) for a in output])
         | 
| 22 | 
             
                output_image = output[0] * 255.0
         | 
| 23 | 
             
                output_image = output_image.clip(0, 255)
         | 
| 24 | 
             
                output_image = output_image.reshape(
         | 
| 25 | 
            -
                    (np.shape( | 
| 26 | 
             
                )
         | 
| 27 | 
             
                output_image = np.uint32(output_image)
         | 
|  | |
| 28 |  | 
| 29 | 
             
                # output_image = tf.cast((output[0, :, :, :] * 255), dtype=np.uint8)
         | 
| 30 |  | 
|  | |
| 11 |  | 
| 12 |  | 
| 13 | 
             
            def infer(original_image):
         | 
|  | |
| 14 | 
             
                image = keras.preprocessing.image.img_to_array(original_image)
         | 
| 15 | 
             
                image = image.astype("float32") / 255.0
         | 
| 16 | 
             
                image = np.expand_dims(image, axis=0)
         | 
|  | |
| 17 | 
             
                output = model.predict(image)
         | 
|  | |
|  | |
| 18 | 
             
                output_image = output[0] * 255.0
         | 
| 19 | 
             
                output_image = output_image.clip(0, 255)
         | 
| 20 | 
             
                output_image = output_image.reshape(
         | 
| 21 | 
            +
                    (np.shape(output_image)[0], np.shape(output_image)[1], 3)
         | 
| 22 | 
             
                )
         | 
| 23 | 
             
                output_image = np.uint32(output_image)
         | 
| 24 | 
            +
                return output_image
         | 
| 25 |  | 
| 26 | 
             
                # output_image = tf.cast((output[0, :, :, :] * 255), dtype=np.uint8)
         | 
| 27 |  | 

