Update app.py

app.py

@@ -29,63 +29,104 @@ def double_res(input_image):
     np.copyto(expanded_input_image[0:input_height, 0:input_width], input_image)
 
     output_image = np.zeros((128*height*2, 128*width*2, 3), dtype=np.float32)
-
+    
+    to_predict = []
     for i in range(height):
         for j in range(width):
             temp_slice = expanded_input_image[i *
                                               128:(i+1)*128, j*128:(j+1)*128]/255
-            upsampled_slice = model.predict(temp_slice[np.newaxis, ...])
-            np.copyto(output_image[i*256:(i+1)*256, j *
-                      256:(j+1)*256], upsampled_slice[0])
+            to_predict.append(temp_slice)
+
+# removing inner borders
+
+    for i in range(height):
+        for j in range(width):        
             if i != 0 and j != 0 and i != height-1 and j != width-1:
-                # removing inner borders
                 right_slice = expanded_input_image[i *
                                                    128:(i+1)*128, (j+1)*128-64:(j+1)*128+64]/255
-                right_upsampled_slice = model.predict(
-                    right_slice[np.newaxis, ...])
-                resized_right_slice = right_upsampled_slice[0][64:192, 64:192]
-                np.copyto(output_image[i*256+64:(i+1)*256-64,
-                          (j+1)*256-64:(j+1)*256+64], resized_right_slice)
+                to_predict.append(right_slice)
+    
 
                 left_slice = expanded_input_image[i *
                                                   128:(i+1)*128, j*128-64:(j)*128+64]/255
-                left_upsampled_slice = model.predict(
-                    left_slice[np.newaxis, ...])
-                resized_left_slice = left_upsampled_slice[0][64:192, 64:192]
-                np.copyto(output_image[i*256+64:(i+1)*256-64,
-                          j*256-64:j*256+64], resized_left_slice)
+                to_predict.append(left_slice)
+    
 
                 upper_slice = expanded_input_image[(
                     i+1)*128-64:(i+1)*128+64, j*128:(j+1)*128]/255
-                upper_upsampled_slice = model.predict(
-                    upper_slice[np.newaxis, ...])
-                resized_upper_slice = upper_upsampled_slice[0][64:192, 64:192]
-                np.copyto(output_image[(i+1)*256-64:(i+1)*256+64,
-                          j*256+64:(j+1)*256-64], resized_upper_slice)
+                to_predict.append(upper_slice)
+                
 
                 lower_slice = expanded_input_image[i *
                                                    128-64:i*128+64, j*128:(j+1)*128]/255
-                lower_upsampled_slice = model.predict(
-                    lower_slice[np.newaxis, ...])
-                resized_lower_slice = lower_upsampled_slice[0][64:192, 64:192]
+                to_predict.append(lower_slice)
+    # removing angles
+
+                lower_right_slice = expanded_input_image[i *
+                                                         128-64:i*128+64, (j+1)*128-64:(j+1)*128+64]/255
+                to_predict.append(lower_right_slice)
+
+                lower_left_slice = expanded_input_image[i *
+                                                        128-64:i*128+64, j*128-64:j*128+64]/255
+                to_predict.append(lower_left_slice)
+                
+# predicting all images at once    
+    predicted = model.predict(np.array(to_predict))
+    counter = 0
+    for i in range(height):
+        for j in range(width):
+            np.copyto(output_image[i*256:(i+1)*256, j *
+                      256:(j+1)*256], predicted[counter])
+            counter+=1
+    
+                
+
+    for i in range(height):
+        for j in range(width):        
+            if i != 0 and j != 0 and i != height-1 and j != width-1:            
+                right_upsampled_slice = predicted[counter]
+                counter+=1
+                resized_right_slice = right_upsampled_slice[64:192, 64:192]
+                np.copyto(output_image[i*256+64:(i+1)*256-64,
+                          (j+1)*256-64:(j+1)*256+64], resized_right_slice)
+    
+                
+    
+
+                left_upsampled_slice = predicted[counter]
+                counter+=1
+                resized_left_slice = left_upsampled_slice[64:192, 64:192]
+                np.copyto(output_image[i*256+64:(i+1)*256-64,
+                          j*256-64:j*256+64], resized_left_slice)
+                
+    
+
+                upper_upsampled_slice = predicted[counter]
+                counter+=1
+                resized_upper_slice = upper_upsampled_slice[64:192, 64:192]
+                np.copyto(output_image[(i+1)*256-64:(i+1)*256+64,
+                          j*256+64:(j+1)*256-64], resized_upper_slice)
+                
+    
+
+                lower_upsampled_slice = predicted[counter]
+                counter+=1
+                resized_lower_slice = lower_upsampled_slice[64:192, 64:192]
                 np.copyto(output_image[i*256-64:i*256+64,
                           j*256+64:(j+1)*256-64], resized_lower_slice)
 
 
-# removing angles
-                lower_right_slice = expanded_input_image[i *
-                                                         128-64:i*128+64, (j+1)*128-64:(j+1)*128+64]/255
-                lower_right_upsampled_slice = model.predict(
-                    lower_right_slice[np.newaxis, ...])
-                resized_lower_right_slice = lower_right_upsampled_slice[0][64:192, 64:192]
+
+                lower_right_upsampled_slice = predicted[counter]
+                counter+=1
+                resized_lower_right_slice = lower_right_upsampled_slice[64:192, 64:192]        
                 np.copyto(output_image[i*256-64:i*256+64,  (j+1)
                           * 256-64:(j+1)*256+64], resized_lower_right_slice)
 
-                lower_left_slice = expanded_input_image[i *
-                                                        128-64:i*128+64, j*128-64:j*128+64]/255
-                lower_left_upsampled_slice = model.predict(
-                    lower_left_slice[np.newaxis, ...])
-                resized_lower_left_slice = lower_left_upsampled_slice[0][64:192, 64:192]
+
+                lower_left_upsampled_slice = predicted[counter]
+                counter+=1
+                resized_lower_left_slice = lower_left_upsampled_slice[64:192, 64:192]
                 np.copyto(
                     output_image[i*256-64:i*256+64,  j*256-64:j*256+64], resized_lower_left_slice)