fixed model shape

app.py

@@ -142,15 +142,9 @@ def predict_and_analyze(model_name, num_channels, dim, image):
     #     im = f.readlines()
     # image = np.frombuffer(image)
     
-    print(image)
-    print(type(image))
-    print(image.name)
-    
     image = np.load(image.name, allow_pickle=True)
     
-    image = image.reshape((num_channels, W, W))
-    print(image)
-    print(type(image))
+    # image = image.reshape((num_channels, W, W))
     
     # W = int(np.sqrt(image.shape[1]))
     
@@ -159,6 +153,8 @@ def predict_and_analyze(model_name, num_channels, dim, image):
     if len(image.shape) != 4:
         image = image[np.newaxis, :, :, :]
         
+    assert image.shape == (1, num_channels, W, W), "Data is the wrong shape"
+        
     input_image = np.sum(image[0, :, :, :], axis=0)
     
     model_name += '_%i' % (num_channels)