progress print statements

app.py

@@ -121,22 +121,7 @@ def predict_and_analyze(model_name, num_channels, dim, image):
     
     '''Loads a model with activations, passes through image and shows activations
     
-    The image must be a pandas dataframe that can be made from a (C, W, H) numpy array
-    using
-    
-    m,n,r = X.shape
-    X = np.column_stack((np.repeat(np.arange(C), W), 
-                               X.reshape(C * W, -1)))
-    df = pd.DataFrame(X)
-    
-    then get the image back with 
-    
-    X = df.values
-    X = X[:, 1:]
-    X = X.reshape((C, W, W))
-    
-    image = 2d numpy array in shape (C, W*W)
-    i.e. take a C,W,W array and reshape into (C, W*W)
+    The image must be a numpy array of shape (C, W, W) or (1, C, W, W) 
     
     '''
     
@@ -165,14 +150,13 @@ def predict_and_analyze(model_name, num_channels, dim, image):
     
     model_name += '_%i' % (num_channels)
         
-        
     print("Loading model")
     model = load_model(model_name, activation=True)
+    print("Model loaded")
     
     print("Looking at activations")
     output, input_image, activation_1, activation_2 = get_activations(model, image, sub_mean=True)
-    
-    print(output)
+    print("Activations and predictions finished")
     
     if output[0] < output[1]:
         output = 'Planet predicted with %f percent confidence' % (100*output[1])