Update app.py

app.py

@@ -269,7 +269,7 @@ def interpolate(t1, t2, d1, d2, th1, th2, steps):
     latent_point_2 = encoder_model_boxes.predict(number_2_expand)[0]
 
     latent_dimensionality = len(latent_point_1)  # define the dimensionality of the latent space
-    num_interp = num_internal + 2  # the number of images to be pictured
+    num_interp = num_internal  # the number of images to be pictured
     latent_matrix = []  # This will contain the latent points of the interpolation
     for column in range(latent_dimensionality):
         new_column = np.linspace(latent_point_1[column], latent_point_2[column], num_interp)