Update app.py

app.py

@@ -34,11 +34,11 @@ classes = ('plane', 'car', 'bird', 'cat', 'deer',
 def inference(input_img, see_misclassified=False,num_misclassified_imgs=0,see_gradcam=False,num_gradcam_imgs=0,transparency = 0.85, target_layer_number = -1,top_classes=3):
 
     if see_misclassified: # show misclassified images
-      org_img   =  np.asarray(Image.open('img_eg_0.jpg'))
+      org_img   =  np.asarray(Image.open('misclassified_images/mis_eg_0.jpg'))
       input_img = org_img
 
     elif num_gradcam_imgs > 0: # show gradcam on example images
-      org_img   =  np.asarray(Image.open('img_eg_0.jpg'))
+      org_img   =  np.asarray(Image.open('examples/car.jpg'))
       input_img = org_img
 
     else: # nothing chosen - misclassified or gradcam