Update app.py

app.py

@@ -85,17 +85,16 @@ 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   =  cv2.imread('/content/drive/MyDrive/AI/ERA_course/session12/example_images/img_eg_0.jpg')
-    #   input_img = org_img
+    if see_misclassified: # show misclassified images
+      org_img   =  np.asarray(Image.open('img_eg_0.jpg'))
+      input_img = org_img
 
-    # elif num_gradcam_imgs > 0: # show gradcam on example images
-    #   org_img   =  cv2.imread('/content/drive/MyDrive/AI/ERA_course/session12/example_images/img_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'))
+      input_img = org_img
 
-    # else: # nothing chosen - misclassified or gradcam
-    
-    org_img = input_img
+    else: # nothing chosen - misclassified or gradcam
+        org_img = input_img
 
     # model inference
     transform = transforms.ToTensor()
@@ -139,4 +138,4 @@ demo = gr.Interface(
     description = description,
     examples = examples)
 
-demo.launch()
+demo.launch(default=True)