app update

app.py

@@ -41,9 +41,9 @@ def model_inference(image, iou_threshold=0.5, threshold=0.4, show_cam="No", tran
     output = model(transformed_image)
     # Selecting layer for gradCAM
     if target_layer == -2:
-      layer = [model.model.layers[-2]]
+      layer = [model.model.layers[-3]]
     else:
-      layer = [model.model.layers[-1]]
+      layer = [model.model.layers[-2]]
 
     cam = YoloCAM(model=model, target_layers=layer, use_cuda=False)
 
@@ -79,13 +79,13 @@ description = "Pytorch Lightning implemetation of YOLOv3 on Pascal VOC dataset.\
 #     ["images/Puppies.jpg", 0.6, 0.7, True, 0.5],
 # ]
 
-demo = gr.Interface(model_inference, inputs=[gr.Image(shape=(416, 416), label="Input an image"),
+demo = gr.Interface(model_inference, inputs=[gr.Image(label="Input an image"),
                                                                           gr.Slider(0, 1, value=0.5, label="IOU Threshold"),
                                                                           gr.Slider(0, 1, value=0.4, label="Threshold"),
                                                                           gr.Radio(["Yes", "No"], value="No"  , label="Show GradCAM outputs"),
                                                                           gr.Slider(0, 1, value=0.5, label="Opacity of GradCAM"),
-                                                                          gr.Slider(-2, -1, value=-2, step=1, label="Which Layer?")],
-                                  outputs=[gr.Gallery(rows=2, columns=1)],
+                                                                          gr.Slider(-2, -1, value=-1, step=1, label="Which Layer?")],
+                                  outputs=[gr.Gallery(rows=2, columns=1), label="Model Outputs"],
                                   title=title, description=description)
 demo.launch()