Update app.py

app.py

@@ -17,9 +17,9 @@ def load_from_pkl(load_path):
 
 Image_3D = None
 Current_name = None
-ALL_message = load_from_pkl(r'./label0601.pkl')
+ALL_message = load_from_pkl(r'.\label0601.pkl')
 
-Model_Paht = r'./model_epoch62.pth.tar'
+Model_Paht = r'.\model_epoch62.pth.tar'
 checkpoint = torch.load(Model_Paht, map_location='cpu')
 
 classnet = resnet50(
@@ -304,11 +304,19 @@ class App:
 
             gr.Markdown('''# Examples''')
             gr.Examples(
-                examples=[[os.path.join(os.path.dirname(__file__), "155086_A_R_MRI.nii.gz"), os.path.join(os.path.dirname(__file__), "155086_A_R_ROI.nii.gz")],
-                          [os.path.join(os.path.dirname(__file__), "4077798_A_L_MRI.nii.gz"), os.path.join(os.path.dirname(__file__), "4077798_A_L_ROI.nii.gz")]],
-                inputs=[[inp,inp2],[inp,inp2]],
-                outputs=[[[out1, out2, out3, slider1, slider2, slider3,out8],out9],[[out1, out2, out3, slider1, slider2, slider3,out8],out9]],
-                fn = [get_Image_reslice,get_ROI],
+                examples=[[os.path.join(os.path.dirname(__file__), "155086_A_R_MRI.nii.gz")],
+                          [os.path.join(os.path.dirname(__file__), "4153597_B_L_MRI.nii.gz")]],
+                inputs=inp,
+                outputs=[out1, out2, out3, slider1, slider2, slider3,out8],
+                fn=get_Image_reslice,
+                cache_examples=True,
+            )
+            gr.Examples(
+                examples=[[os.path.join(os.path.dirname(__file__), "155086_A_R_ROI.nii.gz")],
+                          [os.path.join(os.path.dirname(__file__), "4153597_B_L_ROI.nii.gz")]],
+                inputs=inp2,
+                outputs=out9,
+                fn=get_ROI,
                 cache_examples=True,
             )
         demo.queue(concurrency_count=6)