update app.py

app.py

@@ -63,6 +63,18 @@ def load_sample3():
 def load_sample4():
     return load_sample(4)
 
+def load_sample5():
+    return load_sample(5)
+
+def load_sample6():
+    return load_sample(6)
+
+def load_sample7():
+    return load_sample(7)
+
+def load_sample8():
+    return load_sample(8)
+
 import torchvision
 
 def load_sample(index):
@@ -90,7 +102,6 @@ def load_sample(index):
 
 
 def predict(sample_index):
-    print(sample_index)
     sample = torch.load(f"samples/val{sample_index-1}.pt")
     model.eval()
     with torch.no_grad():
@@ -111,11 +122,12 @@ def predict(sample_index):
 
     return [pil_images_output[0], pil_images_output[1], pil_images_output[2]]
 
-with gr.Blocks(css=".gradio-container {background:lightyellow;color:red;}", title="テスト"
+with gr.Blocks( title="Brain tumor 3D segmentation with MONAIMNIST - ClassCat"
+                    css=".gradio-container {background:azure;}",
                ) as demo:
     sample_index = gr.State([])
 
-    gr.HTML('<div style="font-size:12pt; text-align:center; color:yellow;">MNIST 分類器</div>')
+    gr.HTML("""<div style="font-family:'Times New Roman', 'Serif'; font-size:16pt; font-weight:bold; text-align:center; color:royalblue;">Brain tumor 3D segmentation with MONAI</div>""")
 
     with gr.Row():
         input_image0 = gr.Image(label="image channel 0", type="pil", shape=(240, 240))
@@ -135,6 +147,10 @@ with gr.Blocks(css=".gradio-container {background:lightyellow;color:red;}", titl
         example2_btn = gr.Button("Example 2")
         example3_btn = gr.Button("Example 3")
         example4_btn = gr.Button("Example 4")
+        example5_btn = gr.Button("Example 5")
+        example6_btn = gr.Button("Example 6")
+        example7_btn = gr.Button("Example 7")
+        example8_btn = gr.Button("Example 8")
 
         example1_btn.click(fn=load_sample1, inputs=None, 
                            outputs=[sample_index, input_image0, input_image1, input_image2, input_image3,
@@ -148,6 +164,18 @@ with gr.Blocks(css=".gradio-container {background:lightyellow;color:red;}", titl
         example4_btn.click(fn=load_sample4, inputs=None, 
                            outputs=[sample_index, input_image0, input_image1, input_image2, input_image3,
                                     label_image0, label_image1, label_image2])
+        example5_btn.click(fn=load_sample5, inputs=None, 
+                           outputs=[sample_index, input_image0, input_image1, input_image2, input_image3,
+                                    label_image0, label_image1, label_image2])
+        example6_btn.click(fn=load_sample6, inputs=None, 
+                           outputs=[sample_index, input_image0, input_image1, input_image2, input_image3,
+                                    label_image0, label_image1, label_image2])
+        example7_btn.click(fn=load_sample7, inputs=None, 
+                           outputs=[sample_index, input_image0, input_image1, input_image2, input_image3,
+                                    label_image0, label_image1, label_image2])
+        example8_btn.click(fn=load_sample8, inputs=None, 
+                           outputs=[sample_index, input_image0, input_image1, input_image2, input_image3,
+                                    label_image0, label_image1, label_image2])
 
     with gr.Row():
         output_image0 = gr.Image(label="output channel 0", type="pil")