update app.py

app.py

@@ -84,7 +84,7 @@ def load_sample(index):
     for i in range(4):
         image_filenames.append(f"thumbnails/image{index-1}_{i}.png")
 
-    sample = torch.load(f"samples/val{index-1}.pt")
+    #sample = torch.load(f"samples/val{index-1}.pt")
     #imgs = []
     #for i in range(4):
     #    imgs.append(sample["image"][i, :, :, 70])
@@ -93,16 +93,20 @@ def load_sample(index):
     #for i in range(4):
     #    pil_images.append(torchvision.transforms.functional.to_pil_image(imgs[i]))
 
-    imgs_label = []
-    for i in range(3):
-        imgs_label.append(sample["label"][i, :, :, 70])
+    #imgs_label = []
+    #for i in range(3):
+    #    imgs_label.append(sample["label"][i, :, :, 70])
 
-    pil_images_label = []
+    label_filenames = []
     for i in range(3):
-        pil_images_label.append(torchvision.transforms.functional.to_pil_image(imgs_label[i]))
+        label_filenames.append(f"thumbnails_label/label{index-1}_{i}.png")
+
+    #pil_images_label = []
+    #for i in range(3):
+    #    pil_images_label.append(torchvision.transforms.functional.to_pil_image(imgs_label[i]))
 
     return [index, image_filenames[0], image_filenames[1], image_filenames[2], image_filenames[3],
-            pil_images_label[0], pil_images_label[1], pil_images_label[2]]
+            label_filenames[0], label_filenames[1], label_filenames[2]]
 
     #return [index, pil_images[0], pil_images[1], pil_images[2], pil_images[3],
     #        pil_images_label[0], pil_images_label[1], pil_images_label[2]]
@@ -151,9 +155,14 @@ with gr.Blocks(title="Brain tumor 3D segmentation with MONAIMNIST - ClassCat",
         """
 
     with gr.Row():
+        label_image0 = gr.Image(label="label channel 0", type="filepath", shape=(240, 240))
+        label_image1 = gr.Image(label="label channel 1", type="filepath", shape=(240, 240))
+        label_image2 = gr.Image(label="label channel 2", type="filepath", shape=(240, 240))
+        """
         label_image0 = gr.Image(label="label channel 0", type="pil")
         label_image1 = gr.Image(label="label channel 1", type="pil")
         label_image2 = gr.Image(label="label channel 2", type="pil")
+        """
 
     with gr.Row():
         example1_btn = gr.Button("Example 1")