update app.py

app.py

@@ -84,33 +84,13 @@ 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")
-    #imgs = []
-    #for i in range(4):
-    #    imgs.append(sample["image"][i, :, :, 70])
-
-    #pil_images = []
-    #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])
-
     label_filenames = []
     for i in range(3):
         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],
             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]]
-
 
 def predict(sample_index):
     sample = torch.load(f"samples/val{sample_index-1}.pt")
@@ -147,22 +127,11 @@ with gr.Blocks(title="Brain tumor 3D segmentation with MONAIMNIST - ClassCat",
         input_image1 = gr.Image(label="image channel 1", type="filepath", shape=(240, 240))
         input_image2 = gr.Image(label="image channel 2", type="filepath", shape=(240, 240))
         input_image3 = gr.Image(label="image channel 3", type="filepath", shape=(240, 240))
-        """
-        input_image0 = gr.Image(label="image channel 0", type="pil", shape=(240, 240))
-        input_image1 = gr.Image(label="image channel 1", type="pil", shape=(240, 240))
-        input_image2 = gr.Image(label="image channel 2", type="pil", shape=(240, 240))
-        input_image3 = gr.Image(label="image channel 3", type="pil", shape=(240, 240))
-        """
 
     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")