fixed args

app.py

@@ -5,8 +5,6 @@ import gradio
 from PIL import Image
 from huggingface_hub import hf_hub_download
 from models.linear_predictor import Predictor
-from torch.utils.data import Dataset
-from TestSampleDataset import TestDataset
 import numpy
 import os
 
@@ -63,7 +61,7 @@ for i in range(number_of_examples):
     example_rows.append([file_path, truth_label_text])
 
 @spaces.GPU
-def predict(image):
+def predict(image,truth_labels=None):
     if image is None:
         return None
     
@@ -91,12 +89,17 @@ with gradio.Blocks() as demo:
         gradio.Markdown("Click an example below to test the model against the PathMNIST test dataset.")
         
         # Create a read-only text box to display the column for Truth Labels
-        truth_box = gradio.Textbox(label="Ground Truth Label", interactive=False)
+        with gradio.Column():
+                input_img_ex = gradio.Image(label="Selected Test Image")
+                truth_box = gradio.Textbox(label="Ground Truth Label", interactive=False)
+            
+        with gradio.Column():
+            output_lbl_ex = gradio.Label(num_top_classes=3, label="Model Prediction")
         
         gradio.Examples(
             examples=example_rows,  # Passes both the image file path and the text label
-            inputs=[input_img, truth_box],  # Maps the data columns to both UI components
-            outputs=output_lbl,
+            inputs=[input_img_ex, truth_box],  # Maps the data columns to both UI components
+            outputs=output_lbl_ex,
             fn=predict,
             cache_examples=True,
         )