test

app.py

@@ -30,6 +30,8 @@ def transform_image(img_sample):
     return transformed_img
 
 def predict(Image):
+    tranformed_img = transform_image(Image)
+    """
     model.eval()
     tranformed_img = transform_image(Image)
     img = torch.from_numpy(tranformed_img)
@@ -41,6 +43,8 @@ def predict(Image):
     for cat, value in zip(category, grade):
         output_dict[cat] = value.item()
     return output_dict
+    """
+    return tranformed_img
 
 
 
@@ -50,7 +54,7 @@ label = gr.Label(label="Grade")
 demo = gr.Interface(
     fn=predict,
     inputs=image,
-    outputs=label,
+    outputs=image,#label,
     examples=["examples/0.png", "examples/1.png", "examples/2.png", "examples/3.png", "examples/4.png"]
     )