Update app.py

app.py

@@ -75,7 +75,7 @@ def prepare_transforms():
         torchio.transforms.ZNormalization(masking_method=lambda x: x > 0, keys=["image"])
     ])
 
-# 🔹 Process MRI File
+# Process MRI File
 def preprocess_mri(nifti_path):
     transforms = prepare_transforms()
     data_dict = {"image": nifti_path}
@@ -83,14 +83,11 @@ def preprocess_mri(nifti_path):
     dataloader = DataLoader(dataset, batch_size=1, num_workers=0)
     return next(iter(dataloader))["image"].to(device)
 
-# 🔹 Run Brain Age Prediction (Decorated for GPU Execution)
+# Run Brain Age Prediction (Decorated for GPU Execution)
 @spaces.GPU(duration=90)
-def predict_brain_age_core(path, age, sex): #, actual_age):
+def predict_brain_age(path, age, sex): #, actual_age):
     return f"Brain Age estimate: 42", age
 
-def predict_brain_age(nifti_file, age, sex):
-    return predict_brain_age_core(nifti_file.name, age, sex)
-
 """
 def predict_brain_age(nifti_file, actual_age): #sex
     if not os.path.exists(nifti_file.name):
@@ -156,11 +153,7 @@ with gr.Blocks() as demo:
             brain_age_output = gr.Textbox(label="Predicted Brain Age", interactive=False)
             bad_output = gr.Textbox(label="Brain Age Difference", interactive=False)
     
-    submit_button.click(
-        fn=predict_brain_age,
-        inputs=[mri_input, age_input, sex_input],
-        outputs=[brain_age_output, bad_output]
-    )
+    submit_button.click(fn=predict_brain_age, inputs=[mri_input, age_input, sex_input], outputs=[brain_age_output, bad_output])
     
     gr.Markdown("""
     **Disclaimer:** This is a research tool and is not intended for clinical use.