Updated app.py

app.py

@@ -2,8 +2,8 @@ import gradio as gr
 import subprocess
 import os
 import shutil
+import os
 
-export nnUNet_results="./model"
 
 # Define paths
 MODEL_DIR = "./model"  # Local directory to store the downloaded model
@@ -32,14 +32,12 @@ def run_nnunet_predict(nifti_file):
     os.makedirs(OUTPUT_DIR, exist_ok=True)
 
     # Save the uploaded file to the input directory
-    input_path = os.path.join(INPUT_DIR, "image.nii.gz")
+    input_path = os.path.join(INPUT_DIR, "image_0000.nii.gz")
     with open(input_path, "wb") as f:
         f.write(nifti_file.read())
 
     # Set environment variables for nnUNet
-    os.environ["nnUNet_raw"] = DATASET_DIR
-    os.environ["nnUNet_preprocessed"] = DATASET_DIR
-    os.environ["nnUNet_results"] = DATASET_DIR
+    os.environ["nnUNet_results"] = MODEL_DIR
 
     # Construct and run the nnUNetv2_predict command
     command = [