remove streamlit code

app.py

@@ -1,151 +0,0 @@
-import streamlit as st
-import subprocess
-import os
-import shutil
-from huggingface_hub import hf_hub_download
-
-REPO_ID = "anirudh0410/WSAttention-Prostate"
-FILENAMES = ["pirads.pt", "prostate_segmentation_model.pt", "cspca_model.pth"]
-
-@st.cache_resource
-def download_all_models():
-    # 1. Ensure the 'models' directory exists
-    models_dir = os.path.join(os.getcwd(), 'models')
-    os.makedirs(models_dir, exist_ok=True) # <--- THIS FIXES YOUR ERROR
-
-    for filename in FILENAMES:
-        try:
-            # 2. Download from Hugging Face (to cache)
-            cached_path = hf_hub_download(repo_id=REPO_ID, filename=filename)
-            
-            # 3. Define where we want it to live locally
-            destination_path = os.path.join(models_dir, filename)
-            
-            # 4. Copy only if it's not already there
-            if not os.path.exists(destination_path):
-                shutil.copy(cached_path, destination_path)
-                
-        except Exception as e:
-            st.error(f"Failed to download {filename}: {e}")
-            st.stop()
-
-# --- TRIGGER THE DOWNLOAD STARTUP ---
-with st.spinner("Downloading model weights..."):
-    download_all_models()
-    st.success("Models ready!")
-
-# --- CONFIGURATION ---
-# Base paths
-BASE_DIR = os.getcwd()
-INPUT_BASE = os.path.join(BASE_DIR, "temp_data" )
-OUTPUT_DIR = os.path.join(BASE_DIR, "temp_data", "processed")
-
-# Create specific sub-directories for each input type
-# This ensures we pass a clean directory path to your script
-T2_DIR = os.path.join(INPUT_BASE, "t2")
-ADC_DIR = os.path.join(INPUT_BASE, "adc")
-DWI_DIR = os.path.join(INPUT_BASE, "dwi")
-
-# Ensure all folders exist
-if os.path.exists(INPUT_BASE):
-    shutil.rmtree(INPUT_BASE)
-for path in [T2_DIR, ADC_DIR, DWI_DIR, OUTPUT_DIR]:
-    os.makedirs(path, exist_ok=True)
-
-st.title("Model Inference")
-st.markdown("### Upload your T2W, ADC, and DWI scans")
-
-# --- 1. UI: THREE UPLOADERS ---
-col1, col2, col3 = st.columns(3)
-
-with col1:
-    t2_file = st.file_uploader("Upload T2W (NRRD)", type=["nrrd"])
-with col2:
-    adc_file = st.file_uploader("Upload ADC (NRRD)", type=["nrrd"])
-with col3:
-    dwi_file = st.file_uploader("Upload DWI (NRRD)", type=["nrrd"])
-
-# --- 2. EXECUTION LOGIC ---
-if t2_file and adc_file and dwi_file:
-    st.success("Files ready.")
-    
-    if st.button("Run Inference"):
-        # --- A. CLEANUP & SAVE ---
-        # Clear old files to prevent mixing previous runs
-        # (Optional but recommended for a clean state)
-        for folder in [T2_DIR, ADC_DIR, DWI_DIR, OUTPUT_DIR]:
-            for f in os.listdir(folder):
-                os.remove(os.path.join(folder, f))
-
-        # Save T2
-        # We save it inside the T2_DIR folder
-        with open(os.path.join(T2_DIR, t2_file.name), "wb") as f:
-            shutil.copyfileobj(t2_file, f)
-            
-        # Save ADC
-        with open(os.path.join(ADC_DIR, adc_file.name), "wb") as f:
-            shutil.copyfileobj(adc_file, f)
-            
-        # Save DWI
-        with open(os.path.join(DWI_DIR, dwi_file.name), "wb") as f:
-            shutil.copyfileobj(dwi_file, f)
-
-        st.write("Files saved. Starting pipeline...")
-
-        # --- B. CONSTRUCT COMMAND ---
-        # We pass the FOLDER paths, not file paths, matching your argument names
-        command = [
-            "python", "run_inference.py",
-            "--t2_dir", T2_DIR,
-            "--dwi_dir", DWI_DIR,
-            "--adc_dir", ADC_DIR,
-            "--output_dir", OUTPUT_DIR,
-            "--project_dir", BASE_DIR
-        ]
-        
-        # DEBUG: Show the exact command being run (helpful for troubleshooting)
-        st.code(" ".join(command), language="bash")
-
-        # --- C. RUN SCRIPT ---
-        with st.spinner("Running Inference... (This may take a moment)"):
-            try:
-                # Run the script and capture output
-                result = subprocess.run(
-                    command,
-                    capture_output=True,
-                    text=True,
-                    check=True
-                )
-                
-                st.success("Pipeline Execution Successful!")
-                
-                # Show Logs
-                with st.expander("View Execution Logs"):
-                    st.code(result.stdout)
-                
-                # --- D. SHOW OUTPUT FILES ---
-                st.subheader("Results & Downloads")
-                
-                # List everything in the output directory
-                if os.path.exists(OUTPUT_DIR):
-                    output_files = os.listdir(OUTPUT_DIR)
-                    
-                    if output_files:
-                        for file_name in output_files:
-                            file_path = os.path.join(OUTPUT_DIR, file_name)
-                            
-                            # Skip directories, show download buttons for files
-                            if os.path.isfile(file_path):
-                                with open(file_path, "rb") as f:
-                                    st.download_button(
-                                        label=f"Download {file_name}",
-                                        data=f,
-                                        file_name=file_name
-                                    )
-                    else:
-                        st.warning("Script finished but no files were found in output_dir.")
-                        
-            except subprocess.CalledProcessError as e:
-                st.error("Script Execution Failed.")
-                st.error("Error Output:")
-                st.code(e.stderr)