use the huggingface tmp folder

app.py

@@ -4,23 +4,22 @@ import time
 from PIL import Image
 import os
 import sys
+import shutil
 import gdown
 
-st.set_page_config(
-    page_title="2D Floorplan Vectorizer",
-    layout="wide",
-    initial_sidebar_state="collapsed"
-)
+# ==================================
+# SETUP
+# ==================================
 
-print("Streamlit App Starting...")
+print("🚀 Streamlit App Starting...")
 
 BASE_DIR = os.path.dirname(os.path.abspath(__file__))
 
 # Setup Paths
-UPLOAD_DIR = os.path.join(BASE_DIR, "rcnn_model", "uploads")
+UPLOAD_DIR = "/tmp/uploads/"
 MODEL_DIR = os.path.join(BASE_DIR, "rcnn_model", "scripts")
-JSON_DIR = os.path.join(BASE_DIR, "rcnn_model", "results")
-OUTPUT_DIR = os.path.join(BASE_DIR, "rcnn_model", "output")
+JSON_DIR = "/tmp/results/"
+OUTPUT_DIR = "/tmp/output/"
 SAMPLE_DIR = os.path.join(BASE_DIR, "rcnn_model", "sample")
 logo_path = os.path.join(BASE_DIR, "public", "logo.png")
 model_path = os.path.join(OUTPUT_DIR, "model_final.pth")
@@ -29,23 +28,39 @@ model_path = os.path.join(OUTPUT_DIR, "model_final.pth")
 GOOGLE_DRIVE_FILE_ID = "1yr64AOgaYZPTcQzG6cxG6lWBENHR9qjW"
 GDRIVE_URL = f"https://drive.google.com/uc?id={GOOGLE_DRIVE_FILE_ID}"
 
+# Make folders if they don't exist
 os.makedirs(UPLOAD_DIR, exist_ok=True)
 os.makedirs(JSON_DIR, exist_ok=True)
 os.makedirs(OUTPUT_DIR, exist_ok=True)
 
+# ==================================
 # DOWNLOAD MODEL IF MISSING
+# ==================================
 
 if not os.path.exists(model_path):
-    print("Model file not found! Downloading from Google Drive...")
+    print("🚀 Model file not found! Downloading from Google Drive...")
     try:
         gdown.download(GDRIVE_URL, model_path, quiet=False)
-        print("Model downloaded successfully.")
+        print("✅ Model downloaded successfully.")
     except Exception as e:
-        print(f"Failed to download model: {e}")
+        print(f"❌ Failed to download model: {e}")
+
+# ==================================
+# IMPORT MODEL RUNNER
+# ==================================
 
 sys.path.append(MODEL_DIR)
-from rcnn_model.scripts.rcnn_run import main, write_config
+from rcnn_run import main, write_config
 
+# ==================================
+# CSS Styling
+# ==================================
+
+st.set_page_config(
+    page_title="2D Floorplan Vectorizer",
+    layout="wide",
+    initial_sidebar_state="collapsed"
+)
 
 st.markdown(
     """
@@ -65,28 +80,44 @@ st.markdown(
     unsafe_allow_html=True
 )
 
+# ==================================
+# HEADER
+# ==================================
+
 st.image(logo_path, width=250)
 st.markdown("<div class='header-title'>2D Floorplan Vectorizer</div>", unsafe_allow_html=True)
+
+# ==================================
+# FILE UPLOAD SECTION
+# ==================================
+
 st.subheader("Upload your Floorplan Image")
 uploaded_file = st.file_uploader("Choose an image", type=["png", "jpg", "jpeg"])
 
+# Initialize session state
 if "processing_complete" not in st.session_state:
     st.session_state.processing_complete = False
 if "json_output" not in st.session_state:
     st.session_state.json_output = None
 
+# ==================================
+# IMAGE + JSON Layout
+# ==================================
+
 col1, col2 = st.columns([1, 2])
 
+# ==================================
+# MAIN LOGIC
+# ==================================
+
 if uploaded_file is not None:
-    print("File Uploaded:", uploaded_file.name)
+    print("📤 File Uploaded:", uploaded_file.name)
 
-    # Save uploaded file
     uploaded_path = os.path.join(UPLOAD_DIR, uploaded_file.name)
     with open(uploaded_path, "wb") as f:
         f.write(uploaded_file.getbuffer())
-    print("Uploaded file saved at:", uploaded_path)
+    print("✅ Uploaded file saved at:", uploaded_path)
 
-    # Display uploaded image
     with col1:
         st.markdown("<div class='upload-container'>", unsafe_allow_html=True)
         st.image(Image.open(uploaded_path), caption="Uploaded Image", use_container_width=True)
@@ -99,23 +130,24 @@ if uploaded_file is not None:
             progress_bar = st.progress(0)
             status_text = st.empty()
 
-            # Run Model
+            # === 🔥 Run Model Here ===
             input_image = uploaded_path
             output_json_name = uploaded_file.name.replace(".png", "_result.json").replace(".jpg", "_result.json").replace(".jpeg", "_result.json")
             output_image_name = uploaded_file.name.replace(".png", "_result.png").replace(".jpg", "_result.png").replace(".jpeg", "_result.png")
 
             cfg = write_config()
-            print("Model config created. Running model...")
+            print("⚙️ Model config created. Running model...")
 
-            # Simulate progress bar
+            # Simulate progress
             for i in range(1, 30):
                 time.sleep(0.01)
                 progress_bar.progress(i)
                 status_text.text(f"Preprocessing: {i}%")
 
             main(cfg, input_image, output_json_name, output_image_name)
-            print("Model run complete.")
+            print("✅ Model run complete.")
 
+            # Prepare output paths
             output_json_path = os.path.join(JSON_DIR, output_json_name)
             output_image_path = os.path.join(JSON_DIR, output_image_name)
 
@@ -136,13 +168,17 @@ if uploaded_file is not None:
             if os.path.exists(output_json_path):
                 with open(output_json_path, "r") as jf:
                     st.session_state.json_output = json.load(jf)
-                    print("JSON Output Loaded Successfully.")
+                    print("📄 JSON Output Loaded Successfully.")
             else:
                 st.session_state.json_output = {"error": "JSON output not generated."}
-                print("JSON output missing.")
+                print("❌ JSON output missing.")
 
             st.session_state.processing_complete = True
 
+        # ==================================
+        # DISPLAY Output Image + Download Buttons + JSON side-by-side
+        # ==================================
+
         out_col1, out_col2 = st.columns(2)
 
         with out_col1:
@@ -174,4 +210,4 @@ if uploaded_file is not None:
 
 else:
     st.warning("⚠️ No image uploaded yet.")
-    st.session_state.processing_complete = False
+    st.session_state.processing_complete = False

rcnn_model/scripts/rcnn_run.py

@@ -24,7 +24,7 @@ from rcnn_model.extraction.annotation_builder import AnnotationBuilder as AnnBui
 # results_directory = str(from_root("results"))+"/"
 # sample_data_directory = str(from_root("models/rcnn/sample_data"))+"/"
 
-results_directory = "rcnn_model/results/"
+results_directory = "/tmp/results/"
 sample_data_directory = "rcnn_model/sample/"
 
 def main(cfg,img_source_path, coco_dest_filename, val_img_dest_filename):