retract model update

README.md

@@ -31,11 +31,11 @@ A Gradio web app that allows you to upload 2D floorplan images and automatically
 
 3. **Download the pretrained model:**
 
-    - Download `model_final_2.pth` from [Google Drive here](https://drive.google.com/file/d/1TJLKFI-sSQQ4JOqDgS6aqcw26IsadXGO/view?usp=sharing).
+    - Download `model_final.pth` from [Google Drive here](https://drive.google.com/file/d/1yr64AOgaYZPTcQzG6cxG6lWBENHR9qjW/view?usp=sharing).
     - Place it inside:
 
       ```plaintext
-      floorplan-vectorizer/rcnn_model/output/model_final_2.pth
+      floorplan-vectorizer/rcnn_model/output/model_final.pth
       ```
 
 4. **Run the app:**

app.py

@@ -15,29 +15,25 @@ BASE_DIR = os.path.dirname(os.path.abspath(__file__))
 UPLOAD_DIR = "/tmp/uploads/"
 JSON_DIR = "/tmp/results/"
 OUTPUT_DIR = "/tmp/output/"
-OUTPUT_DIR2= "/tmp/output2/"
 MODEL_DIR = os.path.join(BASE_DIR, "rcnn_model", "scripts")
 logo_path = os.path.join(BASE_DIR, "public", "logo.png")
-model_path = os.path.join(OUTPUT_DIR2, "model_final_2.pth")
+model_path = os.path.join(OUTPUT_DIR, "model_final.pth")
 
 # Google Drive model
-GOOGLE_DRIVE_FILE_ID = "1ptdr6d_jglk_78e4d5s1jUO04XWS1zo"
+GOOGLE_DRIVE_FILE_ID = "1yr64AOgaYZPTcQzG6cxG6lWBENHR9qjW"
 GDRIVE_URL = f"https://drive.google.com/uc?id={GOOGLE_DRIVE_FILE_ID}"
 
 # Create folders
 os.makedirs(UPLOAD_DIR, exist_ok=True)
 os.makedirs(JSON_DIR, exist_ok=True)
 os.makedirs(OUTPUT_DIR, exist_ok=True)
-os.makedirs(OUTPUT_DIR2, exist_ok=True)
 
 # Download model if missing
 if not os.path.exists(model_path):
     print("Model file not found! Downloading...")
     try:
         gdown.download(GDRIVE_URL, model_path, quiet=False, use_cookies=False)
-        if not os.path.exists(model_path):
-            raise Exception("Model download failed: File not found after download.")
-        print("✅ Model downloaded successfully.")
+        print("Model downloaded successfully.")
     except Exception as e:
         print(f"Failed to download model: {e}")
 
@@ -116,4 +112,4 @@ with gr.Blocks() as demo:
     None,
     [run_button],
     )
-demo.launch(server_name="0.0.0.0", server_port=7860, share=True)
+demo.launch(server_name="0.0.0.0", server_port=7860, share=True)

rcnn_model/scripts/rcnn_eval.py

@@ -23,7 +23,7 @@ def main(cfg,results_filename = "eval_results.txt"):
     #update config file
     cfg.DATALOADER.NUM_WORKERS = 1
     cfg.SOLVER.IMS_PER_BATCH = 1                                           
-    cfg.MODEL.WEIGHTS = os.path.join(cfg.OUTPUT_DIR2, "model_final_2.pth")
+    cfg.MODEL.WEIGHTS = os.path.join(cfg.OUTPUT_DIR, "model_final.pth")
 
     #run evaluation
     results = standard_evaluation(cfg)

rcnn_model/scripts/rcnn_run.py

@@ -13,7 +13,7 @@ from rcnn_model.extraction.annotation_builder import AnnotationBuilder as AnnBui
 
 results_directory = "/tmp/results/"
 sample_data_directory = "rcnn_model/sample/"
-model_directory = "/tmp/output2/"
+model_directory = "/tmp/output/"
 
 def main(cfg,img_source_path, coco_dest_filename, val_img_dest_filename):
     os.chdir(str(from_root()))
@@ -22,7 +22,7 @@ def main(cfg,img_source_path, coco_dest_filename, val_img_dest_filename):
     #configure model
     cfg.DATALOADER.NUM_WORKERS = 1
     cfg.SOLVER.IMS_PER_BATCH = 1                                        
-    cfg.MODEL.WEIGHTS = os.path.join(model_directory, "model_final_2.pth")
+    cfg.MODEL.WEIGHTS = os.path.join(model_directory, "model_final.pth")
     cfg.MODEL.DEVICE = "cpu"
     predictor = DefaultPredictor(cfg)