size config

app.py

@@ -1,4 +1,5 @@
 import os
+import sys
 import io
 import base64
 import time
@@ -11,6 +12,9 @@ import torch
 from flask import Flask, request, jsonify, send_from_directory
 from PIL import Image
 
+# Ensure local modules take precedence (fixes issues if rfdetr is both local and installed)
+sys.path.insert(0, os.getcwd())
+
 # Libraries for Models
 from ultralytics import YOLO
 import supervision as sv
@@ -71,11 +75,17 @@ def init_models():
                 download_file(RF_WEIGHT_URL, RF_WEIGHT_PATH)
                 print("[INFO] Loading RF-DETR...")
                 # Initialize with CPU params
-                MODEL_RF = RFDETRSegPreview(pretrain_weights=RF_WEIGHT_PATH)
-                # Attempt optimization if method exists
-                if hasattr(MODEL_RF, 'optimize_for_inference'):
-                    MODEL_RF.optimize_for_inference()
-                print("[INFO] RF-DETR Ready.")
+                # Added try-except to catch architecture mismatches (e.g. Nano vs Base)
+                try:
+                    MODEL_RF = RFDETRSegPreview(pretrain_weights=RF_WEIGHT_PATH)
+                    # Attempt optimization if method exists
+                    if hasattr(MODEL_RF, 'optimize_for_inference'):
+                        MODEL_RF.optimize_for_inference()
+                    print("[INFO] RF-DETR Ready.")
+                except RuntimeError as re:
+                    print(f"[ERROR] RF-DETR Architecture Mismatch: {re}")
+                    print("[WARN] Skipping RF-DETR loading. App will run with YOLO only.")
+                    MODEL_RF = None
             except Exception as e:
                 print(f"[ERROR] RF-DETR Load Failed: {e}")
                 traceback.print_exc()