Match model preprocessing scale

app.py

@@ -25,6 +25,7 @@ UPLOAD_DIR = BASE_DIR / "static" / "uploads"
 DATABASE_PATH = BASE_DIR / "instance" / "traffic_signs.sqlite3"
 MODEL_PATH = BASE_DIR / "traffic_classifier.h5"
 ALLOWED_EXTENSIONS = {"png", "jpg", "jpeg", "webp"}
+NORMALIZE_INPUT = os.environ.get("NORMALIZE_INPUT", "false").lower() in {"1", "true", "yes"}
 URL_CONTENT_TYPES = {
     "image/jpeg": "jpg",
     "image/png": "png",
@@ -227,7 +228,9 @@ def save_uploaded_image(file):
 def prepare_image(path):
     image = Image.open(path).convert("RGB")
     image = image.resize((30, 30))
-    array = np.asarray(image, dtype=np.float32) / 255.0
+    array = np.asarray(image, dtype=np.float32)
+    if NORMALIZE_INPUT:
+        array = array / 255.0
     return np.expand_dims(array, axis=0)