Update app.py

app.py

@@ -1,14 +1,14 @@
-import streamlit as st
-from open_image_models import LicensePlateDetector
-from PIL import Image
+from typing import get_args
+
 import cv2
 import numpy as np
+import streamlit as st
+from PIL import Image
+
+from open_image_models.detection.core.hub import PlateDetectorModel
 
 # Define the available models
-PlateDetectorModel = ['yolo-v9-t-640-license-plate-end2end', 
-                      'yolo-v9-t-512-license-plate-end2end', 
-                      'yolo-v9-t-384-license-plate-end2end', 
-                      'yolo-v9-t-256-license-plate-end2end']
+detection_models = get_args(PlateDetectorModel)
 
 # Streamlit interface
 st.title("🦀 Open Image Models: Pre-trained Models for Object Detection")
@@ -16,7 +16,7 @@ st.write("Leverage fast and efficient pre-trained ONNX models for various object
 st.markdown("---")
 
 # Model selection dropdown (specific to license plate detection in this example)
-selected_model = st.selectbox("🔍 Select a License Plate Detection Model", PlateDetectorModel)
+selected_model = st.selectbox("🔍 Select a License Plate Detection Model", detection_models)
 
 # File uploader for images
 uploaded_file = st.file_uploader("📂 Upload an image...", type=["jpg", "png", "jpeg", "webp"])
@@ -42,15 +42,15 @@ if uploaded_file is not None:
     # Streamlit display for detections
     if detections:
         st.success(f"✅ {len(detections)} License Plates Detected!")
-        
+
         # Use an expander to show details in a more organized way
         with st.expander("See detected plates details"):
             for i, detection in enumerate(detections):
                 # Access attributes of the DetectionResult class
                 bbox = detection.bounding_box
                 st.markdown(f"""
-                **Plate {i+1}:**  
-                - **Label:** {detection.label}  
+                **Plate {i+1}:**
+                - **Label:** {detection.label}
                 - **Confidence:** {detection.confidence:.2f}
                 - **Bounding Box:** (x1: {bbox.x1}, y1: {bbox.y1}, x2: {bbox.x2}, y2: {bbox.y2})
                 """)