Create app.py

app.py

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+from typing import get_args
+
+import cv2
+import numpy as np
+import streamlit as st
+from PIL import Image
+
+from fast_alpr import ALPR
+from fast_alpr.default_detector import PlateDetectorModel
+from fast_alpr.default_ocr import OcrModel
+
+# Default models
+DETECTOR_MODELS = list(get_args(PlateDetectorModel))
+OCR_MODELS = list(get_args(OcrModel))
+# Put european OCR first
+OCR_MODELS.remove("european-plates-mobile-vit-v2-model")
+OCR_MODELS.insert(0, "european-plates-mobile-vit-v2-model")
+
+st.title("FastALPR Demo")
+st.write("An automatic license plate recognition (ALPR) system with customizable detector and OCR models.")
+
+# Sidebar for selecting models
+detector_model = st.sidebar.selectbox("Choose Detector Model", DETECTOR_MODELS)
+ocr_model = st.sidebar.selectbox("Choose OCR Model", OCR_MODELS)
+
+# Load image
+uploaded_file = st.file_uploader("Upload an image of a vehicle with a license plate", type=["jpg", "jpeg", "png"])
+
+if uploaded_file is not None:
+    # Convert uploaded file to a format compatible with OpenCV
+    img = Image.open(uploaded_file)
+    img_array = np.array(img.convert("RGB"))  # Convert to RGB if needed
+    st.image(img, caption="Uploaded Image", use_column_width=True)
+
+    # Initialize ALPR with selected models
+    alpr = ALPR(detector_model=detector_model, ocr_model=ocr_model)
+
+    # Run ALPR on the uploaded image
+    st.write("Processing...")
+    results = alpr.predict(img_array)
+
+    # Draw predictions on the image
+    annotated_img_array = alpr.draw_predictions(img_array)
+
+    # Convert the annotated image back to display in Streamlit
+    annotated_img = Image.fromarray(cv2.cvtColor(annotated_img_array, cv2.COLOR_BGR2RGB))
+    st.image(annotated_img, caption="Annotated Image with OCR Results", use_column_width=True)
+
+    # Display OCR results in text format for more detail
+    if results:
+        st.write("**OCR Results:**")
+        for result in results:
+            st.write(f"- Detected Plate: `{result['text']}` with confidence `{result['confidence']:.2f}`")
+    else:
+        st.write("No license plate detected.")
+else:
+    st.write("Please upload an image to continue.")