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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 global OCR first | |
| OCR_MODELS.remove("global-plates-mobile-vit-v2-model") | |
| OCR_MODELS.insert(0, "global-plates-mobile-vit-v2-model") | |
| st.title("FastALPR Demo") | |
| st.write("An automatic license plate recognition (ALPR) system with customizable detector and OCR models.") | |
| st.markdown(""" | |
| [FastALPR](https://github.com/ankandrew/fast-alpr) library uses [open-image-models](https://github.com/ankandrew/open-image-models) | |
| for plate detection and [fast-plate-ocr](https://github.com/ankandrew/fast-plate-ocr) for optical character recognition (**OCR**). | |
| """) | |
| # 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_container_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(annotated_img_array) | |
| st.image(annotated_img, caption="Annotated Image with OCR Results", use_container_width=True) | |
| # Display OCR results in text format for more detail | |
| if results: | |
| st.write("**OCR Results:**") | |
| for result in results: | |
| # Access the detection and OCR attributes from ALPRResult | |
| plate_text = result.ocr.text if result.ocr else "N/A" | |
| plate_confidence = result.ocr.confidence if result.ocr else 0.0 | |
| st.write(f"- Detected Plate: `{plate_text}` with confidence `{plate_confidence:.2f}`") | |
| else: | |
| st.write("No license plate detected 😔.") | |
| else: | |
| st.write("Please upload an image to continue.") |