WARNING ⚠️ Unable to automatically guess model task, assuming ‘task=detect’. Explicitly define task for your model, i.e. ‘task=detectt’, ‘segment’, ‘classify’,’pose’ or ‘obb’.
[http @ 00000265b0ce1a80] Stream ends prematurely at 40818, should be 18446744073709551615
[http @ 00000265b0ce1a80] Stream ends prematurely at 40818, should be 18446744073709551615

Code:
import cv2
import numpy as np
from ultralytics import YOLO
from sort.sort import Sort
from util import read_license_plate
import streamlit as st
import pandas as pd
import io

class LicensePlateDetector:
def init(self, model_path):
self.model = YOLO(model_path)

def detect(self, frame):
    return self.model(frame)[0]

class LicensePlateProcessor:
@staticmethod
def process(license_plate_crop):
if license_plate_crop.size == 0:
return None
license_plate_crop_gray = cv2.cvtColor(license_plate_crop, cv2.COLOR_BGR2GRAY)
_, license_plate_crop_thresh = cv2.threshold(
license_plate_crop_gray, 125, 255, cv2.THRESH_BINARY_INV
)
return license_plate_crop_thresh

@staticmethod
def read(license_plate_crop_thresh):
    if license_plate_crop_thresh is None or license_plate_crop_thresh.size == 0:
        return None, 0
    return read_license_plate(license_plate_crop_thresh)

def main():
st.title(“Live Stream License Plate Detection”)

video_url = st.text_input("Enter video stream URL (http/rtsp):")

if video_url:
    license_plate_detector = LicensePlateDetector(
        ""
    )
    license_plate_processor = LicensePlateProcessor()

    cap = cv2.VideoCapture(video_url)

    if not cap.isOpened():
        st.error("Error opening video stream.")
        return

    while True:
        ret, frame = cap.read()

        if not ret:
            st.error("Error reading frame.")
            break

        # Process frame
        license_plates = license_plate_detector.detect(frame)

        for license_plate in license_plates.boxes.data.tolist():
            x1, y1, x2, y2, score, class_id = license_plate

            license_plate_crop = frame[int(y1) : int(y2), int(x1) : int(x2), :]
            license_plate_crop_thresh = license_plate_processor.process(
                license_plate_crop
            )
            license_plate_text, license_plate_text_score = (
                license_plate_processor.read(license_plate_crop_thresh)
            )

            if license_plate_text is not None:
                # Draw bounding box on frame
                cv2.rectangle(
                    frame, (int(x1), int(y1)), (int(x2), int(y2)), (0, 255, 0), 2
                )
                cv2.putText(
                    frame,
                    license_plate_text,
                    (int(x1), int(y1) - 10),
                    cv2.FONT_HERSHEY_SIMPLEX,
                    0.9,
                    (36, 255, 12),
                    2,
                )

                # Display result
                st.image(frame, channels="BGR", use_column_width=True)

    cap.release()

if name == “main“:
main()