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import streamlit as st
from ultralytics import YOLO
import cv2
import easyocr
import numpy as np
import pandas as pd
from PIL import Image
import tempfile
@st.cache_resource
def load_model():
model = YOLO('yolo11n-custom.pt')
model.fuse()
return model
model = load_model()
reader = easyocr.Reader(['en'])
def detect_license_plate(image):
results = model.predict(image, conf=0.15, iou=0.3, classes=[0])
plate_texts = []
img_array = np.array(image)
# img = cv2.imread(image_path)
img = cv2.cvtColor(img_array, cv2.COLOR_RGB2BGR)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
img_height, img_width, _ = img.shape
for result in results:
for bbox in result.boxes.xyxy:
x1, y1, x2, y2 = map(int, bbox.tolist())
plate = img[int(y1):int(y2), int(x1):int(x2)]
scale=2
height, width = plate.shape[:2]
plate = cv2.resize(plate, (width * scale, height * scale), interpolation=cv2.INTER_CUBIC)
lab = cv2.cvtColor(plate, cv2.COLOR_RGB2LAB)
l, a, b = cv2.split(lab)
clahe = cv2.createCLAHE(clipLimit=3.0, tileGridSize=(8, 8))
l = clahe.apply(l)
plate = cv2.merge((l, a, b))
plate = cv2.cvtColor(plate, cv2.COLOR_LAB2RGB)
text = reader.readtext(plate, detail=0, allowlist="ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789-")
text = " ".join(text).upper()
text_scale = max(1, width / 250)
thickness = max(2, width // 200)
cv2.rectangle(img, (x1, y1), (x2, y2), (0, 255, 0), thickness)
(text_width, text_height), _ = cv2.getTextSize(text, cv2.FONT_HERSHEY_SIMPLEX, text_scale, thickness)
text_x = x1 + (width - text_width) // 2 # Centered horizontally
text_y = y1 - 10 if y1 > 50 else y2 + text_height + 20 # Above unless too high
text_box_y1 = text_y - text_height - 5
text_box_y2 = text_y + 5
cv2.rectangle(img, (text_x - 8, text_box_y1 - 3), (text_x + text_width + 8, text_box_y2 + 3), (0, 0, 0), -1)
cv2.rectangle(img, (text_x - 5, text_box_y1), (text_x + text_width + 5, text_box_y2), (255, 255, 255), -1)
cv2.putText(img, text, (text_x, text_y), cv2.FONT_HERSHEY_SIMPLEX, text_scale, (0, 0, 0), thickness)
plate_texts.append(text)
image = img
return image, plate_texts
st.title("🚘 Real-Time License Plate Detection", anchor=False)
st.write("For better license plate detection, ensure you use high-quality images. If detection is unclear, try enhancing the image first. Use the Refine Image for Detection tool.")
st.write("Upload an image, upload a video, or use your webcam for real-time license plate detection.")
option = st.radio("Choose Input Source:", ("Upload Image", "Upload Video", "Webcam"), horizontal=True )
if option == "Upload Image":
uploaded_file = st.file_uploader("Upload an image", type=["jpg", "png", "jpeg"])
if uploaded_file:
img = Image.open(uploaded_file)
st.write("Processing...")
processed_img, plate_texts = detect_license_plate(img)
st.image(processed_img, caption="Detected Plates Image", use_container_width=True)
st.write("**Detected License Plates:**")
if plate_texts:
plates = pd.DataFrame({"License Plate": plate_texts})
plates.index = plates.index + 1
st.table(plates)
else:
st.write("No license plates detected.")
elif option == "Upload Video":
uploaded_video = st.file_uploader("Choose a video...", type=["mp4", "avi", "mov"])
if uploaded_video is not None:
st.write("Processing video...")
tfile = tempfile.NamedTemporaryFile(delete=False)
tfile.write(uploaded_video.read())
cap = cv2.VideoCapture(tfile.name)
frame_placeholder = st.empty()
while cap.isOpened():
ret, frame = cap.read()
if not ret:
break
processed_frame, plate_texts = detect_license_plate(frame)
frame_placeholder.image(processed_frame, caption="Detected Plates Video", use_container_width=True)
cap.release()
elif option == "Webcam":
if "running" not in st.session_state:
st.session_state.running = True
if st.button("Stop"):
st.session_state.running = False
st.write("Starting Webcam... Press **Stop** to end.")
cap = cv2.VideoCapture(0)
frame_placeholder = st.empty()
while cap.isOpened():
ret, frame = cap.read()
if not ret:
st.warning("Failed to capture webcam feed.")
break
processed_frame, plate_texts = detect_license_plate(frame)
frame_placeholder.image(processed_frame, channels="BGR", caption="Webcam Feed", use_container_width=True)
if not st.session_state.running:
break
cap.release() |