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import streamlit as st
from ultralytics import YOLO
import numpy as np
import cv2
from PIL import Image
st.title("🔍 Suspicious Activity Detection with YOLOv11")
# Load the model
@st.cache_resource
def load_model():
return YOLO("yolo11l.pt")
model = load_model()
uploaded_file = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
if uploaded_file:
image = Image.open(uploaded_file)
st.image(image, caption="Uploaded Image", use_column_width=True)
if st.button("Detect Activity"):
img_array = np.array(image.convert("RGB"))[..., ::-1] # Convert to BGR
results = model.predict(img_array)
for r in results:
plotted = r.plot()
st.image(plotted, caption="Detections", use_column_width=True)
st.subheader("Detected Objects:")
for box in r.boxes:
conf = float(box.conf[0])
cls = int(box.cls[0])
cls_name = model.names[cls]
st.write(f"- {cls_name} (Confidence: {conf:.2f})")
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