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Runtime error
File size: 1,013 Bytes
defef4e 42df645 defef4e 42df645 0be7ae3 42df645 0be7ae3 a80de8b 0be7ae3 a80de8b 0be7ae3 a80de8b 0be7ae3 a80de8b 0be7ae3 a80de8b 0be7ae3 a80de8b 0be7ae3 a80de8b 0be7ae3 a80de8b 0be7ae3 a80de8b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 | import streamlit as st
import cv2
import numpy as np
from ultralytics import YOLO
# Load the YOLO model
model = YOLO("best.pt") # Ensure the path to your model is correct
# Set the title of the app
st.title("Live Fire Detection App")
# Define color ranges for fire detection
lower_red = np.array([0, 100, 100])
upper_red = np.array([10, 255, 255])
# Create a video capture object
cap = cv2.VideoCapture(0) # 0 for default camera, change as needed
while True:
ret, frame = cap.read()
# Convert BGR to HSV color space
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
# Create a mask for the fire color range
mask = cv2.inRange(hsv, lower_red, upper_red)
# Apply the mask to the original frame
res = cv2.bitwise_and(frame, frame, mask=mask)
# Display the resulting frame
cv2.imshow('Fire Detection', res)
# Exit if 'q' is pressed
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# Release the capture and close windows
cap.release()
cv2.destroyAllWindows() 1
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