Fire-Detection-in-open-CV-in-python

1.Install OpenCV and other required libraries:

pip install opencv-python

2.Import the necessary libraries:

import cv2
import numpy as np

3.Load the video or image frame:

frame = cv2.imread('frame.jpg')  # Replace 'frame.jpg' with the path to your image or video frame

4.Convert the frame to the appropriate color space:

hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)

5.Define the lower and upper thresholds for fire detection:

lower_red = np.array([0, 50, 50])    # Adjust these values based on your specific requirements
upper_red = np.array([10, 255, 255])  # Adjust these values based on your specific requirements

6.Apply the thresholding to detect fire:

mask = cv2.inRange(hsv, lower_red, upper_red)

7.Perform morphological operations to reduce noise and improve detection:

kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)

8.Find contours of the fire region:

contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

9.Draw bounding rectangles around the detected fire:

for contour in contours:
    (x, y, w, h) = cv2.boundingRect(contour)
    cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 255), 2)

10.Display the result:

cv2.imshow('Fire Detection', frame)
cv2.waitKey(0)
cv2.destroyAllWindows()

Remember to replace 'frame.jpg' in Step 3 with the actual path to your image or video frame. Also, adjust the values in Steps 5 (lower and upper thresholds) based on the specific color range of the fire you are detecting.

This code assumes you are working with a single image or a single frame of a video. If you want to perform fire detection on a video stream, you would need to modify the code accordingly by looping over the frames.