import cv2 import numpy as np import winsound

Start webcam

cap = cv2.VideoCapture(0)

while True: ret, frame = cap.read() if not ret: break

# Resize for speed
frame = cv2.resize(frame, (640, 480))

# Convert to HSV
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)

# Fire color ranges (red, orange, yellow)
lower1 = np.array([0, 150, 150])
upper1 = np.array([10, 255, 255])

lower2 = np.array([15, 100, 100])
upper2 = np.array([35, 255, 255])

# Combine masks
mask1 = cv2.inRange(hsv, lower1, upper1)
mask2 = cv2.inRange(hsv, lower2, upper2)
mask = cv2.bitwise_or(mask1, mask2)

# Remove noise
mask = cv2.GaussianBlur(mask, (5, 5), 0)

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

fire_detected = False
for cnt in contours:
    area = cv2.contourArea(cnt)
    if area > 1500:  # Minimum fire area to trigger
        x, y, w, h = cv2.boundingRect(cnt)
        cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 255), 2)
        cv2.putText(frame, "FIRE DETECTED!", (x, y - 10),
                    cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 2)
        fire_detected = True

# Play alarm if fire detected
if fire_detected:
    winsound.Beep(1000, 500)

# Show output
cv2.imshow("Fire Detection", frame)
cv2.imshow("Fire Mask", mask)

# Exit on ESC
if cv2.waitKey(1) & 0xFF == 27:
    break

cap.release() cv2.destroyAllWindows()

Fire-Detection

This project uses OpenCV to detect fire in real-time from a webcam feed by identifying red, orange, and yellow color ranges in the HSV spectrum. It combines multiple color masks, removes noise, and detects irregular shapes using contour analysis to reduce false alarms.