Update app.py

app.py

@@ -2,79 +2,26 @@ import streamlit as st
 import cv2
 import numpy as np
 from ultralytics import YOLO
-import math
 
 
-
-
-
-
-
-
-# Define fire color range (adjust based on your dataset)
-lower_red = np.array([0, 100, 100])
-upper_red = np.array([10, 255, 255])
-
 # Load the YOLO model
 model = YOLO("best.pt")  # Ensure the path to your model is correct
 
-def detect_fire(frame):
-    """Detects fire in an image using YOLOv8 and color thresholding.
-
-    Args:
-        frame: The image to be processed (OpenCV BGR format).
-
-    Returns:
-        bool: True if fire is detected, False otherwise.
-    """
-
-    # Convert image to RGB format for YOLOv8 compatibility
-    image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
-
-    # Make predictions using YOLOv8 (modify class ID if needed)
-    results = model(image)
-
-    # Check for fire detections or color thresholding
-    fire_detected = False
-    for detection in results.pandas().xyxy[0]:  # Assuming single image inference
-        class_id = int(detection['name'])  # Get class ID (adjust based on your dataset)
-        if (class_id == 0 or  # Check for fire class (adjust for your model)
-            cv2.inRange(cv2.cvtColor(frame, cv2.COLOR_BGR2HSV), lower_red, upper_red).any()):  # Check for fire color range
-            fire_detected = True
-            break  # Stop iterating after finding fire
-
-    return fire_detected
-
-def main():
-    """Captures video from webcam, detects fire, and displays results."""
-
-    cap = cv2.VideoCapture(0)  # 0 for default camera
-
-    while True:
-        ret, frame = cap.read()
-
-        if not ret:
-            print("Error: Could not read frame.")
-            break
-
-        # Detect fire
-        fire_detected = detect_fire(frame)
+webcamera = cv2.VideoCapture(0)
+# webcamera.set(cv2.CAP_PROP_FRAME_WIDTH, 1920)
+# webcamera.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080)
 
-        # Display results (modify text/color as needed)
-        if fire_detected:
-            cv2.putText(frame, "Fire Detected!", (10, 30), cv2.FONT_HERSHEY_SIMPLEX,
-                        1, (0, 0, 255), 2, cv2.LINE_AA)
-        else:
-            cv2.putText(frame, "No Fire Detected", (10, 30), cv2.FONT_HERSHEY_SIMPLEX,
-                        1, (0, 255, 0), 2, cv2.LINE_AA)
+while True:
+    success, frame = webcamera.read()
+    
+    results = model.track(frame, classes=0, conf=0.8, imgsz=480)
+    cv2.putText(frame, f"Total: {len(results[0].boxes)}", (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2, cv2.LINE_AA)
+    cv2.imshow("Live Camera", results[0].plot())
 
-        cv2.imshow('Fire Detection', frame)
+    if cv2.waitKey(1) == ord('q'):
+        break
 
-        if cv2.waitKey(1) & 0xFF == ord('q'):
-            break
+webcamera.release()
+cv2.destroyAllWindows()
 
-    cap.release()
-    cv2.destroyAllWindows()
 
-if __name__ == '__main__':
-    main()