Update app.py

app.py

@@ -2,25 +2,55 @@ import streamlit as st
 import cv2
 import numpy as np
 from ultralytics import YOLO
+import math
+
 
-# 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")
+# start webcam
 cap = cv2.VideoCapture(0)
 cap.set(3, 640)
 cap.set(4, 480)
 
+# Load the YOLO model
+model = YOLO("best.pt")  # Ensure the path to your model is correct
+
+
 while True:
-    ret, img= cap.read()
-    cv2.imshow('Webcam', img)
+    success, img = cap.read()
+    results = model(img, stream=True)
 
-    if cv2.waitKey(1) == ord('q'):
-        break
+    # coordinates
+    for r in results:
+        boxes = r.boxes
 
-cap.release()
-cv2.destroyAllWindows()
+        for box in boxes:
+            # bounding box
+            x1, y1, x2, y2 = box.xyxy[0]
+            x1, y1, x2, y2 = int(x1), int(y1), int(x2), int(y2) # convert to int values
+
+            # put box in cam
+            cv2.rectangle(img, (x1, y1), (x2, y2), (255, 0, 255), 3)
+
+            # confidence
+            confidence = math.ceil((box.conf[0]*100))/100
+            print("Confidence --->",confidence)
 
+            # class name
+            cls = int(box.cls[0])
+            print("Class name -->", classNames[cls])
 
+            # object details
+            org = [x1, y1]
+            font = cv2.FONT_HERSHEY_SIMPLEX
+            fontScale = 1
+            color = (255, 0, 0)
+            thickness = 2
 
+            cv2.putText(img, classNames[cls], org, font, fontScale, color, thickness)
+
+    cv2.imshow('Webcam', img)
+    if cv2.waitKey(1) == ord('q'):
+        break
+
+cap.release()
+cv2.destroyAllWindows()