Update app.py

app.py

@@ -11,7 +11,7 @@ model = YOLO("best.pt")
 st.title("Fire Detection in Forest")
 
 # Sidebar for input options
-input_option = st.sidebar.selectbox("Select Input Method", ["Upload Image", "Use Webcam"])
+input_option = st.sidebar.selectbox("Select Input Method", ["Upload Image", "Use Webcam","Upload Video"])
 
 if input_option == "Upload Image":
     # Upload Image
@@ -76,3 +76,46 @@ elif input_option == "Use Webcam":
 
     # Release the camera
     camera.release()
+
+elif input_option == "Upload Video":
+    uploaded_video = st.file_uploader("choose a video",type=["mp4","avi","mov","mkv"])
+    if uploaded_video is not None:
+        # Save the uploaded video temporarily
+        temp_video_path = "temp_video.mp4"
+        with open(temp_video_path, "wb") as f:
+            f.write(uploaded_video.read())
+
+        # Open the video file
+        video_capture = cv2.VideoCapture(temp_video_path)
+
+        # Create a placeholder for the video frames
+        video_frame_placeholder = st.empty()
+
+        # Loop through video frames
+        while video_capture.isOpened():
+            ret, frame = video_capture.read()
+            if not ret:
+                st.write("Finished processing video.")
+                break
+
+            # Make predictions
+            results = model.predict(source=frame, conf=0.5)
+
+            # Draw bounding boxes on the frame
+            for result in results:
+                boxes = result.boxes.xyxy
+                for box in boxes:
+                    x1, y1, x2, y2 = box[:4].astype(int)
+                    frame = cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
+
+            # Convert frame to RGB
+            rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+
+            # Display the frame
+            video_frame_placeholder.image(rgb_frame, channels="RGB", use_column_width=True)
+
+        # Release the video capture
+        video_capture.release()
+
+    
+