Update app.py

app.py

@@ -1,46 +1,49 @@
+import streamlit as st
 import cv2
+import numpy as np
 from ultralytics import YOLO
-import streamlit as st
 from tempfile import NamedTemporaryFile
+import os
 
-# Load YOLOv8 model
+# Initialize YOLOv8 model
 model = YOLO("yolov8n.pt")
 
-# Streamlit UI
-st.title("🔍 YOLOv8 Object Detection on Video")
+# Streamlit app title and creator information
+st.markdown("Created by: [Engr. Hamesh Raj](https://www.linkedin.com/in/datascientisthameshraj/)")
+st.title("🎥 YOLOv8 Object Detection on Videos")
 
-# Upload video file
-uploaded_file = st.file_uploader("Upload Video", type=["mp4", "avi", "mov"])
+# Sidebar for video upload
+st.sidebar.header("Upload Video")
+uploaded_video = st.sidebar.file_uploader("Choose a video...", type=["mp4", "mov", "avi", "mkv"])
 
-if uploaded_file is not None:
+if uploaded_video is not None:
     # Save the uploaded video to a temporary file
-    temp_input_file = NamedTemporaryFile(delete=False)
-    temp_input_file.write(uploaded_file.read())
-    temp_input_file.flush()
+    temp_video = NamedTemporaryFile(delete=False)
+    temp_video.write(uploaded_video.read())
+    video_path = temp_video.name
 
     # Display the uploaded video
-    st.video(temp_input_file.name)
+    st.sidebar.video(uploaded_video)
 
-    # Define the output video file path
-    temp_output_file = NamedTemporaryFile(delete=False, suffix='.mp4')
+    # Submit button to process the video
+    if st.sidebar.button("Submit"):
+        st.subheader("Processing Video...")
 
-    # Open the input video file
-    cap = cv2.VideoCapture(temp_input_file.name)
-
-    # Check if the video was opened successfully
-    if not cap.isOpened():
-        st.error("Error: Could not open video file.")
-    else:
-        # Get video properties
+        # Open the video file
+        cap = cv2.VideoCapture(video_path)
         frame_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
         frame_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
         fps = cap.get(cv2.CAP_PROP_FPS)
 
+        # Create a temporary file to save the output video
+        temp_output_video = NamedTemporaryFile(delete=False, suffix='.mp4')
+        output_video_path = temp_output_video.name
+
         # Define codec and create VideoWriter object
-        fourcc = cv2.VideoWriter_fourcc(*'mp4v')  # Codec for .mp4 files
-        out = cv2.VideoWriter(temp_output_file.name, fourcc, fps, (frame_width, frame_height))
+        fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+        out = cv2.VideoWriter(output_video_path, fourcc, fps, (frame_width, frame_height))
 
-        # Process the video frame by frame
+        # Process each frame of the video
         while cap.isOpened():
             ret, frame = cap.read()
             if not ret:
@@ -49,38 +52,35 @@ if uploaded_file is not None:
             # Perform object detection
             results = model(frame)
 
-            # Access detection results
-            if results:
-                for result in results:
-                    boxes = result.boxes  # Access boxes attribute
-                    for box in boxes:
-                        x1, y1, x2, y2 = map(int, box.xyxy[0])
-                        conf = box.conf[0]
-                        cls = box.cls[0]
-                        label = f'{model.names[int(cls)]} {conf:.2f}'
-
-                        # Draw bounding boxes on the frame
-                        cv2.rectangle(frame, (x1, y1), (x2, y2), (255, 0, 0), 2)
-                        cv2.putText(frame, label, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (255, 0, 0), 2)
-
-            # Write the frame with bounding boxes to the output video
+            # Draw bounding boxes on the frame
+            for result in results:
+                for box in result.boxes:
+                    x1, y1, x2, y2 = map(int, box.xyxy[0])
+                    conf = box.conf[0]
+                    cls = box.cls[0]
+                    label = f'{model.names[int(cls)]} {conf:.2f}'
+
+                    cv2.rectangle(frame, (x1, y1), (x2, y2), (255, 0, 0), 2)
+                    cv2.putText(frame, label, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (255, 0, 0), 2)
+
             out.write(frame)
 
-        # Release resources
         cap.release()
         out.release()
-        cv2.destroyAllWindows()
 
-        st.success("Video processing complete!")
+        # Display the processed video
+        st.subheader("Processed Video")
+        st.video(output_video_path)
 
-        # Display the processed video in the browser
-        st.video(temp_output_file.name)
-
-        # Provide a download link for the processed video
-        with open(temp_output_file.name, 'rb') as file:
-            btn = st.download_button(
+        # Download button for the processed video
+        with open(output_video_path, "rb") as file:
+            st.download_button(
                 label="Download Processed Video",
                 data=file,
                 file_name="processed_video.mp4",
                 mime="video/mp4"
-            )
+            )
+
+        # Clean up temporary files
+        os.remove(video_path)
+        os.remove(output_video_path)