app.py

import streamlit as st
import cv2
import tempfile
from ultralytics import YOLO
import imageio
import os

# ---------------- YOLO Model ----------------
st.title("🎥 YOLOv8 Object Tracking on Video")
model = YOLO("yolov8n.pt")  # Pretrained YOLOv8n model

# ---------------- Function to Process Video ----------------
def detect_objects_in_video(video_path):
    cap = cv2.VideoCapture(video_path)
    fps = int(cap.get(cv2.CAP_PROP_FPS)) or 25

    # Temporary output file
    temp_output = tempfile.NamedTemporaryFile(delete=False, suffix=".mp4")
    output_path = temp_output.name
    temp_output.close()

    writer = imageio.get_writer(output_path, fps=fps, codec="libx264")

    stframe = st.empty()
    total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
    processed_frames = 0

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

        results = model(frame, imgsz=1280, conf=0.25)
        annotated_frame = results[0].plot()

        writer.append_data(cv2.cvtColor(annotated_frame, cv2.COLOR_BGR2RGB))

        # Progress bar
        processed_frames += 1
        stframe.text(f"Processing frame {processed_frames}/{total_frames}...")

    cap.release()
    writer.close()

    # Read video as bytes for Streamlit
    with open(output_path, "rb") as f:
        video_bytes = f.read()

    try:
        os.remove(output_path)
    except PermissionError:
        pass

    return video_bytes

# ---------------- Streamlit UI ----------------
st.write("Upload a video and see detections in MP4 format.")

uploaded_file = st.file_uploader("Upload a video", type=["mp4", "mov", "avi"])

if uploaded_file is not None:
    # Save uploaded video to temp file
    temp_input = tempfile.NamedTemporaryFile(delete=False, suffix=".mp4")
    temp_input.write(uploaded_file.read())
    temp_input.close()

    st.subheader("📥 Original Video")
    st.video(temp_input.name)  # Display original video

    st.write("🔄 Processing video with YOLOv8... please wait")
    video_bytes = detect_objects_in_video(temp_input.name)

    st.subheader("✅ Processed Video")
    st.video(video_bytes)  # Display processed video

    st.download_button(
        label="⬇️ Download Processed Video",
        data=video_bytes,
        file_name="processed_output.mp4",
        mime="video/mp4"
    )

    # Cleanup
    try:
        os.remove(temp_input.name)
    except PermissionError:
        pass