Update app.py

app.py

@@ -1,87 +0,0 @@
-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