Upload app.py

app.py

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+# streamlit_yolo_video.py
+
+import streamlit as st
+import cv2
+import numpy as np
+from ultralytics import YOLO
+import tempfile
+
+# -------------------------------
+# Streamlit App Title
+# -------------------------------
+st.title("YOLOv8 Object Detection on Video")
+
+# -------------------------------
+# Load YOLO Detection Model
+# -------------------------------
+@st.cache_resource
+def load_model(model_name="yolov8n.pt"):
+    return YOLO(model_name)
+
+model = load_model()
+
+# -------------------------------
+# Upload Video
+# -------------------------------
+uploaded_file = st.file_uploader("Upload a video", type=["mp4", "mov", "avi", "mkv"])
+
+if uploaded_file is not None:
+    # Save uploaded video temporarily
+    tfile = tempfile.NamedTemporaryFile(delete=False)
+    tfile.write(uploaded_file.read())
+    video_path = tfile.name
+
+    # Open video
+    cap = cv2.VideoCapture(video_path)
+    width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+    height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+    fps = cap.get(cv2.CAP_PROP_FPS)
+
+    # Output video writer
+    output_path = "output_video.mp4"
+    fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+    out = cv2.VideoWriter(output_path, fourcc, fps, (width, height))
+
+    stframe = st.empty()
+    st.info("Processing video... This may take some time depending on length.")
+
+    while cap.isOpened():
+        ret, frame = cap.read()
+        if not ret:
+            break
+
+        # YOLO expects RGB
+        frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+        results = model(frame_rgb)
+
+        # Annotated frame
+        annotated_frame = results[0].plot()
+        annotated_frame_bgr = cv2.cvtColor(annotated_frame, cv2.COLOR_RGB2BGR)
+
+        # Write frame to output video
+        out.write(annotated_frame_bgr)
+
+        # Display in Streamlit
+        stframe.image(annotated_frame, channels="RGB", use_column_width=True)
+
+    cap.release()
+    out.release()
+
+    st.success("Video processing completed!")
+
+    # Download button
+    with open(output_path, "rb") as f:
+        st.download_button("Download Annotated Video", f, "annotated_video.mp4")