| import streamlit as st | |
| from prediction import smartcities | |
| # Streamlit Interface | |
| st.header("Smart City Cars and Bikes detection") | |
| st.markdown("Upload a video or select the example") | |
| ## Select video to inference | |
| file_video = st.file_uploader(" Upload a video ", type=["mp4"]) | |
| # st.video(example) | |
| if st.button("example"): | |
| file_video = "test_video.mp4" | |
| ## Process video | |
| if file_video is not None: | |
| video = open(file_video, "wb") | |
| # output = smartcities(video) | |
| # video_bytes = video.read() | |
| # output = smartcities(video_bytes) | |
| col1, col2 = st.columns(2) | |
| if output is not None: | |
| with col1: | |
| st.subheader("Input: ") | |
| st.video(video) | |
| # st.video(video_bytes) | |
| # with col2: | |
| # st.subheader("Output: ") | |
| # st.video(output) | |
| # st.download_button("Download", output) | |