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import streamlit as st | |
from PIL import Image | |
from youtube_downloader import Download | |
from collections import deque | |
from prediction import Predict | |
downld=Download() | |
st.snow() | |
st.title("Human Action Recognization [DL]") | |
with st.expander("Details", expanded=False): | |
st.write(''' | |
need to add the details as this is under development''') | |
url= st.text_input("Insert Youtube Url as instructed above ") | |
if st.button("submit"): | |
title, output_dir=downld.youtube_d(url) | |
col1, col2 = st.columns([2, 2]) | |
with col1: | |
st.success('Video Downloaded!', icon="β ") | |
print(output_dir) | |
st.video(f"{output_dir}/{title}.mp4") | |
with col2: | |
st.info("Wait a while Model is Performing its Task") | |
pred =Predict() | |
frames_needed=25 | |
input_path=f"{output_dir}/{title}.mp4" | |
output_path=f"test_videos/{title}_output.mp4" | |
pred.prediction(input_path,output_path ,frames_needed) | |
st.video(output_path) | |
st.balloons() | |