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import whisper
from pytube import YouTube
import requests
import time
import streamlit as st
from streamlit_lottie import st_lottie
import numpy as np
import os
from typing import Iterator
from io import StringIO
from utils import write_vtt, write_srt
import ffmpeg
from languages import LANGUAGES
st.set_page_config(page_title="Auto Subtitled Video Generator", page_icon=":movie_camera:", layout="wide")
# Define a function that we can use to load lottie files from a link.
@st.cache(allow_output_mutation=True)
def load_lottieurl(url: str):
r = requests.get(url)
if r.status_code != 200:
return None
return r.json()
col1, col2 = st.columns([1, 3])
with col1:
lottie = load_lottieurl("https://assets8.lottiefiles.com/packages/lf20_jh9gfdye.json")
st_lottie(lottie, speed=1, height=250, width=250)
with col2:
st.write("""
## Auto Subtitled Video Generator
##### Input a YouTube video link and get a video with subtitles.
###### ➠ If you want to transcribe the video in its original language, select the task as "Transcribe"
###### ➠ If you want to translate the subtitles to English, select the task as "Translate"
###### I recommend starting with the base model and then experimenting with the larger models, the small and medium models often work well. """)
@st.cache(allow_output_mutation=True)
def populate_metadata(link):
yt = YouTube(link)
author = yt.author
title = yt.title
description = yt.description
thumbnail = yt.thumbnail_url
length = yt.length
views = yt.views
return author, title, description, thumbnail, length, views
@st.cache(allow_output_mutation=True)
def download_video(link):
yt = YouTube(link)
video = yt.streams.filter(progressive=True, file_extension='mp4').order_by('resolution').desc().first().download()
return video
def convert(seconds):
return time.strftime("%H:%M:%S", time.gmtime(seconds))
loaded_model = whisper.load_model("base")
current_size = "None"
@st.cache(allow_output_mutation=True)
def change_model(current_size, size):
if current_size != size:
loaded_model = whisper.load_model(size)
return loaded_model
else:
raise Exception("Model size is the same as the current size.")
@st.cache(allow_output_mutation=True)
def inference(link, loaded_model, task):
yt = YouTube(link)
path = yt.streams.filter(only_audio=True)[0].download(filename="audio.mp3")
if task == "Transcribe":
options = dict(task="transcribe", best_of=5)
results = loaded_model.transcribe(path, **options)
vtt = getSubs(results["segments"], "vtt", 80)
srt = getSubs(results["segments"], "srt", 80)
lang = results["language"]
return results["text"], vtt, srt, lang
elif task == "Translate":
options = dict(task="translate", best_of=5)
results = loaded_model.transcribe(path, **options)
vtt = getSubs(results["segments"], "vtt", 80)
srt = getSubs(results["segments"], "srt", 80)
lang = results["language"]
return results["text"], vtt, srt, lang
else:
raise ValueError("Task not supported")
@st.cache(allow_output_mutation=True)
def getSubs(segments: Iterator[dict], format: str, maxLineWidth: int) -> str:
segmentStream = StringIO()
if format == 'vtt':
write_vtt(segments, file=segmentStream, maxLineWidth=maxLineWidth)
elif format == 'srt':
write_srt(segments, file=segmentStream, maxLineWidth=maxLineWidth)
else:
raise Exception("Unknown format " + format)
segmentStream.seek(0)
return segmentStream.read()
def get_language_code(language):
if language in LANGUAGES.keys():
detected_language = LANGUAGES[language]
return detected_language
else:
raise ValueError("Language not supported")
def generate_subtitled_video(video, audio, transcript):
video_file = ffmpeg.input(video)
audio_file = ffmpeg.input(audio)
ffmpeg.concat(video_file.filter("subtitles", transcript), audio_file, v=1, a=1).output("final.mp4").run(quiet=True, overwrite_output=True)
video_with_subs = open("final.mp4", "rb")
return video_with_subs
def main():
size = st.selectbox("Select Model Size (The larger the model, the more accurate the transcription will be, but it will take longer)", ["tiny", "base", "small", "medium", "large"], index=1)
loaded_model = change_model(current_size, size)
st.write(f"Model is {'multilingual' if loaded_model.is_multilingual else 'English-only'} "
f"and has {sum(np.prod(p.shape) for p in loaded_model.parameters()):,} parameters.")
link = st.text_input("YouTube Link (The longer the video, the longer the processing time)")
task = st.selectbox("Select Task", ["Transcribe", "Translate"], index=0)
if task == "Transcribe":
if st.button("Transcribe"):
author, title, description, thumbnail, length, views = populate_metadata(link)
results = inference(link, loaded_model, task)
video = download_video(link)
lang = results[3]
detected_language = get_language_code(lang)
col3, col4 = st.columns(2)
col5, col6, col7, col8 = st.columns(4)
col9, col10 = st.columns(2)
with col3:
st.video(video)
# Write the results to a .txt file and download it.
with open("transcript.txt", "w+", encoding='utf8') as f:
f.writelines(results[0])
f.close()
with open(os.path.join(os.getcwd(), "transcript.txt"), "rb") as f:
datatxt = f.read()
with open("transcript.vtt", "w+",encoding='utf8') as f:
f.writelines(results[1])
f.close()
with open(os.path.join(os.getcwd(), "transcript.vtt"), "rb") as f:
datavtt = f.read()
with open("transcript.srt", "w+",encoding='utf8') as f:
f.writelines(results[2])
f.close()
with open(os.path.join(os.getcwd(), "transcript.srt"), "rb") as f:
datasrt = f.read()
with col5:
st.download_button(label="Download Transcript (.txt)",
data=datatxt,
file_name="transcript.txt")
with col6:
st.download_button(label="Download Transcript (.vtt)",
data=datavtt,
file_name="transcript.vtt")
with col7:
st.download_button(label="Download Transcript (.srt)",
data=datasrt,
file_name="transcript.srt")
with col9:
st.success("You can download the transcript in .srt format, edit it (if you need to) and upload it to YouTube to create subtitles for your video.")
with col10:
st.info("Streamlit refreshes after the download button is clicked. The data is cached so you can download the transcript again without having to transcribe the video again.")
with col4:
with st.spinner("Generating Subtitled Video"):
video_with_subs = generate_subtitled_video(video, "audio.mp3", "transcript.srt")
st.video(video_with_subs)
st.balloons()
with col8:
st.download_button(label="Download Subtitled Video",
data=video_with_subs,
file_name=f"{title} with subtitles.mp4")
elif task == "Translate":
if st.button("Translate to English"):
author, title, description, thumbnail, length, views = populate_metadata(link)
results = inference(link, loaded_model, task)
video = download_video(link)
lang = results[3]
detected_language = get_language_code(lang)
col3, col4 = st.columns(2)
col5, col6, col7, col8 = st.columns(4)
col9, col10 = st.columns(2)
with col3:
st.video(video)
# Write the results to a .txt file and download it.
with open("transcript.txt", "w+", encoding='utf8') as f:
f.writelines(results[0])
f.close()
with open(os.path.join(os.getcwd(), "transcript.txt"), "rb") as f:
datatxt = f.read()
with open("transcript.vtt", "w+",encoding='utf8') as f:
f.writelines(results[1])
f.close()
with open(os.path.join(os.getcwd(), "transcript.vtt"), "rb") as f:
datavtt = f.read()
with open("transcript.srt", "w+",encoding='utf8') as f:
f.writelines(results[2])
f.close()
with open(os.path.join(os.getcwd(), "transcript.srt"), "rb") as f:
datasrt = f.read()
with col5:
st.download_button(label="Download Transcript (.txt)",
data=datatxt,
file_name="transcript.txt")
with col6:
st.download_button(label="Download Transcript (.vtt)",
data=datavtt,
file_name="transcript.vtt")
with col7:
st.download_button(label="Download Transcript (.srt)",
data=datasrt,
file_name="transcript.srt")
with col9:
st.success("You can download the transcript in .srt format, edit it (if you need to) and upload it to YouTube to create subtitles for your video.")
with col10:
st.info("Streamlit refreshes after the download button is clicked. The data is cached so you can download the transcript again without having to transcribe the video again.")
with col4:
with st.spinner("Generating Subtitled Video"):
video_with_subs = generate_subtitled_video(video, "audio.mp3", "transcript.srt")
st.video(video_with_subs)
st.balloons()
with col8:
st.download_button(label="Download Subtitled Video",
data=video_with_subs,
file_name=f"{title} with subtitles.mp4")
else:
st.error("Please select a task.")
if __name__ == "__main__":
main()
st.markdown("###### Made with :heart: by [@BatuhanYılmaz](https://twitter.com/batuhan3326) [](https://www.buymeacoffee.com/batuhanylmz)") |