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| import whisper | |
| from pytube import YouTube | |
| import requests, io | |
| from urllib.request import urlopen | |
| from PIL import Image | |
| import time | |
| import streamlit as st | |
| from streamlit_lottie import st_lottie | |
| import numpy as np | |
| import os | |
| st.set_page_config(page_title="Youtube Transcriber", page_icon="🗣", layout="wide") | |
| # Define a function that we can use to load lottie files from a link. | |
| 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://assets9.lottiefiles.com/private_files/lf30_bntlaz7t.json") | |
| st_lottie(lottie, speed=1, height=200, width=200) | |
| with col2: | |
| st.write(""" | |
| ## Youtube Transcriber | |
| ##### This is an app that transcribes YouTube videos into text.""") | |
| #def load_model(size): | |
| #default_size = size | |
| #if size == default_size: | |
| #return None | |
| #else: | |
| #loaded_model = whisper.load_model(size) | |
| #return loaded_model | |
| 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 | |
| # Uncomment if you want to fetch the thumbnails as well. | |
| #def fetch_thumbnail(thumbnail): | |
| #tnail = urlopen(thumbnail) | |
| #raw_data = tnail.read() | |
| #image = Image.open(io.BytesIO(raw_data)) | |
| #st.image(image, use_column_width=True) | |
| def convert(seconds): | |
| #return time.strftime("%H:%M:%S", time.gmtime(seconds)) | |
| loaded_model = whisper.load_model("small") | |
| #current_size = "None" | |
| #size = st.selectbox("Model Size", ["tiny", "base", "small", "medium", "large"], index=1) | |
| def change_model(current_size, size): | |
| if current_size != size: | |
| loaded_model = whisper.load_model(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.") | |
| return loaded_model | |
| else: | |
| return None | |
| def inference(link): | |
| yt = YouTube(link) | |
| path = yt.streams.filter(only_audio=True)[0].download(filename="audio.mp4") | |
| results = loaded_model.transcribe(path) | |
| return results["text"] | |
| def main(): | |
| change_model(current_size, size) | |
| link = st.text_input("YouTube Link") | |
| if st.button("Transcribe"): | |
| author, title, description, thumbnail, length, views = populate_metadata(link) | |
| results = inference(link) | |
| col3, col4 = st.columns(2) | |
| with col3: | |
| #fetch_thumbnail(thumbnail) | |
| st.video(link) | |
| st.markdown(f"**Channel**: {author}") | |
| st.markdown(f"**Title**: {title}") | |
| st.markdown(f"**Length**: {convert(length)}") | |
| st.markdown(f"**Views**: {views:,}") | |
| with col4: | |
| with st.expander("Video Description"): | |
| st.write(description) | |
| #st.markdown(f"**Video Description**: {description}") | |
| with st.expander("Video Transcript"): | |
| st.write(results) | |
| # Write the results to a .txt file and download it. | |
| with open("transcript.txt", "w+") as f: | |
| f.writelines(results) | |
| f.close() | |
| with open(os.path.join(os.getcwd(), "transcript.txt"), "rb") as f: | |
| data = f.read() | |
| if st.download_button(label="Download Transcript", | |
| data=data, | |
| file_name="transcript.txt"): | |
| st.success("Downloaded Successfully!") | |
| if __name__ == "__main__": | |
| main() |