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Update pages/02_📼_Upload_Video_File.py
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pages/02_📼_Upload_Video_File.py
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@@ -2,6 +2,7 @@ import whisper
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import streamlit as st
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from streamlit_lottie import st_lottie
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from utils import write_vtt, write_srt
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import ffmpeg
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import requests
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from typing import Iterator
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@@ -12,6 +13,9 @@ import os
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st.set_page_config(page_title="Semaitles", page_icon=":movie_camera:", layout="wide")
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# Define a function that we can use to load lottie files from a link.
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@st.cache(allow_output_mutation=True)
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def load_lottieurl(url: str):
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@@ -102,7 +106,33 @@ def generate_subtitled_video(video, audio, transcript):
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video_with_subs = open("final.mp4", "rb")
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return video_with_subs
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def main():
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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)
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loaded_model = change_model(current_size, size)
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import streamlit as st
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from streamlit_lottie import st_lottie
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from utils import write_vtt, write_srt
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from flores200_codes import flores_codes
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import ffmpeg
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import requests
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from typing import Iterator
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st.set_page_config(page_title="Semaitles", page_icon=":movie_camera:", layout="wide")
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# Sema Translator
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Public_Url = 'https://lewiskimaru-helloworld.hf.space' #endpoint
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# Define a function that we can use to load lottie files from a link.
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@st.cache(allow_output_mutation=True)
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def load_lottieurl(url: str):
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video_with_subs = open("final.mp4", "rb")
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return video_with_subs
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def translate(userinput, target_lang, source_lang=None):
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if source_lang:
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url = f"{Public_Url}/translate_enter/"
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data = {
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"userinput": userinput,
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"source_lang": source_lang,
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"target_lang": target_lang,
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}
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response = requests.post(url, json=data)
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result = response.json()
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print(type(result))
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source_lange = source_lang
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translation = result['translated_text']
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else:
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url = f"{Public_Url}/translate_detect/"
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data = {
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"userinput": userinput,
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"target_lang": target_lang,
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}
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response = requests.post(url, json=data)
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result = response.json()
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source_lange = result['source_language']
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translation = result['translated_text']
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return source_lange, translation
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def main():
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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)
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loaded_model = change_model(current_size, size)
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