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from transformers import pipeline
import gradio as gr
import time
from video_downloader import download_video1
from moviepy.editor import AudioFileClip, VideoFileClip
from moviepy.video.io.ffmpeg_tools import ffmpeg_extract_subclip
import datetime
import os
from pydub import AudioSegment
from pydub.silence import split_on_silence
pipe = pipeline("automatic-speech-recognition", model="Artanis1551/whisper_swedish")
def process_video1(date):
video_path = download_video1(date)
# Get the duration of the video
video = VideoFileClip(video_path)
duration = video.duration
# If the video is longer than 30 seconds, only take the first 30 seconds
if duration > 30:
video_path = f"short_{date}.mp4"
ffmpeg_extract_subclip(video_path, 0, 30, targetname=video_path)
# Extract audio from the video
audio_path = f"audio_{date}.wav"
AudioFileClip(video_path).write_audiofile(audio_path)
# Split the audio into chunks
audio = AudioSegment.from_wav(audio_path)
chunks = split_on_silence(audio, min_silence_len=500, silence_thresh=-40)
# Transcribe each chunk
transcription = ""
for i, chunk in enumerate(chunks):
chunk.export(f"chunk{i}.wav", format="wav")
with open(f"chunk{i}.wav", "rb") as audio_file:
audio = audio_file.read()
transcription += pipe(audio)["text"] + "\n "
os.remove(f"chunk{i}.wav")
# Remove the audio file
os.remove(audio_path)
return video_path, transcription
iface = gr.Interface(
fn=process_video1,
inputs=[
gr.inputs.Textbox(label="Date with format YYYY-MM-DD"),
],
outputs=[
gr.outputs.Video(),
gr.Textbox(lines=1000, max_lines=100, interactive=True),
],
title="Transcribe Swedish Parliament Decisions",
description="This app transcribes the top Swedish Parliament decision"
+ " video from the given date. Only the first 30 seconds of the "
+ "video will be used if it is longer than that.",
)
iface.launch()
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