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import gradio as gr
import os
import subprocess
import whisper
from whisper.utils import write_vtt
model = whisper.load_model("small")
def video2mp3(video_file, output_ext="mp3"):
filename, ext = os.path.splitext(video_file)
subprocess.call(["ffmpeg", "-y", "-i", video_file, f"{filename}.{output_ext}"],
stdout=subprocess.DEVNULL,
stderr=subprocess.STDOUT)
return f"{filename}.{output_ext}"
def transcribe_audio(file):
options = dict(task="transcribe", best_of=5, fp16 = False)
text = model.transcribe(file, **options)["text"]
return text.strip()
def translate_audio(file):
options = dict(task="translate", best_of=5, fp16 = False)
text = model.transcribe(file, **options)["text"]
return text.strip()
def translate_video(input_video):
audio_file = video2mp3(input_video)
options = dict(beam_size=5, best_of=5, fp16 = False)
translate_options = dict(task="translate", **options)
result = model.transcribe(audio_file,**translate_options)
output_dir = '/content/'
audio_path = audio_file.split(".")[0]
with open(os.path.join(output_dir, audio_path + ".vtt"), "w") as vtt:
write_vtt(result["segments"], file=vtt)
subtitle = audio_path + ".vtt"
output_video = audio_path + "_subtitled.mp4"
os.system(f"ffmpeg -i {input_video} -vf subtitles={subtitle} {output_video}")
return output_video
block = gr.Blocks()
with block:
with gr.Group():
with gr.Box():
with gr.Row().style():
inp_video = gr.Video(
label="Input Video",
type="filepath",
mirror_webcam = False
)
op_video = gr.Video()
btn = gr.Button("Generate Subtitle Video")
btn.click(translate_video, inputs=[inp_video], outputs=[op_video])
with gr.Group():
audio = gr.Audio(
show_label=False,
source="microphone",
type="filepath"
)
with gr.Box():
with gr.Row().style(equal_height=True):
transcribe_button = gr.Button("Transcribe")
translate_button = gr.Button("Translate")
textbox = gr.Textbox(show_label=False)
transcribe_button.click(transcribe_audio, inputs=[audio], outputs=[textbox])
translate_button.click(translate_audio, inputs=[audio], outputs=[textbox])
block.launch(debug = True) |