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import os
import gradio as gr
from moviepy.video.io.VideoFileClip import VideoFileClip
from pydub import AudioSegment
import whisper
from transformers import pipeline, MarianMTModel, MarianTokenizer
import yt_dlp as youtube_dl
def download_youtube_video(url):
try:
os.system(f"yt-dlp -o video.mp4 {url}")
return "video.mp4"
except Exception as e:
return str(e)
def extract_audio(video_path):
try:
audio = AudioSegment.from_file(video_path)
audio.export("extracted_audio.mp3", format="mp3")
return "extracted_audio.mp3"
except Exception as e:
return str(e)
def transcribe_audio(audio_path):
try:
model = whisper.load_model("base")
result = model.transcribe(audio_path)
return result['text']
except Exception as e:
return str(e)
def summarize_text(text):
try:
summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
summary = summarizer(text, max_length=150, min_length=30, do_sample=False)
return summary[0]['summary_text']
except Exception as e:
return str(e)
def translate_text(text, tgt_lang="es"):
try:
model_name = f"Helsinki-NLP/opus-mt-en-{tgt_lang}"
tokenizer = MarianTokenizer.from_pretrained(model_name)
model = MarianMTModel.from_pretrained(model_name)
translated = model.generate(**tokenizer(text, return_tensors="pt", padding=True))
return tokenizer.decode(translated[0], skip_special_tokens=True)
except Exception as e:
return str(e)
def process_video(video_file, youtube_url):
if youtube_url:
video_path = download_youtube_video(youtube_url)
elif video_file:
video_path = video_file.name
else:
return "No valid input provided."
audio_path = extract_audio(video_path)
transcription = transcribe_audio(audio_path)
return transcription
def summarize_and_translate(text, lang):
summary = summarize_text(text)
translation = translate_text(summary, lang)
return summary, translation
with gr.Blocks() as app:
gr.Markdown("# 🎥 Smart Video-to-Text Summarization App")
with gr.Row():
video_upload = gr.File(label="Upload Video File", type="filepath")
youtube_link = gr.Textbox(label="YouTube URL")
process_button = gr.Button("🚀 Process Video")
transcription_output = gr.Textbox(label="Transcription", interactive=False)
process_button.click(process_video, inputs=[video_upload, youtube_link], outputs=transcription_output)
summarize_button = gr.Button("📝 Summarize Text")
summary_output = gr.Textbox(label="Summary", interactive=False)
translate_button = gr.Button("🌍 Translate Summary")
language_dropdown = gr.Dropdown(choices=["es", "fr", "de", "zh"], label="Select Translation Language")
translated_output = gr.Textbox(label="Translated Summary", interactive=False)
summarize_button.click(summarize_text, inputs=transcription_output, outputs=summary_output)
translate_button.click(summarize_and_translate, inputs=[transcription_output, language_dropdown], outputs=[summary_output, translated_output])
app.launch()
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