app.py

import tempfile
import gradio as gr
import subprocess
import os, stat
from googletrans import Translator
from TTS.api import TTS
import ffmpeg
import whisper
from scipy.signal import wiener
import soundfile as sf
from pydub import AudioSegment
import numpy as np
import librosa
from zipfile import ZipFile
import shlex
import librosa
import numpy as np
import cv2
import torch
import torchvision
from tqdm import tqdm
from numba import jit

os.environ["COQUI_TOS_AGREED"] = "1"

ZipFile("ffmpeg.zip").extractall()
st = os.stat('ffmpeg')
os.chmod('ffmpeg', st.st_mode | stat.S_IEXEC)

def process_video(video, high_quality, target_language):
    output_filename = "resized_video.mp4"
    if high_quality:
        ffmpeg.input(video).output(output_filename, vf='scale=-1:720').run()
        video_path = output_filename
    else:
        video_path = video

    # Debugging Step 1: Check if video_path exists
    if not os.path.exists(video_path):
        return f"Error: {video_path} does not exist."

    ffmpeg.input(video_path).output('output_audio.wav', acodec='pcm_s24le', ar=48000, map='a').run()

    y, sr = sf.read("output_audio.wav")
    y = y.astype(np.float32)
    y_denoised = wiener(y)
    sf.write("output_audio_denoised.wav", y_denoised, sr)

    sound = AudioSegment.from_file("output_audio_denoised.wav", format="wav")
    sound = sound.apply_gain(0)  # Reduce gain by 5 dB
    sound = sound.low_pass_filter(3000).high_pass_filter(100)
    sound.export("output_audio_processed.wav", format="wav")

    shell_command = f"ffmpeg -y -i output_audio_processed.wav -af lowpass=3000,highpass=100 output_audio_final.wav".split(" ")
    subprocess.run([item for item in shell_command], capture_output=False, text=True, check=True)

    model = whisper.load_model("base")
    result = model.transcribe("output_audio_final.wav")
    whisper_text = result["text"]
    whisper_language = result['language']
    
    print(whisper_text)
    
    language_mapping = {'English': 'en', 'Spanish': 'es', 'French': 'fr', 'German': 'de', 'Italian': 'it', 'Portuguese': 'pt', 'Polish': 'pl', 'Turkish': 'tr', 'Russian': 'ru', 'Dutch': 'nl', 'Czech': 'cs', 'Arabic': 'ar', 'Chinese (Simplified)': 'zh-cn'}
    target_language_code = language_mapping[target_language]
    translator = Translator()
    try:
        translated_text = translator.translate(whisper_text, src=whisper_language, dest=target_language_code).text
        print(translated_text)
    except AttributeError as e:
        print("Failed to translate text. Likely an issue with token extraction in the Google Translate API.")
        translated_text = "Translation failed due to API issue."


        
    tts = TTS("tts_models/multilingual/multi-dataset/xtts_v1")
    tts.to('cuda')  # Replacing deprecated gpu=True
    tts.tts_to_file(translated_text, speaker_wav='output_audio_final.wav', file_path="output_synth.wav", language=target_language_code)

    pad_top = 0
    pad_bottom = 15
    pad_left = 0
    pad_right = 0
    rescaleFactor = 1

    # Debugging Step 2: Remove quotes around the video path
    video_path_fix = video_path

    cmd = f"python Wav2Lip/inference.py --checkpoint_path 'Wav2Lip/checkpoints/wav2lip_gan.pth' --face {shlex.quote(video_path_fix)} --audio 'output_synth.wav' --pads {pad_top} {pad_bottom} {pad_left} {pad_right} --resize_factor {rescaleFactor} --nosmooth --outfile 'output_video.mp4'"
    subprocess.run(cmd, shell=True)
    # Debugging Step 3: Check if output video exists
    if not os.path.exists("output_video.mp4"):
        raise FileNotFoundError("Error: output_video.mp4 was not generated.")
    return "output_video.mp4"

iface = gr.Interface(
    fn=process_video,
    inputs=[
        gr.Video(),
        gr.inputs.Checkbox(label="High Quality"),
        gr.inputs.Dropdown(choices=["English", "Spanish", "French", "German", "Italian", "Portuguese", "Polish", "Turkish", "Russian", "Dutch", "Czech", "Arabic", "Chinese (Simplified)"], label="Target Language for Dubbing")
    ],
    outputs=gr.outputs.File(),
    live=False
)

iface.launch()