Update app.py

app.py

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+import os
+import requests
+import gradio as gr
+import moviepy.editor as mp
+from TTS.api import TTS
+import torch
+import assemblyai as aai
+
+# Download necessary models if not already present
+model_files = {
+    "wav2lip.pth": "https://github.com/justinjohn0306/Wav2Lip/releases/download/models/wav2lip.pth",
+    "wav2lip_gan.pth": "https://github.com/justinjohn0306/Wav2Lip/releases/download/models/wav2lip_gan.pth",
+    "resnet50.pth": "https://github.com/justinjohn0306/Wav2Lip/releases/download/models/resnet50.pth",
+    "mobilenet.pth": "https://github.com/justinjohn0306/Wav2Lip/releases/download/models/mobilenet.pth",
+    "s3fd.pth": "https://www.adrianbulat.com/downloads/python-fan/s3fd-619a316812.pth"
+}
+
+for filename, url in model_files.items():
+    file_path = os.path.join("checkpoints" if "pth" in filename else "face_detection", filename)
+    if not os.path.exists(file_path):
+        print(f"Downloading {filename}...")
+        r = requests.get(url)
+        with open(file_path, 'wb') as f:
+            f.write(r.content)
+
+# Initialize TTS model
+tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2", gpu=True)
+
+# Translation class
+class translation:
+    def _init_(self, video_path, original_language, target_language):
+        self.video_path = video_path
+        self.original_language = original_language
+        self.target_language = target_language
+
+    def org_language_parameters(self, original_language):
+        language_codes = {'English': 'en', 'German': 'de', 'Italian': 'it', 'Spanish': 'es'}
+        self.lan_code = language_codes.get(original_language, '')
+
+    def target_language_parameters(self, target_language):
+        language_codes = {'English': 'en', 'German': 'de', 'Italian': 'it', 'Spanish': 'es'}
+        self.tran_code = language_codes.get(target_language, '')
+
+    def extract_audio(self):
+        video = mp.VideoFileClip(self.video_path)
+        audio = video.audio
+        audio_path = "output_audio.wav"
+        audio.write_audiofile(audio_path)
+        return audio_path
+
+    def transcribe_audio(self, audio_path):
+        aai.settings.api_key = os.getenv("ASSEMBLYAI_API_KEY")
+        config = aai.TranscriptionConfig(language_code=self.lan_code)
+        transcriber = aai.Transcriber(config=config)
+        transcript = transcriber.transcribe(audio_path)
+        return transcript.text
+
+    def translate_text(self, transcript_text):
+        base_url = "https://api.cognitive.microsofttranslator.com/translate"
+        headers = {
+            "Ocp-Apim-Subscription-Key": os.getenv("MICROSOFT_TRANSLATOR_API_KEY"),
+            "Content-Type": "application/json",
+            "Ocp-Apim-Subscription-Region": "southeastasia"
+        }
+        params = {"api-version": "3.0", "from": self.lan_code, "to": self.tran_code}
+        body = [{"text": transcript_text}]
+        response = requests.post(base_url, headers=headers, params=params, json=body)
+        translation = response.json()[0]["translations"][0]["text"]
+        return translation
+
+    def generate_audio(self, translated_text):
+        tts.tts_to_file(text=translated_text, speaker_wav='output_audio.wav', file_path="output_synth.wav", language=self.tran_code)
+        return "output_synth.wav"
+
+    def translate_video(self):
+        audio_path = self.extract_audio()
+        self.org_language_parameters(self.original_language)
+        self.target_language_parameters(self.target_language)
+        transcript_text = self.transcribe_audio(audio_path)
+        translated_text = self.translate_text(transcript_text)
+        translated_audio_path = self.generate_audio(translated_text)
+
+        # Run Wav2Lip inference
+        os.system(f"python inference.py --checkpoint_path 'checkpoints/wav2lip_gan.pth' --face {self.video_path} --audio {translated_audio_path} --outfile 'output_video.mp4'")
+        return 'output_video.mp4'
+
+
+# Gradio Interface
+def app(video_path, original_language, target_language):
+    translator = translation(video_path, original_language, target_language)
+    video_file = translator.translate_video()
+    return video_file
+
+interface = gr.Interface(
+    fn=app,
+    inputs=[
+        gr.Video(label="Video Path"),
+        gr.Dropdown(["English", "German", "Italian", "Spanish"], label="Original Language"),
+        gr.Dropdown(["English", "German", "Italian", "Spanish"], label="Targeted Language"),
+    ],
+    outputs=gr.Video(label="Translated Video")
+)
+
+interface.launch()