Create app.py

app.py

@@ -0,0 +1,165 @@
+from TTS.api import TTS
+tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2", gpu=True).to("cuda")
+# Dependencies
+%cd /content/
+
+import locale
+locale.getpreferredencoding = lambda: "UTF-8"
+
+!git clone https://github.com/justinjohn0306/Wav2Lip
+!cd Wav2Lip && pip install -r requirements_colab.txt
+
+%cd /content/Wav2Lip
+
+!wget "https://www.adrianbulat.com/downloads/python-fan/s3fd-619a316812.pth" -O "face_detection/detection/sfd/s3fd.pth"
+!wget 'https://github.com/justinjohn0306/Wav2Lip/releases/download/models/wav2lip.pth' -O 'checkpoints/wav2lip.pth'
+!wget 'https://github.com/justinjohn0306/Wav2Lip/releases/download/models/wav2lip_gan.pth' -O 'checkpoints/wav2lip_gan.pth'
+!wget 'https://github.com/justinjohn0306/Wav2Lip/releases/download/models/resnet50.pth' -O 'checkpoints/resnet50.pth'
+!wget 'https://github.com/justinjohn0306/Wav2Lip/releases/download/models/mobilenet.pth' -O 'checkpoints/mobilenet.pth'
+import subprocess
+import assemblyai as aai
+import requests
+import moviepy.editor as mp
+
+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):
+        if original_language == 'English':
+            self.lan_code='en'
+        elif original_language =='German':
+            self.lan_code='de'
+        elif original_language =='French':
+            self.lan_code='fr'
+        elif original_language =='Spanish':
+            self.lan_code='es'
+        else:
+            self.lan_code = ''
+
+  def target_language_parameters(self,target_language):
+        if target_language == 'English':
+            self.tran_code='en'
+        elif target_language =='German':
+            self.tran_code='de'
+        elif target_language =='French':
+            self.tran_code='fr'
+        elif target_language =='Spanish':
+            self.tran_code='es'
+        else:
+            self.tran_code = ''
+
+  def extract_audio(self):
+          video = mp.VideoFileClip(self.video_path)
+          audio = video.audio
+          audio_path = "output_audio.wav"
+          audio.write_audiofile(audio_path)
+          print("Audio extracted successfully!")
+          return audio_path
+
+
+  def transcribe_audio(self,audio_path):
+      aai.settings.api_key = "c29eb650444a4ae4be6a787ebb15d5e2"
+      config = aai.TranscriptionConfig(language_code=self.lan_code)
+      transcriber = aai.Transcriber(config=config)
+      transcript = transcriber.transcribe(audio_path)
+      transcript_text = transcript.text
+      return transcript_text
+      if transcript.status == aai.TranscriptStatus.error:
+          print(transcript.error)
+          return None
+
+
+  def translate_text(self,transcript_text):
+          base_url = "https://api.cognitive.microsofttranslator.com"
+          endpoint = "/translate"
+          headers = {
+              "Ocp-Apim-Subscription-Key": "cd226bb1f3644276bea01d82dd861cbb",
+              "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 + endpoint, headers=headers, params=params, json=body)
+          response.raise_for_status()
+          translation = response.json()[0]["translations"][0]["text"]
+          return translation
+
+
+
+
+        #generate audio
+  def generate_audio(self,translated_text):
+      tts.tts_to_file(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)
+      #Generate video
+    %cd /content/Wav2Lip
+
+      #This is the detection box padding, if you see it doesnt sit quite right, just adjust the values a bit. Usually the bottom one is the biggest issue
+    pad_top =  0
+    pad_bottom =  15
+    pad_left =  0
+    pad_right =  0
+    rescaleFactor =  1
+    video_path_fix = f"'../{self.video_path}'"
+    audio_path_fix = f"'../{translated_audio_path}'"
+    !python inference.py --checkpoint_path 'checkpoints/wav2lip_gan.pth' --face $video_path_fix --audio $audio_path_fix --pads $pad_top $pad_bottom $pad_left $pad_right --resize_factor $rescaleFactor --nosmooth --outfile '/content/output_video.mp4'
+    return '/content/output_video.mp4'  # Return the path to the translated video file
+    # return '/content/output_video.mp4', open('/content/output_video.mp4', 'rb')  # Return the path and file object of the translated video file
+
+# from translator import translation  # Import the Translator class from translate module
+import gradio as gr
+import os
+from google.colab import files
+
+
+def app(video_path, original_language, target_language):
+    %cd /content/
+
+    video_name = os.path.basename(video_path)
+
+    # Save the uploaded file to the content folder in Colab
+    with open(video_name, "wb") as f:
+        with open(video_path, "rb") as uploaded_file:
+            f.write(uploaded_file.read())
+
+
+    translator = translation(video_name, original_language, target_language)
+    video_file = translator.translate_video()
+
+
+    return video_file
+
+interface_video_file = gr.Interface(
+    fn=app,
+    inputs=[
+        gr.Video(label="Video Path"),
+        gr.Dropdown(["English", "German", "French", "Spanish"], label="Original Language"),
+        gr.Dropdown(["English", "German", "French", "Spanish"], label="Targeted Language"),
+    ],
+    outputs=gr.Video(label="Translated Video")
+)
+
+interface_video_file.launch(debug=True)
+
+