Create app.py

app.py

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+import gradio as gr
+import moviepy.editor as mp
+from transformers import pipeline
+
+# Load Whisper model for speech-to-text
+asr = pipeline("automatic-speech-recognition", model="openai/whisper-large")
+
+# MarianMT or M2M100 for translation (multi-language)
+translator = pipeline("translation", model="facebook/m2m100_418M")
+
+def generate_subtitles(video_path, target_language):
+    # Extract audio from video
+    video = mp.VideoFileClip(video_path)
+    audio = video.audio
+    audio.write_audiofile("temp_audio.wav", codec='pcm_s16le')
+
+    # Convert speech to text (ASR using Whisper)
+    with open("temp_audio.wav", "rb") as audio_file:
+        transcription = asr(audio_file)["text"]
+
+    # Translate transcription to the target language
+    translation_pipeline = pipeline('translation', model='facebook/m2m100_418M')
+    translated_subtitles = translation_pipeline(transcription, forced_bos_token_id=translation_pipeline.tokenizer.get_lang_id(target_language))[0]["translation_text"]
+
+    # Return subtitles (text for now)
+    subtitles = f"Original: {transcription}\nTranslated: {translated_subtitles}"
+    return subtitles
+
+# Define Gradio interface
+def subtitle_video(video_file, target_language):
+    video_path = video_file.name
+    return generate_subtitles(video_path, target_language)
+
+# Gradio app layout
+interface = gr.Interface(
+    fn=subtitle_video,
+    inputs=[
+        gr.Video(label="Upload Video"),
+        gr.Textbox(label="Target Language Code (e.g., 'fr' for French, 'es' for Spanish)"),
+    ],
+    outputs="text",
+    title="Automatic Video Subtitler & Translator"
+)
+
+interface.launch()