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១. ការដំ ឡើងប ណ្ណា ល័យ (Run ក្នុង Cell ទឡើ១) !pip install -q -U google-generativeai spleeter whisper moviepy edge-tts ២. កូដម "The Beast" (Run ក្នុង Cell ទឡើ២) import os, whisper, asyncio, edge_tts, re, torch import google.generativeai as genai from spleeter.separator import Separator from moviepy.editor import VideoFileClip, AudioFileClip, CompositeAudioClip import moviepy.video.fx.all as vfx # --- ⚙️ កំណត់សោរ API របស់ ម្ចា ស់គ្រូ --- API_KEY = "AIzaSyDr5B0ZvrFwBUz69iUddF-KMHSb4IGENWA" genai.configure(api_key=API_KEY) gemini_ai = genai.GenerativeModel('gemini-1.5- flash') Video_Name = "Ai.mp4" VIDEO_PATH = f"input_video/{Video_Name}" OUTPUT_PATH = f"final_result/BM7_BEAST_V6_{Video_Name}"# --- 🧠 មុខងារវិភាគ្រភេទ និងបកបដោយ Gemini --- async def ai_process_context(text): try: prompt = ( f"Translate this Chinese drama line to natural spoken Khmer: '{text}'. " f"Also identify if the speaker is Male or Female. " f"Format: [Gender] | [Translation]" ) response = gemini_ai.generate_content(prompt) result = response.text.strip() gender = "Male" if "Male" in result else "Female" khmer_text = result.split('|')[-1].strip() khmer_text = re.sub(r'[.!?៖។]' , ' ', khmer_text) return gender, khmer_text except: return "Male", "" async def generate_beast_audio(text, start, duration, index): gender, kh_text = await ai_process_context(text) if not kh_text: return None, None # ប្ដូរសំឡេងតាមភេទស្វ័យបវត្តិ voice = "km-KH-PisethNeural" if gender == "Male" else "km-KH- SreymomNeural" tmp = f"tmp_{index}.mp3" comm = edge_tts.Communicate(kh_text, voice, rate="+15%", pitch="-1Hz") await comm.save(tmp) audio = AudioFileClip(tmp).set_start(start).volumex(6.0) if audio.duration > duration: audio = vfx.speedx(audio, factor=audio.duration/duration).set_duration(duration) return audio, tmp async def start_beast_dubbing(): # ១. បំបកសំឡេង (Spleeter) print(" Step 1: Removing Original Vocals (Spleeter)...") separator = Separator('spleeter: 2stems') separator.separate_to_file(VIDEO_PATH, "temp_beast") base = os.path.splitext(os.path.basename(VIDEO_PATH))[0] bg_music_path = f"temp_beast/ {base}/accompaniment.wav"# ២. សោ ្ដ ប់ (Whisper) print(" 🚀 Step 2: AI Listening (Whisper)...") model = whisper.load_model("medium").to("cuda" if torch.cuda.is_available() else "cpu") result = model.transcribe(VIDEO_PATH, language="zh") audio_tracks = [AudioFileClip(bg_music_path).volumex(0.3)] temp_files = [] # ៣. ផលិតសំឡេងបកប print(" 🎙️ Step 3: Dubbing with Gemini Context...") for i, s in enumerate(result['segments']): aud, path = await 🧹 generate_beast_audio(s['text'], s['start'], s['end']-s['start'], i) if aud: audio_tracks.append(aud) temp_files.append(path) # ៤. រ ួ មបញម្ចាូលវីដេអូ video = VideoFileClip(VIDEO_PATH) final_video = video.set_audio(CompositeAudioClip(audio_tracks)) final_video.write_videofile(OUTPUT_PATH, codec="libx264", audio_codec="aac") print(f" ✅ DONE! Video saved at: {OUTPUT_PATH}") # ⚠️ សប់ Google Colab តូវបប្រើ await await start_beast_dubbing()