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"""
DittoTalkingHead Streaming API Server
WebSocket/SSEによるリアルタイムストリーミング実装
"""
from fastapi import FastAPI, WebSocket, WebSocketDisconnect, File, UploadFile, HTTPException
from fastapi.responses import StreamingResponse
from fastapi.middleware.cors import CORSMiddleware
import asyncio
import tempfile
import numpy as np
import base64
import json
from typing import AsyncGenerator, Optional
import cv2
import time
import logging
from pathlib import Path
import traceback
from stream_pipeline_offline import StreamSDK
# ログ設定
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
app = FastAPI(title="DittoTalkingHead Streaming API")
# CORS設定
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# SDK設定
CFG_PKL = "checkpoints/ditto_cfg/v0.4_hubert_cfg_pytorch.pkl"
DATA_ROOT = "checkpoints/ditto_pytorch"
# グローバル設定
class AppState:
def __init__(self):
self.sdk: Optional[StreamSDK] = None
self.active_connections: int = 0
self.max_connections: int = 5
state = AppState()
def init_sdk():
"""SDKの初期化"""
if state.sdk is None:
logger.info("Initializing StreamSDK...")
state.sdk = StreamSDK(CFG_PKL, DATA_ROOT)
logger.info("StreamSDK initialized successfully")
return state.sdk
@app.on_event("startup")
async def startup_event():
"""起動時にSDKを初期化"""
init_sdk()
@app.get("/")
async def root():
"""ヘルスチェック"""
return {
"status": "ok",
"service": "DittoTalkingHead Streaming API",
"active_connections": state.active_connections,
"max_connections": state.max_connections
}
@app.websocket("/ws/generate")
async def websocket_endpoint(websocket: WebSocket):
"""WebSocketエンドポイント - リアルタイムストリーミング"""
# 接続数チェック
if state.active_connections >= state.max_connections:
await websocket.close(code=1008, reason="Server busy")
return
await websocket.accept()
state.active_connections += 1
logger.info(f"New WebSocket connection. Active: {state.active_connections}")
sdk_instance = None
output_path = None
try:
# 初期設定を受信
config = await websocket.receive_json()
source_image_b64 = config.get("source_image")
sample_rate = config.get("sample_rate", 16000)
chunk_duration = config.get("chunk_duration", 0.2)
if not source_image_b64:
await websocket.send_json({"type": "error", "message": "source_image is required"})
return
# 画像をデコードして一時ファイルに保存
image_data = base64.b64decode(source_image_b64)
with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp_img:
tmp_img.write(image_data)
source_path = tmp_img.name
# 出力ファイルの準備
output_path = tempfile.mktemp(suffix=".mp4")
# SDK設定
sdk_instance = init_sdk()
sdk_instance.setup(source_path, output_path, online_mode=True, max_size=1024)
await websocket.send_json({
"type": "ready",
"message": "Ready to receive audio chunks",
"chunk_size": int(sample_rate * chunk_duration)
})
# フレーム送信タスク
async def send_frames():
frame_count = 0
last_frame_time = time.time()
while True:
try:
current_time = time.time()
if sdk_instance.writer_queue.qsize() > 0:
frame = sdk_instance.writer_queue.get_nowait()
if frame is not None:
# フレームをJPEGエンコード(品質調整可能)
encode_param = [int(cv2.IMWRITE_JPEG_QUALITY), 80]
_, jpeg = cv2.imencode('.jpg',
cv2.cvtColor(frame, cv2.COLOR_RGB2BGR),
encode_param)
frame_b64 = base64.b64encode(jpeg).decode('utf-8')
# FPS計算
fps = 1.0 / (current_time - last_frame_time) if current_time > last_frame_time else 0
last_frame_time = current_time
await websocket.send_json({
"type": "frame",
"frame_id": frame_count,
"timestamp": current_time,
"fps": round(fps, 2),
"data": frame_b64
})
frame_count += 1
except asyncio.CancelledError:
break
except Exception as e:
logger.error(f"Error sending frame: {e}")
await asyncio.sleep(0.01) # 10ms間隔でチェック
# フレーム送信タスクを開始
frame_task = asyncio.create_task(send_frames())
# 音声チャンクを受信して処理
total_samples = 0
chunk_size = int(sample_rate * chunk_duration)
processing_start = time.time()
while True:
message = await websocket.receive()
if "bytes" in message:
# 音声データを受信
audio_bytes = message["bytes"]
audio_chunk = np.frombuffer(audio_bytes, dtype=np.float32)
# パディング
if len(audio_chunk) < chunk_size:
audio_chunk = np.pad(audio_chunk, (0, chunk_size - len(audio_chunk)))
# SDKに送信
sdk_instance.run_chunk(audio_chunk[:chunk_size])
total_samples += len(audio_chunk)
# 進捗情報を送信
elapsed = time.time() - processing_start
await websocket.send_json({
"type": "progress",
"samples_processed": total_samples,
"duration_seconds": total_samples / sample_rate,
"elapsed_seconds": elapsed
})
elif "text" in message:
# コマンドを受信
command = json.loads(message["text"])
if command.get("action") == "stop":
logger.info("Received stop command")
break
# 処理終了
frame_task.cancel()
try:
await frame_task
except asyncio.CancelledError:
pass
# フレーム数を推定してsetup_Nd
estimated_frames = int(total_samples / sample_rate * 20)
sdk_instance.setup_Nd(estimated_frames)
# 残りのフレームを処理
await websocket.send_json({"type": "processing", "message": "Finalizing video..."})
# SDKを閉じて最終MP4を生成
sdk_instance.close()
# 最終的なMP4を送信
if Path(output_path).exists():
with open(output_path, "rb") as f:
mp4_data = f.read()
mp4_b64 = base64.b64encode(mp4_data).decode('utf-8')
await websocket.send_json({
"type": "final_video",
"size_bytes": len(mp4_data),
"duration_seconds": total_samples / sample_rate,
"data": mp4_b64
})
else:
await websocket.send_json({
"type": "error",
"message": "Failed to generate final video"
})
except WebSocketDisconnect:
logger.info("Client disconnected")
except Exception as e:
logger.error(f"WebSocket error: {e}")
logger.error(traceback.format_exc())
try:
await websocket.send_json({
"type": "error",
"message": str(e)
})
except:
pass
finally:
state.active_connections -= 1
logger.info(f"Connection closed. Active: {state.active_connections}")
# クリーンアップ
if output_path and Path(output_path).exists():
try:
Path(output_path).unlink()
except:
pass
@app.post("/sse/generate")
async def sse_generate(
source_image: UploadFile = File(...),
sample_rate: int = 16000,
max_duration: float = 10.0
):
"""SSEエンドポイント - Server-Sent Eventsによるストリーミング"""
if state.active_connections >= state.max_connections:
raise HTTPException(status_code=503, detail="Server busy")
state.active_connections += 1
async def generate() -> AsyncGenerator[str, None]:
sdk_instance = None
output_path = None
try:
# 画像を保存
with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp_img:
content = await source_image.read()
tmp_img.write(content)
source_path = tmp_img.name
output_path = tempfile.mktemp(suffix=".mp4")
# SDK設定
sdk_instance = init_sdk()
sdk_instance.setup(source_path, output_path, online_mode=True, max_size=1024)
# イベント送信
yield f"data: {json.dumps({'type': 'start', 'message': 'Processing started'})}\n\n"
# デモ用:ダミー音声を生成して処理
chunk_duration = 0.2
chunk_size = int(sample_rate * chunk_duration)
num_chunks = int(max_duration / chunk_duration)
for i in range(num_chunks):
# ダミー音声チャンク(実際の実装では音声ストリームから取得)
audio_chunk = np.random.randn(chunk_size).astype(np.float32) * 0.1
sdk_instance.run_chunk(audio_chunk)
# フレームチェック
if sdk_instance.writer_queue.qsize() > 0:
try:
frame = sdk_instance.writer_queue.get_nowait()
if frame is not None:
# サムネイル生成(低解像度)
thumbnail = cv2.resize(frame, (160, 160))
_, jpeg = cv2.imencode('.jpg', cv2.cvtColor(thumbnail, cv2.COLOR_RGB2BGR))
frame_b64 = base64.b64encode(jpeg).decode('utf-8')
yield f"data: {json.dumps({'type': 'thumbnail', 'frame_id': i, 'data': frame_b64})}\n\n"
except:
pass
await asyncio.sleep(chunk_duration)
# 完了
estimated_frames = num_chunks * 5 # 概算
sdk_instance.setup_Nd(estimated_frames)
sdk_instance.close()
yield f"data: {json.dumps({'type': 'complete', 'frames': estimated_frames})}\n\n"
except Exception as e:
logger.error(f"SSE error: {e}")
yield f"data: {json.dumps({'type': 'error', 'message': str(e)})}\n\n"
finally:
state.active_connections -= 1
if output_path and Path(output_path).exists():
try:
Path(output_path).unlink()
except:
pass
return StreamingResponse(
generate(),
media_type="text/event-stream",
headers={
"Cache-Control": "no-cache",
"Connection": "keep-alive",
}
)
@app.get("/test")
async def test_page():
"""テスト用HTMLページ"""
html_content = """
<!DOCTYPE html>
<html>
<head>
<title>DittoTalkingHead Streaming Test</title>
<style>
body { font-family: Arial, sans-serif; margin: 20px; }
.container { max-width: 800px; margin: 0 auto; }
#live-frame { max-width: 100%; border: 1px solid #ccc; }
#status { margin: 10px 0; padding: 10px; background: #f0f0f0; }
.controls { margin: 20px 0; }
button { padding: 10px 20px; margin: 5px; }
</style>
</head>
<body>
<div class="container">
<h1>DittoTalkingHead Streaming Test</h1>
<div class="controls">
<input type="file" id="source-image" accept="image/*">
<button id="start-btn">Start Streaming</button>
<button id="stop-btn" disabled>Stop</button>
</div>
<div id="status">Ready</div>
<img id="live-frame" style="display: none;">
<video id="final-video" controls style="display: none; width: 100%;"></video>
</div>
<script>
// WebSocket実装はstreaming_api_guide.mdを参照
console.log('WebSocket endpoint: ws://localhost:8000/ws/generate');
</script>
</body>
</html>
"""
from fastapi.responses import HTMLResponse
return HTMLResponse(content=html_content)
if __name__ == "__main__":
import uvicorn
import torch
# GPU設定
if torch.cuda.is_available():
torch.cuda.empty_cache()
torch.backends.cudnn.benchmark = True
logger.info("Starting DittoTalkingHead Streaming API Server...")
logger.info(f"GPU available: {torch.cuda.is_available()}")
uvicorn.run(
app,
host="0.0.0.0",
port=8000,
log_level="info",
access_log=True
) |