-
Notifications
You must be signed in to change notification settings - Fork 605
/
app.py
542 lines (461 loc) · 23.1 KB
/
app.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
###############################################################################
# Copyright (C) 2024 LiveTalking@lipku https://github.com/lipku/LiveTalking
# email: [email protected]
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
# server.py
from flask import Flask, render_template,send_from_directory,request, jsonify
from flask_sockets import Sockets
import base64
import time
import json
#import gevent
#from gevent import pywsgi
#from geventwebsocket.handler import WebSocketHandler
import os
import re
import numpy as np
from threading import Thread,Event
#import multiprocessing
import torch.multiprocessing as mp
from aiohttp import web
import aiohttp
import aiohttp_cors
from aiortc import RTCPeerConnection, RTCSessionDescription
from aiortc.rtcrtpsender import RTCRtpSender
from webrtc import HumanPlayer
import argparse
import random
import shutil
import asyncio
import torch
app = Flask(__name__)
#sockets = Sockets(app)
nerfreals = {}
opt = None
model = None
avatar = None
# def llm_response(message):
# from llm.LLM import LLM
# # llm = LLM().init_model('Gemini', model_path= 'gemini-pro',api_key='Your API Key', proxy_url=None)
# # llm = LLM().init_model('ChatGPT', model_path= 'gpt-3.5-turbo',api_key='Your API Key')
# llm = LLM().init_model('VllmGPT', model_path= 'THUDM/chatglm3-6b')
# response = llm.chat(message)
# print(response)
# return response
def llm_response(message,nerfreal):
start = time.perf_counter()
from openai import OpenAI
client = OpenAI(
# 如果您没有配置环境变量,请在此处用您的API Key进行替换
api_key=os.getenv("DASHSCOPE_API_KEY"),
# 填写DashScope SDK的base_url
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
end = time.perf_counter()
print(f"llm Time init: {end-start}s")
completion = client.chat.completions.create(
model="qwen-plus",
messages=[{'role': 'system', 'content': 'You are a helpful assistant.'},
{'role': 'user', 'content': message}],
stream=True,
# 通过以下设置,在流式输出的最后一行展示token使用信息
stream_options={"include_usage": True}
)
result=""
first = True
for chunk in completion:
if len(chunk.choices)>0:
#print(chunk.choices[0].delta.content)
if first:
end = time.perf_counter()
print(f"llm Time to first chunk: {end-start}s")
first = False
msg = chunk.choices[0].delta.content
lastpos=0
#msglist = re.split('[,.!;:,。!?]',msg)
for i, char in enumerate(msg):
if char in ",.!;:,。!?:;" :
result = result+msg[lastpos:i+1]
lastpos = i+1
if len(result)>10:
print(result)
nerfreal.put_msg_txt(result)
result=""
result = result+msg[lastpos:]
end = time.perf_counter()
print(f"llm Time to last chunk: {end-start}s")
nerfreal.put_msg_txt(result)
#####webrtc###############################
pcs = set()
def randN(N):
'''生成长度为 N的随机数 '''
min = pow(10, N - 1)
max = pow(10, N)
return random.randint(min, max - 1)
def build_nerfreal(sessionid):
opt.sessionid=sessionid
if opt.model == 'wav2lip':
from lipreal import LipReal
nerfreal = LipReal(opt,model,avatar)
elif opt.model == 'musetalk':
from musereal import MuseReal
nerfreal = MuseReal(opt,model,avatar)
elif opt.model == 'ernerf':
from nerfreal import NeRFReal
nerfreal = NeRFReal(opt,model,avatar)
return nerfreal
#@app.route('/offer', methods=['POST'])
async def offer(request):
params = await request.json()
offer = RTCSessionDescription(sdp=params["sdp"], type=params["type"])
if len(nerfreals) >= opt.max_session:
print('reach max session')
return -1
sessionid = randN(6) #len(nerfreals)
print('sessionid=',sessionid)
nerfreals[sessionid] = None
nerfreal = await asyncio.get_event_loop().run_in_executor(None, build_nerfreal,sessionid)
nerfreals[sessionid] = nerfreal
pc = RTCPeerConnection()
pcs.add(pc)
@pc.on("connectionstatechange")
async def on_connectionstatechange():
print("Connection state is %s" % pc.connectionState)
if pc.connectionState == "failed":
await pc.close()
pcs.discard(pc)
del nerfreals[sessionid]
if pc.connectionState == "closed":
pcs.discard(pc)
del nerfreals[sessionid]
player = HumanPlayer(nerfreals[sessionid])
audio_sender = pc.addTrack(player.audio)
video_sender = pc.addTrack(player.video)
capabilities = RTCRtpSender.getCapabilities("video")
preferences = list(filter(lambda x: x.name == "H264", capabilities.codecs))
preferences += list(filter(lambda x: x.name == "VP8", capabilities.codecs))
preferences += list(filter(lambda x: x.name == "rtx", capabilities.codecs))
transceiver = pc.getTransceivers()[1]
transceiver.setCodecPreferences(preferences)
await pc.setRemoteDescription(offer)
answer = await pc.createAnswer()
await pc.setLocalDescription(answer)
#return jsonify({"sdp": pc.localDescription.sdp, "type": pc.localDescription.type})
return web.Response(
content_type="application/json",
text=json.dumps(
{"sdp": pc.localDescription.sdp, "type": pc.localDescription.type, "sessionid":sessionid}
),
)
async def human(request):
params = await request.json()
sessionid = params.get('sessionid',0)
if params.get('interrupt'):
nerfreals[sessionid].flush_talk()
if params['type']=='echo':
nerfreals[sessionid].put_msg_txt(params['text'])
elif params['type']=='chat':
res=await asyncio.get_event_loop().run_in_executor(None, llm_response, params['text'],nerfreals[sessionid])
#nerfreals[sessionid].put_msg_txt(res)
return web.Response(
content_type="application/json",
text=json.dumps(
{"code": 0, "data":"ok"}
),
)
async def humanaudio(request):
try:
form= await request.post()
sessionid = int(form.get('sessionid',0))
fileobj = form["file"]
filename=fileobj.filename
filebytes=fileobj.file.read()
nerfreals[sessionid].put_audio_file(filebytes)
return web.Response(
content_type="application/json",
text=json.dumps(
{"code": 0, "msg":"ok"}
),
)
except Exception as e:
return web.Response(
content_type="application/json",
text=json.dumps(
{"code": -1, "msg":"err","data": ""+e.args[0]+""}
),
)
async def set_audiotype(request):
params = await request.json()
sessionid = params.get('sessionid',0)
nerfreals[sessionid].set_curr_state(params['audiotype'],params['reinit'])
return web.Response(
content_type="application/json",
text=json.dumps(
{"code": 0, "data":"ok"}
),
)
async def record(request):
params = await request.json()
sessionid = params.get('sessionid',0)
if params['type']=='start_record':
# nerfreals[sessionid].put_msg_txt(params['text'])
nerfreals[sessionid].start_recording()
elif params['type']=='end_record':
nerfreals[sessionid].stop_recording()
return web.Response(
content_type="application/json",
text=json.dumps(
{"code": 0, "data":"ok"}
),
)
async def is_speaking(request):
params = await request.json()
sessionid = params.get('sessionid',0)
return web.Response(
content_type="application/json",
text=json.dumps(
{"code": 0, "data": nerfreals[sessionid].is_speaking()}
),
)
async def on_shutdown(app):
# close peer connections
coros = [pc.close() for pc in pcs]
await asyncio.gather(*coros)
pcs.clear()
async def post(url,data):
try:
async with aiohttp.ClientSession() as session:
async with session.post(url,data=data) as response:
return await response.text()
except aiohttp.ClientError as e:
print(f'Error: {e}')
async def run(push_url,sessionid):
nerfreal = await asyncio.get_event_loop().run_in_executor(None, build_nerfreal,sessionid)
nerfreals[sessionid] = nerfreal
pc = RTCPeerConnection()
pcs.add(pc)
@pc.on("connectionstatechange")
async def on_connectionstatechange():
print("Connection state is %s" % pc.connectionState)
if pc.connectionState == "failed":
await pc.close()
pcs.discard(pc)
player = HumanPlayer(nerfreals[sessionid])
audio_sender = pc.addTrack(player.audio)
video_sender = pc.addTrack(player.video)
await pc.setLocalDescription(await pc.createOffer())
answer = await post(push_url,pc.localDescription.sdp)
await pc.setRemoteDescription(RTCSessionDescription(sdp=answer,type='answer'))
##########################################
# os.environ['MKL_SERVICE_FORCE_INTEL'] = '1'
# os.environ['MULTIPROCESSING_METHOD'] = 'forkserver'
if __name__ == '__main__':
mp.set_start_method('spawn')
parser = argparse.ArgumentParser()
parser.add_argument('--pose', type=str, default="data/data_kf.json", help="transforms.json, pose source")
parser.add_argument('--au', type=str, default="data/au.csv", help="eye blink area")
parser.add_argument('--torso_imgs', type=str, default="", help="torso images path")
parser.add_argument('-O', action='store_true', help="equals --fp16 --cuda_ray --exp_eye")
parser.add_argument('--data_range', type=int, nargs='*', default=[0, -1], help="data range to use")
parser.add_argument('--workspace', type=str, default='data/video')
parser.add_argument('--seed', type=int, default=0)
### training options
parser.add_argument('--ckpt', type=str, default='data/pretrained/ngp_kf.pth')
parser.add_argument('--num_rays', type=int, default=4096 * 16, help="num rays sampled per image for each training step")
parser.add_argument('--cuda_ray', action='store_true', help="use CUDA raymarching instead of pytorch")
parser.add_argument('--max_steps', type=int, default=16, help="max num steps sampled per ray (only valid when using --cuda_ray)")
parser.add_argument('--num_steps', type=int, default=16, help="num steps sampled per ray (only valid when NOT using --cuda_ray)")
parser.add_argument('--upsample_steps', type=int, default=0, help="num steps up-sampled per ray (only valid when NOT using --cuda_ray)")
parser.add_argument('--update_extra_interval', type=int, default=16, help="iter interval to update extra status (only valid when using --cuda_ray)")
parser.add_argument('--max_ray_batch', type=int, default=4096, help="batch size of rays at inference to avoid OOM (only valid when NOT using --cuda_ray)")
### loss set
parser.add_argument('--warmup_step', type=int, default=10000, help="warm up steps")
parser.add_argument('--amb_aud_loss', type=int, default=1, help="use ambient aud loss")
parser.add_argument('--amb_eye_loss', type=int, default=1, help="use ambient eye loss")
parser.add_argument('--unc_loss', type=int, default=1, help="use uncertainty loss")
parser.add_argument('--lambda_amb', type=float, default=1e-4, help="lambda for ambient loss")
### network backbone options
parser.add_argument('--fp16', action='store_true', help="use amp mixed precision training")
parser.add_argument('--bg_img', type=str, default='white', help="background image")
parser.add_argument('--fbg', action='store_true', help="frame-wise bg")
parser.add_argument('--exp_eye', action='store_true', help="explicitly control the eyes")
parser.add_argument('--fix_eye', type=float, default=-1, help="fixed eye area, negative to disable, set to 0-0.3 for a reasonable eye")
parser.add_argument('--smooth_eye', action='store_true', help="smooth the eye area sequence")
parser.add_argument('--torso_shrink', type=float, default=0.8, help="shrink bg coords to allow more flexibility in deform")
### dataset options
parser.add_argument('--color_space', type=str, default='srgb', help="Color space, supports (linear, srgb)")
parser.add_argument('--preload', type=int, default=0, help="0 means load data from disk on-the-fly, 1 means preload to CPU, 2 means GPU.")
# (the default value is for the fox dataset)
parser.add_argument('--bound', type=float, default=1, help="assume the scene is bounded in box[-bound, bound]^3, if > 1, will invoke adaptive ray marching.")
parser.add_argument('--scale', type=float, default=4, help="scale camera location into box[-bound, bound]^3")
parser.add_argument('--offset', type=float, nargs='*', default=[0, 0, 0], help="offset of camera location")
parser.add_argument('--dt_gamma', type=float, default=1/256, help="dt_gamma (>=0) for adaptive ray marching. set to 0 to disable, >0 to accelerate rendering (but usually with worse quality)")
parser.add_argument('--min_near', type=float, default=0.05, help="minimum near distance for camera")
parser.add_argument('--density_thresh', type=float, default=10, help="threshold for density grid to be occupied (sigma)")
parser.add_argument('--density_thresh_torso', type=float, default=0.01, help="threshold for density grid to be occupied (alpha)")
parser.add_argument('--patch_size', type=int, default=1, help="[experimental] render patches in training, so as to apply LPIPS loss. 1 means disabled, use [64, 32, 16] to enable")
parser.add_argument('--init_lips', action='store_true', help="init lips region")
parser.add_argument('--finetune_lips', action='store_true', help="use LPIPS and landmarks to fine tune lips region")
parser.add_argument('--smooth_lips', action='store_true', help="smooth the enc_a in a exponential decay way...")
parser.add_argument('--torso', action='store_true', help="fix head and train torso")
parser.add_argument('--head_ckpt', type=str, default='', help="head model")
### GUI options
parser.add_argument('--gui', action='store_true', help="start a GUI")
parser.add_argument('--W', type=int, default=450, help="GUI width")
parser.add_argument('--H', type=int, default=450, help="GUI height")
parser.add_argument('--radius', type=float, default=3.35, help="default GUI camera radius from center")
parser.add_argument('--fovy', type=float, default=21.24, help="default GUI camera fovy")
parser.add_argument('--max_spp', type=int, default=1, help="GUI rendering max sample per pixel")
### else
parser.add_argument('--att', type=int, default=2, help="audio attention mode (0 = turn off, 1 = left-direction, 2 = bi-direction)")
parser.add_argument('--aud', type=str, default='', help="audio source (empty will load the default, else should be a path to a npy file)")
parser.add_argument('--emb', action='store_true', help="use audio class + embedding instead of logits")
parser.add_argument('--ind_dim', type=int, default=4, help="individual code dim, 0 to turn off")
parser.add_argument('--ind_num', type=int, default=10000, help="number of individual codes, should be larger than training dataset size")
parser.add_argument('--ind_dim_torso', type=int, default=8, help="individual code dim, 0 to turn off")
parser.add_argument('--amb_dim', type=int, default=2, help="ambient dimension")
parser.add_argument('--part', action='store_true', help="use partial training data (1/10)")
parser.add_argument('--part2', action='store_true', help="use partial training data (first 15s)")
parser.add_argument('--train_camera', action='store_true', help="optimize camera pose")
parser.add_argument('--smooth_path', action='store_true', help="brute-force smooth camera pose trajectory with a window size")
parser.add_argument('--smooth_path_window', type=int, default=7, help="smoothing window size")
# asr
parser.add_argument('--asr', action='store_true', help="load asr for real-time app")
parser.add_argument('--asr_wav', type=str, default='', help="load the wav and use as input")
parser.add_argument('--asr_play', action='store_true', help="play out the audio")
#parser.add_argument('--asr_model', type=str, default='deepspeech')
parser.add_argument('--asr_model', type=str, default='cpierse/wav2vec2-large-xlsr-53-esperanto') #
# parser.add_argument('--asr_model', type=str, default='facebook/wav2vec2-large-960h-lv60-self')
# parser.add_argument('--asr_model', type=str, default='facebook/hubert-large-ls960-ft')
parser.add_argument('--asr_save_feats', action='store_true')
# audio FPS
parser.add_argument('--fps', type=int, default=50)
# sliding window left-middle-right length (unit: 20ms)
parser.add_argument('-l', type=int, default=10)
parser.add_argument('-m', type=int, default=8)
parser.add_argument('-r', type=int, default=10)
parser.add_argument('--fullbody', action='store_true', help="fullbody human")
parser.add_argument('--fullbody_img', type=str, default='data/fullbody/img')
parser.add_argument('--fullbody_width', type=int, default=580)
parser.add_argument('--fullbody_height', type=int, default=1080)
parser.add_argument('--fullbody_offset_x', type=int, default=0)
parser.add_argument('--fullbody_offset_y', type=int, default=0)
#musetalk opt
parser.add_argument('--avatar_id', type=str, default='avator_1')
parser.add_argument('--bbox_shift', type=int, default=5)
parser.add_argument('--batch_size', type=int, default=16)
# parser.add_argument('--customvideo', action='store_true', help="custom video")
# parser.add_argument('--customvideo_img', type=str, default='data/customvideo/img')
# parser.add_argument('--customvideo_imgnum', type=int, default=1)
parser.add_argument('--customvideo_config', type=str, default='')
parser.add_argument('--tts', type=str, default='edgetts') #xtts gpt-sovits cosyvoice
parser.add_argument('--REF_FILE', type=str, default=None)
parser.add_argument('--REF_TEXT', type=str, default=None)
parser.add_argument('--TTS_SERVER', type=str, default='http://127.0.0.1:9880') # http://localhost:9000
# parser.add_argument('--CHARACTER', type=str, default='test')
# parser.add_argument('--EMOTION', type=str, default='default')
parser.add_argument('--model', type=str, default='ernerf') #musetalk wav2lip
parser.add_argument('--transport', type=str, default='rtcpush') #rtmp webrtc rtcpush
parser.add_argument('--push_url', type=str, default='http://localhost:1985/rtc/v1/whip/?app=live&stream=livestream') #rtmp://localhost/live/livestream
parser.add_argument('--max_session', type=int, default=1) #multi session count
parser.add_argument('--listenport', type=int, default=8010)
opt = parser.parse_args()
#app.config.from_object(opt)
#print(app.config)
opt.customopt = []
if opt.customvideo_config!='':
with open(opt.customvideo_config,'r') as file:
opt.customopt = json.load(file)
if opt.model == 'ernerf':
from nerfreal import NeRFReal,load_model,load_avatar
model = load_model(opt)
avatar = load_avatar(opt)
# we still need test_loader to provide audio features for testing.
# for k in range(opt.max_session):
# opt.sessionid=k
# nerfreal = NeRFReal(opt, trainer, test_loader,audio_processor,audio_model)
# nerfreals.append(nerfreal)
elif opt.model == 'musetalk':
from musereal import MuseReal,load_model,load_avatar,warm_up
print(opt)
model = load_model()
avatar = load_avatar(opt.avatar_id)
warm_up(opt.batch_size,model)
# for k in range(opt.max_session):
# opt.sessionid=k
# nerfreal = MuseReal(opt,audio_processor,vae, unet, pe,timesteps)
# nerfreals.append(nerfreal)
elif opt.model == 'wav2lip':
from lipreal import LipReal,load_model,load_avatar,warm_up
print(opt)
model = load_model("./models/wav2lip.pth")
avatar = load_avatar(opt.avatar_id)
warm_up(opt.batch_size,model,96)
# for k in range(opt.max_session):
# opt.sessionid=k
# nerfreal = LipReal(opt,model)
# nerfreals.append(nerfreal)
if opt.transport=='rtmp':
thread_quit = Event()
nerfreals[0] = build_nerfreal(0)
rendthrd = Thread(target=nerfreals[0].render,args=(thread_quit,))
rendthrd.start()
#############################################################################
appasync = web.Application()
appasync.on_shutdown.append(on_shutdown)
appasync.router.add_post("/offer", offer)
appasync.router.add_post("/human", human)
appasync.router.add_post("/humanaudio", humanaudio)
appasync.router.add_post("/set_audiotype", set_audiotype)
appasync.router.add_post("/record", record)
appasync.router.add_post("/is_speaking", is_speaking)
appasync.router.add_static('/',path='web')
# Configure default CORS settings.
cors = aiohttp_cors.setup(appasync, defaults={
"*": aiohttp_cors.ResourceOptions(
allow_credentials=True,
expose_headers="*",
allow_headers="*",
)
})
# Configure CORS on all routes.
for route in list(appasync.router.routes()):
cors.add(route)
pagename='webrtcapi.html'
if opt.transport=='rtmp':
pagename='echoapi.html'
elif opt.transport=='rtcpush':
pagename='rtcpushapi.html'
print('start http server; http://<serverip>:'+str(opt.listenport)+'/'+pagename)
def run_server(runner):
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
loop.run_until_complete(runner.setup())
site = web.TCPSite(runner, '0.0.0.0', opt.listenport)
loop.run_until_complete(site.start())
if opt.transport=='rtcpush':
for k in range(opt.max_session):
push_url = opt.push_url
if k!=0:
push_url = opt.push_url+str(k)
loop.run_until_complete(run(push_url,k))
loop.run_forever()
#Thread(target=run_server, args=(web.AppRunner(appasync),)).start()
run_server(web.AppRunner(appasync))
#app.on_shutdown.append(on_shutdown)
#app.router.add_post("/offer", offer)
# print('start websocket server')
# server = pywsgi.WSGIServer(('0.0.0.0', 8000), app, handler_class=WebSocketHandler)
# server.serve_forever()