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tmappdev
/
lipsync
Lipsync model using MuseTalk
- Public
- 2.9K runs
-
A100 (80GB)
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=tmappdev/lipsync
or set up a project from scratch
Install Replicate’s Node.js client library:
npm install replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:
import Replicate from "replicate";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});Run tmappdev/lipsync using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"tmappdev/lipsync:f21209234331014d7253fef53f5b44a5ae28a41cae14a3d67f5a872c503fe789",
{
input: {
fps: 25,
bbox_shift: 0,
audio_input: "https://storage.googleapis.com/chattuesday/audios/img_9518da8f-71c3-4576-9dd2-4e6fc78ef9f4.mp3",
video_input: "https://replicate.delivery/pbxt/LzlR1mCzrpoMUA5GPk1RzxkriLjW5YMBmyJ2ieXbjARlgEBs/lily-ldwi8a_LdG-2.mp4"
}
}
);
// To access the file URL:
console.log(output.url()); //=> "http://example.com"
// To write the file to disk:
fs.writeFile("my-image.png", output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:
pip install replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:
import replicateRun tmappdev/lipsync using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"tmappdev/lipsync:f21209234331014d7253fef53f5b44a5ae28a41cae14a3d67f5a872c503fe789",
input={
"fps": 25,
"bbox_shift": 0,
"audio_input": "https://storage.googleapis.com/chattuesday/audios/img_9518da8f-71c3-4576-9dd2-4e6fc78ef9f4.mp3",
"video_input": "https://replicate.delivery/pbxt/LzlR1mCzrpoMUA5GPk1RzxkriLjW5YMBmyJ2ieXbjARlgEBs/lily-ldwi8a_LdG-2.mp4"
}
)
print(output)To learn more, take a look at the guide on getting started with Python.
Set the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run tmappdev/lipsync using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \
-H "Authorization: Bearer $REPLICATE_API_TOKEN" \
-H "Content-Type: application/json" \
-H "Prefer: wait" \
-d $'{
"version": "f21209234331014d7253fef53f5b44a5ae28a41cae14a3d67f5a872c503fe789",
"input": {
"fps": 25,
"bbox_shift": 0,
"audio_input": "https://storage.googleapis.com/chattuesday/audios/img_9518da8f-71c3-4576-9dd2-4e6fc78ef9f4.mp3",
"video_input": "https://replicate.delivery/pbxt/LzlR1mCzrpoMUA5GPk1RzxkriLjW5YMBmyJ2ieXbjARlgEBs/lily-ldwi8a_LdG-2.mp4"
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Add a payment method to run this model.
Sign in with GitHub
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terms of service and privacy policy
Output
{
"completed_at": "2024-11-19T12:47:17.496460Z",
"created_at": "2024-11-19T12:31:41.156000Z",
"data_removed": false,
"error": null,
"id": "27zs2x9rchrj60ck8hmaz9wjsg",
"input": {
"fps": 25,
"bbox_shift": 0,
"audio_input": "https://storage.googleapis.com/chattuesday/audios/img_9518da8f-71c3-4576-9dd2-4e6fc78ef9f4.mp3",
"video_input": "https://replicate.delivery/pbxt/LzlR1mCzrpoMUA5GPk1RzxkriLjW5YMBmyJ2ieXbjARlgEBs/lily-ldwi8a_LdG-2.mp4"
},
"logs": "please download ffmpeg-static and export to FFMPEG_PATH.\nFor example: export FFMPEG_PATH=/musetalk/ffmpeg-4.4-amd64-static\n2024-11-19 12:34:06.862656: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n2024-11-19 12:34:06.906267: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\nTo enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n2024-11-19 12:34:07.686505: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\nLoads checkpoint by local backend from path: ./models/dwpose/dw-ll_ucoco_384.pth\ncuda start\nDownloading: \"https://www.adrianbulat.com/downloads/python-fan/s3fd-619a316812.pth\" to /root/.cache/torch/hub/checkpoints/s3fd-619a316812.pth\n 0%| | 0.00/85.7M [00:00<?, ?B/s]\n 0%| | 32.0k/85.7M [00:00<07:16, 206kB/s]\n 0%| | 96.0k/85.7M [00:00<04:35, 326kB/s]\n 0%| | 208k/85.7M [00:00<02:57, 505kB/s] \n 0%| | 432k/85.7M [00:00<01:42, 872kB/s]\n 1%| | 880k/85.7M [00:00<00:55, 1.59MB/s]\n 2%|▏ | 1.73M/85.7M [00:00<00:29, 3.00MB/s]\n 4%|▍ | 3.50M/85.7M [00:01<00:14, 5.81MB/s]\n 8%|▊ | 6.98M/85.7M [00:01<00:07, 11.2MB/s]\n 13%|█▎ | 10.7M/85.7M [00:01<00:05, 15.2MB/s]\n 17%|█▋ | 14.5M/85.7M [00:01<00:04, 18.1MB/s]\n 21%|██▏ | 18.3M/85.7M [00:01<00:03, 20.1MB/s]\n 26%|██▌ | 22.1M/85.7M [00:01<00:03, 21.5MB/s]\n 30%|███ | 25.9M/85.7M [00:02<00:02, 22.5MB/s]\n 35%|███▍ | 29.6M/85.7M [00:02<00:02, 23.0MB/s]\n 39%|███▉ | 33.5M/85.7M [00:02<00:02, 23.5MB/s]\n 43%|████▎ | 37.2M/85.7M [00:02<00:02, 23.7MB/s]\n 48%|████▊ | 41.0M/85.7M [00:02<00:01, 24.0MB/s]\n 52%|█████▏ | 44.8M/85.7M [00:02<00:01, 24.1MB/s]\n 57%|█████▋ | 48.5M/85.7M [00:03<00:01, 24.2MB/s]\n 61%|██████ | 52.4M/85.7M [00:03<00:01, 24.3MB/s]\n 66%|██████▌ | 56.2M/85.7M [00:03<00:01, 24.4MB/s]\n 70%|██████▉ | 59.9M/85.7M [00:03<00:01, 24.3MB/s]\n 74%|███████▍ | 63.7M/85.7M [00:03<00:00, 24.3MB/s]\n 78%|███████▊ | 67.0M/85.7M [00:03<00:00, 23.4MB/s]\n 83%|████████▎ | 70.8M/85.7M [00:04<00:00, 23.9MB/s]\n 87%|████████▋ | 74.6M/85.7M [00:04<00:00, 24.1MB/s]\n 92%|█████████▏| 78.4M/85.7M [00:04<00:00, 24.3MB/s]\n 96%|█████████▌| 82.1M/85.7M [00:04<00:00, 24.2MB/s]\n100%|██████████| 85.7M/85.7M [00:04<00:00, 19.8MB/s]\nAn error occurred while trying to fetch ./models/sd-vae-ft-mse/: Error no file named diffusion_pytorch_model.safetensors found in directory ./models/sd-vae-ft-mse/.\nDefaulting to unsafe serialization. Pass `allow_pickle=False` to raise an error instead.\n/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/torch/_utils.py:776: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\nreturn self.fget.__get__(instance, owner)()\nRUN: predict\nvideo in 25.0 FPS, audio idx in 50FPS\nextracting landmarks...time consuming\nreading images...\n 0%| | 0/118 [00:00<?, ?it/s]\n 6%|▌ | 7/118 [00:00<00:01, 63.33it/s]\n 12%|█▏ | 14/118 [00:00<00:01, 62.62it/s]\n 18%|█▊ | 21/118 [00:00<00:01, 62.17it/s]\n 24%|██▎ | 28/118 [00:00<00:01, 61.64it/s]\n 30%|██▉ | 35/118 [00:00<00:01, 60.89it/s]\n 36%|███▌ | 42/118 [00:00<00:01, 60.46it/s]\n 42%|████▏ \n[...] log volume exceeds 256KiB size limit: truncating logs [...]\n27, 6.77it/s]\n 10%|█ | 69/661 [00:20<01:27, 6.77it/s]\n 11%|█ | 70/661 [00:20<01:27, 6.76it/s]\n 11%|█ | 71/661 [00:20<01:27, 6.76it/s]\n 11%|█ | 72/661 [00:20<01:27, 6.76it/s]\n 11%|█ | 73/661 [00:20<01:26, 6.76it/s]\n 11%|█ | 74/661 [00:20<01:26, 6.76it/s]\n 11%|█▏ | 75/661 [00:21<01:26, 6.76it/s]\n 11%|█▏ | 76/661 [00:21<01:26, 6.77it/s]\n 12%|█▏ | 77/661 [00:21<01:26, 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[01:11<08:04, 9.49it/s]\n 13%|█▎ | 688/5283 [01:11<07:49, 9.79it/s]\n 13%|█▎ | 689/5283 [01:11<08:04, 9.49it/s]\n 13%|█▎ | 691/5283 [01:11<07:48, 9.80it/s]\n 13%|█▎ | 692/5283 [01:12<08:03, 9.50it/s]\n 13%|█▎ | 694/5283 [01:12<07:47, 9.81it/s]\n 13%|█▎ | 695/5283 [01:12<08:04, 9.48it/s]\n 13%|█▎ | 697/5283 [01:12<07:50, 9.75it/s]\n 13%|█▎ | 698/5283 [01:12<08:04, 9.46it/s]\n 13%|█▎ | 699/5283 [01:12<08:11, 9.33it/s]\n 13%|█▎ | 701/5283 [01:12<08:07, 9.39it/s]\n 13%|█▎ | 703/5283 [01:13<07:49, 9.76it/s]\n 13%|█▎ | 704/5283 [01:13<08:01, 9.51it/s]\n 13%|█▎ | 706/5283 [01:13<07:43, 9.87it/s]\n 13%|█▎ | 707/5283 [01:13<07:56, 9.59it/s]\n 13%|█▎ | 709/5283 [01:13<07:39, 9.95it/s]\n 13%|█▎ | 710/5283 [01:13<07:53, 9.65it/s]\n 13%|█▎ | 712/5283 [01:14<07:38, 9.98it/s]\n 13%|█▎ | 713/5283 [01:14<07:52, 9.67it/s]\n 14%|█▎ | 715/5283 [01:14<07:39, 9.94it/s]\n 14%|█▎ | 716/5283 [01:14<07:54, 9.63it/s]\n 14%|█▎ | 718/5283 [01:14<07:39, 9.94it/s]\n 14%|█▎ | 719/5283 [01:14<07:55, 9.60it/s]\n 14%|█▎ | 721/5283 [01:15<07:41, 9.89it/s]\n 14%|█▎ | 722/5283 [01:15<07:56, 9.57it/s]\n 14%|█▎ | 724/5283 [01:15<07:41, 9.88it/s]\n 14%|█▎ | 725/5283 [01:15<07:55, 9.59it/s]\n 14%|█▍ | 727/5283 [01:15<07:40, 9.89it/s]\n 14%|█▍ | 728/5283 [01:15<07:55, 9.58it/s]\n 14%|█▍ | 730/5283 [01:15<07:42, 9.85it/s]\n 14%|█▍ | 731/5283 [01:16<07:56, 9.55it/s]\n 14%|█▍ | 733/5283 [01:16<07:42, 9.84it/s]\n 14%|█▍ | 734/5283 [01:16<07:56, 9.55it/s]\n 14%|█▍ | 736/5283 [01:16<07:40, 9.88it/s]\n 14%|█▍ | 737/5283 [01:16<07:56, 9.55it/s]\n 14%|█▍ | 739/5283 [01:16<07:42, 9.82it/s]\n 14%|█▍ | 740/5283 [01:16<07:58, 9.50it/s]\n 14%|█▍ | 742/5283 [01:17<07:43, 9.81it/s]\n 14%|█▍ | 743/5283 [01:17<07:57, 9.50it/s]\n 14%|█▍ | 745/5283 [01:17<07:41, 9.82it/s]\n 14%|█▍ | 746/5283 [01:17<07:55, 9.55it/s]\n 14%|█▍ | 748/5283 [01:17<07:41, 9.82it/s]\n 14%|█▍ | 749/5283 [01:17<07:54, 9.55it/s]\n 14%|█▍ | 751/5283 [01:18<07:40, 9.85it/s]\n 14%|█▍ | 752/5283 [01:18<07:53, 9.57it/s]\n 14%|█▍ | 754/5283 [01:18<07:37, 9.89it/s]\n 14%|█▍ | 755/5283 [01:18<07:51, 9.60it/s]\n 14%|█▍ | 757/5283 [01:18<07:36, 9.92it/s]\n 14%|█▍ | 758/5283 [01:18<07:51, 9.60it/s]\n 14%|█▍ | 760/5283 [01:19<07:37, 9.89it/s]\n 14%|█▍ | 761/5283 [01:19<07:52, 9.58it/s]\n 14%|█▍ | 763/5283 [01:19<07:39, 9.83it/s]\n 14%|█▍ | 764/5283 [01:19<07:53, 9.55it/s]\n 14%|█▍ | 766/5283 [01:19<07:38, 9.86it/s]\n 15%|█▍ | 767/5283 [01:19<07:52, 9.57it/s]\n 15%|█▍ | 769/5283 [01:19<07:37, 9.87it/s]\n 15%|█▍ | 770/5283 [01:20<07:52, 9.56it/s]\n 15%|█▍ | 772/5283 [01:20<07:38, 9.84it/s]\n 15%|█▍ | 773/5283 [01:20<07:52, 9.55it/s]\n 15%|█▍ | 775/5283 [01:20<07:36, 9.87it/s]\n 15%|█▍ | 776/5283 [01:20<07:50, 9.57it/s]\n 15%|█▍ | 778/5283 [01:20<07:36, 9.86it/s]\n 15%|█▍ | 779/5283 [01:21<07:51, 9.55it/s]\n 15%|█▍ | 781/5283 [01:21<07:36, 9.86it/s]\n 15%|█▍ | 782/5283 [01:21<07:50, 9.56it/s]\n 15%|█▍ | 784/5283 [01:21<07:35, 9.87it/s]\n 15%|█▍ | 785/5283 [01:21<07:49, 9.58it/s]\n 15%|█▍ | 787/5283 [01:21<07:35, 9.87it/s]\n 15%|█▍ | 788/5283 [01:21<07:51, 9.53it/s]\n 15%|█▍ | 790/5283 [01:22<07:37, 9.82it/s]\n 15%|█▍ | 791/5283 [01:22<07:56, 9.43it/s]\n 15%|█▌ | 793/5283 [01:22<07:45, 9.64it/s]\n 15%|█▌ | 794/5283 [01:22<07:59, 9.37it/s]\n 15%|█▌ | 796/5283 [01:22<07:42, 9.69it/s]\n 15%|█▌ | 797/5283 [01:22<07:56, 9.42it/s]\n 15%|█▌ | 799/5283 [01:23<07:38, 9.77it/s]\n 15%|█▌ | 800/5283 [01:23<07:53, 9.47it/s]\n 15%|█▌ | 802/5283 [01:23<07:38, 9.78it/s]\n 15%|█▌ | 803/5283 [01:23<07:52, 9.49it/s]\n 15%|█▌ | 805/5283 [01:23<07:36, 9.82it/s]\n 15%|█▌ | 806/5283 [01:23<07:50, 9.52it/s]\n 15%|█▌ | 808/5283 [01:24<07:39, 9.73it/s]\n 15%|█▌ | 809/5283 [01:24<07:57, 9.37it/s]\n 15%|█▌ | 811/5283 [01:24<07:42, 9.68it/s]\n 15%|█▌ | 812/5283 [01:24<07:57, 9.37it/s]\n 15%|█▌ | 814/5283 [01:24<07:39, 9.72it/s]\n 15%|█▌ | 815/5283 [01:24<07:50, 9.49it/s]\n 15%|█▌ | 817/5283 [01:24<07:36, 9.79it/s]\n 15%|█▌ | 818/5283 [01:25<07:47, 9.55it/s]\n 16%|█▌ | 820/5283 [01:25<07:33, 9.83it/s]\n 16%|█▌ | 821/5283 [01:25<07:47, 9.54it/s]\n 16%|█▌ | 823/5283 [01:25<07:32, 9.86it/s]\n 16%|█▌ | 824/5283 [01:25<07:46, 9.56it/s]\n 16%|█▌ | 826/5283 [01:25<07:34, 9.81it/s]\n 16%|█▌ | 827/5283 [01:25<07:49, 9.50it/s]\n 16%|█▌ | 829/5283 [01:26<07:34, 9.80it/s]\n 16%|█▌ | 830/5283 [01:26<07:48, 9.50it/s]\n 16%|█▌ | 832/5283 [01:26<07:32, 9.83it/s]\n 16%|█▌ | 833/5283 [01:26<07:46, 9.55it/s]\n 16%|█▌ | 835/5283 [01:26<07:31, 9.85it/s]\n 16%|█▌ | 836/5283 [01:26<07:45, 9.55it/s]\n 16%|█▌ | 838/5283 [01:27<07:31, 9.85it/s]\n 16%|█▌ | 839/5283 [01:27<07:45, 9.55it/s]\n 16%|█▌ | 841/5283 [01:27<07:31, 9.84it/s]\n 16%|█▌ | 842/5283 [01:27<07:45, 9.54it/s]\n 16%|█▌ | 844/5283 [01:27<07:30, 9.85it/s]\n 16%|█▌ | 845/5283 [01:27<07:45, 9.53it/s]\n 16%|█▌ | 847/5283 [01:28<07:31, 9.83it/s]\n 16%|█▌ | 848/5283 [01:28<07:45, 9.53it/s]\n 16%|█▌ | 850/5283 [01:28<07:30, 9.83it/s]\n 16%|█▌ | 851/5283 [01:28<07:44, 9.55it/s]\n 16%|█▌ | 853/5283 [01:28<07:29, 9.86it/s]\n 16%|█▌ | 854/5283 [01:28<07:42, 9.57it/s]\n 16%|█▌ | 856/5283 [01:28<07:30, 9.84it/s]\n 16%|█▌ | 857/5283 [01:29<07:44, 9.54it/s]\n 16%|█▋ | 859/5283 [01:29<07:31, 9.81it/s]\n 16%|█▋ | 860/5283 [01:29<07:44, 9.51it/s]\n 16%|█▋ | 862/5283 [01:29<07:31, 9.80it/s]\n 16%|█▋ | 863/5283 [01:29<07:44, 9.51it/s]\n 16%|█▋ | 865/5283 [01:29<07:31, 9.79it/s]\n 16%|█▋ | 866/5283 [01:30<07:45, 9.48it/s]\n 16%|█▋ | 868/5283 [01:30<07:31, 9.78it/s]\n 16%|█▋ | 869/5283 [01:30<07:45, 9.49it/s]\n 16%|█▋ | 871/5283 [01:30<07:29, 9.82it/s]\n 17%|█▋ | 872/5283 [01:30<07:42, 9.54it/s]\n 17%|█▋ | 874/5283 [01:30<07:27, 9.84it/s]\n 17%|█▋ | 875/5283 [01:30<07:42, 9.53it/s]\n 17%|█▋ | 877/5283 [01:31<07:29, 9.81it/s]\n 17%|█▋ | 878/5283 [01:31<07:43, 9.51it/s]\n 17%|█▋ | 880/5283 [01:31<07:28, 9.81it/s]\n 17%|█▋ | 881/5283 [01:31<07:43, 9.49it/s]\n 17%|█▋ | 883/5283 [01:31<07:27, 9.82it/s]\n 17%|█▋ | 884/5283 [01:31<07:41, 9.53it/s]\n 17%|█▋ | 886/5283 [01:32<07:26, 9.85it/s]\n 17%|█▋ | 887/5283 [01:32<07:40, 9.54it/s]\n 17%|█▋ | 889/5283 [01:32<07:27, 9.82it/s]\n 17%|█▋ | 890/5283 [01:32<07:41, 9.51it/s]\n 17%|█▋ | 892/5283 [01:32<07:26, 9.84it/s]\n 17%|█▋ | 893/5283 [01:32<07:39, 9.55it/s]\n 17%|█▋ | 895/5283 [01:32<07:25, 9.84it/s]\n 17%|█▋ | 896/5283 [01:33<07:39, 9.55it/s]\n 17%|█▋ | 898/5283 [01:33<07:25, 9.84it/s]\n 17%|█▋ | 899/5283 [01:33<07:38, 9.56it/s]\n 17%|█▋ | 901/5283 [01:33<07:24, 9.87it/s]\n 17%|█▋ | 902/5283 [01:33<07:40, 9.52it/s]\n 17%|█▋ | 904/5283 [01:33<07:26, 9.81it/s]\n 17%|█▋ | 905/5283 [01:34<07:39, 9.52it/s]\n 17%|█▋ | 907/5283 [01:34<07:25, 9.82it/s]\n 17%|█▋ | 908/5283 [01:34<07:39, 9.53it/s]\n 17%|█▋ | 910/5283 [01:34<07:25, 9.82it/s]\n 17%|█▋ | 911/5283 [01:34<07:38, 9.54it/s]\n 17%|█▋ | 913/5283 [01:34<07:23, 9.85it/s]\n 17%|█▋ | 914/5283 [01:34<07:37, 9.56it/s]\n 17%|█▋ | 916/5283 [01:35<07:22, 9.87it/s]\n 17%|█▋ | 917/5283 [01:35<07:36, 9.56it/s]\n 17%|█▋ | 919/5283 [01:35<07:21, 9.88it/s]\n 17%|█▋ | 920/5283 [01:35<07:35, 9.59it/s]\n 17%|█▋ | 922/5283 [01:35<07:20, 9.91it/s]\n 17%|█▋ | 923/5283 [01:35<07:34, 9.60it/s]\n 18%|█▊ | 925/5283 [01:36<07:21, 9.88it/s]\n 18%|█▊ | 926/5283 [01:36<07:35, 9.57it/s]\n 18%|█▊ | 927/5283 [01:36<07:31, 9.65it/s]\n 18%|█▊ | 929/5283 [01:36<07:33, 9.60it/s]\n 18%|█▊ | 931/5283 [01:36<07:20, 9.88it/s]\n 18%|█▊ | 932/5283 [01:36<07:35, 9.56it/s]\n 18%|█▊ | 934/5283 [01:37<07:21, 9.85it/s]\n 18%|█▊ | 935/5283 [01:37<07:35, 9.54it/s]\n 18%|█▊ | 937/5283 [01:37<07:20, 9.86it/s]\n 18%|█▊ | 938/5283 [01:37<07:32, 9.59it/s]\n 18%|█▊ | 940/5283 [01:37<07:17, 9.92it/s]\n 18%|█▊ | 941/5283 [01:37<07:30, 9.64it/s]\n 18%|█▊ | 943/5283 [01:37<07:16, 9.93it/s]\n 18%|█▊ | 944/5283 [01:38<07:29, 9.66it/s]\n 18%|█▊ | 946/5283 [01:38<07:16, 9.93it/s]\n 18%|█▊ | 947/5283 [01:38<07:32, 9.57it/s]\n 18%|█▊ | 949/5283 [01:38<07:19, 9.87it/s]\n 18%|█▊ | 950/5283 [01:38<07:32, 9.58it/s]\n 18%|█▊ | 952/5283 [01:38<07:20, 9.84it/s]\n 18%|█▊ | 953/5283 [01:38<07:33, 9.55it/s]\n 18%|█▊ | 955/5283 [01:39<07:18, 9.86it/s]\n 18%|█▊ | 956/5283 [01:39<07:33, 9.55it/s]\n 18%|█▊ | 958/5283 [01:39<07:18, 9.86it/s]\n 18%|█▊ | 959/5283 [01:39<07:33, 9.54it/s]\n 18%|█▊ | 961/5283 [01:39<07:18, 9.85it/s]\n 18%|█▊ | 962/5283 [01:39<07:32, 9.56it/s]\n 18%|█▊ | 964/5283 [01:40<07:18, 9.85it/s]\n 18%|█▊ | 965/5283 [01:40<07:32, 9.55it/s]\n 18%|█▊ | 967/5283 [01:40<07:18, 9.85it/s]\n 18%|█▊ | 968/5283 [01:40<07:31, 9.56it/s]\n 18%|█▊ | 970/5283 [01:40<07:17, 9.87it/s]\n 18%|█▊ | 971/5283 [01:40<07:30, 9.57it/s]\n 18%|█▊ | 973/5283 [01:41<07:16, 9.87it/s]\n 18%|█▊ | 974/5283 [01:41<07:30, 9.57it/s]\n 18%|█▊ | 976/5283 [01:41<07:16, 9.86it/s]\n 18%|█▊ | 977/5283 [01:41<07:29, 9.59it/s]\n 19%|█▊ | 979/5283 [01:41<07:17, 9.84it/s]\n 19%|█▊ | 980/5283 [01:41<07:30, 9.54it/s]\n 19%|█▊ | 982/5283 [01:41<07:17, 9.84it/s]\n 19%|█▊ | 983/5283 [01:42<07:30, 9.54it/s]\n 19%|█▊ | 985/5283 [01:42<07:17, 9.82it/s]\n 19%|█▊ | 986/5283 [01:42<07:31, 9.52it/s]\n 19%|█▊ | 988/5283 [01:42<07:16, 9.83it/s]\n 19%|█▊ | 989/5283 [01:42<07:30, 9.54it/s]\n 19%|█▉ | 991/5283 [01:42<07:16, 9.83it/s]\n 19%|█▉ | 992/5283 [01:42<07:30, 9.53it/s]\n 19%|█▉ | 994/5283 [01:43<07:16, 9.83it/s]\n 19%|█▉ | 995/5283 [01:43<07:30, 9.53it/s]\n 19%|█▉ | 997/5283 [01:43<07:15, 9.85it/s]\n 19%|█▉ | 998/5283 [01:43<07:27, 9.57it/s]\n 19%|█▉ | 1000/5283 [01:43<07:14, 9.86it/s]\n 19%|█▉ | 1001/5283 [01:43<07:27, 9.56it/s]\n 19%|█▉ | 1003/5283 [01:44<07:14, 9.86it/s]\n 19%|█▉ | 1004/5283 [01:44<07:27, 9.56it/s]\n 19%|█▉ | 1006/5283 [01:44<07:13, 9.88it/s]\n 19%|█▉ | 1007/5283 [01:44<07:26, 9.58it/s]\n 19%|█▉ | 1009/5283 [01:44<07:12, 9.88it/s]\n 19%|█▉ | 1010/5283 [01:44<07:29, 9.50it/s]\n 19%|█▉ | 1012/5283 [01:45<07:14, 9.83it/s]\n 19%|█▉ | 1013/5283 [01:45<07:28, 9.53it/s]\n 19%|█▉ | 1015/5283 [01:45<07:14, 9.82it/s]\n 19%|█▉ | 1016/5283 [01:45<07:27, 9.53it/s]\n 19%|█▉ | 1018/5283 [01:45<07:13, 9.83it/s]\n 19%|█▉ | 1019/5283 [01:45<07:27, 9.52it/s]\n 19%|█▉ | 1021/5283 [01:45<07:14, 9.80it/s]\n 19%|█▉ | 1022/5283 [01:46<07:27, 9.51it/s]\n 19%|█▉ | 1024/5283 [01:46<07:13, 9.82it/s]\n 19%|█▉ | 1025/5283 [01:46<07:26, 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[09:04<00:01, 9.55it/s]\n100%|█████████▉| 5266/5283 [09:05<00:01, 9.86it/s]\n100%|█████████▉| 5267/5283 [09:05<00:01, 9.56it/s]\n100%|█████████▉| 5268/5283 [09:05<00:01, 9.65it/s]\n100%|█████████▉| 5270/5283 [09:05<00:01, 9.57it/s]\n100%|█████████▉| 5272/5283 [09:05<00:01, 9.85it/s]\n100%|█████████▉| 5273/5283 [09:05<00:01, 9.54it/s]\n100%|█████████▉| 5275/5283 [09:05<00:00, 9.83it/s]\n100%|█████████▉| 5276/5283 [09:06<00:00, 9.54it/s]\n100%|█████████▉| 5278/5283 [09:06<00:00, 9.83it/s]\n100%|█████████▉| 5279/5283 [09:06<00:00, 9.53it/s]\n100%|█████████▉| 5281/5283 [09:06<00:00, 9.84it/s]\n100%|█████████▉| 5282/5283 [09:06<00:00, 9.55it/s]\n100%|██████████| 5283/5283 [09:06<00:00, 9.66it/s]\nffmpeg -y -v warning -r 25.0 -f image2 -i /src/results/tmpgwijzrc3lily-ldwi8a_LdG-2_tmp5w74vyssimg_9518da8f-71c3-4576-9dd2-4e6fc78ef9f4/%08d.png -vcodec libx264 -vf format=rgb24,scale=out_color_matrix=bt709,format=yuv420p -crf 18 temp.mp4\nffmpeg -y -v warning -i /tmp/tmp5w74vyssimg_9518da8f-71c3-4576-9dd2-4e6fc78ef9f4.mp3 -i temp.mp4 /src/results/tmpgwijzrc3lily-ldwi8a_LdG-2_tmp5w74vyssimg_9518da8f-71c3-4576-9dd2-4e6fc78ef9f4.mp4\n[mp3 @ 0x5fe7126b8540] Estimating duration from bitrate, this may be inaccurate\nresult is save to /src/results/tmpgwijzrc3lily-ldwi8a_LdG-2_tmp5w74vyssimg_9518da8f-71c3-4576-9dd2-4e6fc78ef9f4.mp4",
"metrics": {
"predict_time": 793.188920833,
"total_time": 936.34046
},
"output": "https://replicate.delivery/yhqm/5QL3bYQH9y7qMJSy4mIdaeB1e79t4zRNkVGasldAVgerWHlnA/tmpgwijzrc3lily-ldwi8a_LdG-2_tmp5w74vyssimg_9518da8f-71c3-4576-9dd2-4e6fc78ef9f4.mp4",
"started_at": "2024-11-19T12:34:04.307539Z",
"status": "succeeded",
"urls": {
"stream": "https://stream.replicate.com/v1/files/qoxq-aawczj5fpaz2vhyh4mlkfrmiyub5ztjopv5mppxdcm6t6pf2dv2q",
"get": "https://api.replicate.com/v1/predictions/27zs2x9rchrj60ck8hmaz9wjsg",
"cancel": "https://api.replicate.com/v1/predictions/27zs2x9rchrj60ck8hmaz9wjsg/cancel"
},
"version": "b7e775591e83379c7c99a3dea151002e92fcd6093609b05200df5fa04d53f1c1"
}Generated in
please download ffmpeg-static and export to FFMPEG_PATH.
For example: export FFMPEG_PATH=/musetalk/ffmpeg-4.4-amd64-static
2024-11-19 12:34:06.862656: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2024-11-19 12:34:06.906267: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-11-19 12:34:07.686505: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
Loads checkpoint by local backend from path: ./models/dwpose/dw-ll_ucoco_384.pth
cuda start
Downloading: "https://www.adrianbulat.com/downloads/python-fan/s3fd-619a316812.pth" to /root/.cache/torch/hub/checkpoints/s3fd-619a316812.pth
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An error occurred while trying to fetch ./models/sd-vae-ft-mse/: Error no file named diffusion_pytorch_model.safetensors found in directory ./models/sd-vae-ft-mse/.
Defaulting to unsafe serialization. Pass `allow_pickle=False` to raise an error instead.
/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/torch/_utils.py:776: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()
return self.fget.__get__(instance, owner)()
RUN: predict
video in 25.0 FPS, audio idx in 50FPS
extracting landmarks...time consuming
reading images...
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[...] log volume exceeds 256KiB size limit: truncating logs [...]
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ffmpeg -y -v warning -r 25.0 -f image2 -i /src/results/tmpgwijzrc3lily-ldwi8a_LdG-2_tmp5w74vyssimg_9518da8f-71c3-4576-9dd2-4e6fc78ef9f4/%08d.png -vcodec libx264 -vf format=rgb24,scale=out_color_matrix=bt709,format=yuv420p -crf 18 temp.mp4
ffmpeg -y -v warning -i /tmp/tmp5w74vyssimg_9518da8f-71c3-4576-9dd2-4e6fc78ef9f4.mp3 -i temp.mp4 /src/results/tmpgwijzrc3lily-ldwi8a_LdG-2_tmp5w74vyssimg_9518da8f-71c3-4576-9dd2-4e6fc78ef9f4.mp4
[mp3 @ 0x5fe7126b8540] Estimating duration from bitrate, this may be inaccurate
result is save to /src/results/tmpgwijzrc3lily-ldwi8a_LdG-2_tmp5w74vyssimg_9518da8f-71c3-4576-9dd2-4e6fc78ef9f4.mp4This output was created using a different version of the model, tmappdev/lipsync:b7e77559.
Examples
Run time and cost
This model costs approximately $0.31 to run on Replicate, or 3 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.
This model runs on Nvidia A100 (80GB) GPU hardware. Predictions typically complete within 4 minutes. The predict time for this model varies significantly based on the inputs.