lucataco/diffusion-motion-transfer:6bc872d3 – Run with an API on Replicate

Version

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lucataco /diffusion-motion-transfer:6bc872d3

Playground API

Input

video

*file

Input video

video_prompt

string

Shift + Return to add a new line

Amazing quality, masterpiece, A locomotive rides in a forestAmazing quality, masterpiece, A locomotive rides in a forest

Prompt used to describe the input video

Default: "Amazing quality, masterpiece, A locomotive rides in a forest"

n_timesteps

integer

Number of times to preprocess the video

Default: 999

target_prompt

string

Shift + Return to add a new line

Amazing quality, masterpiece, A motorbike driving in a forestAmazing quality, masterpiece, A motorbike driving in a forest

Prompt used to describe the output video

Default: "Amazing quality, masterpiece, A motorbike driving in a forest"

negative_prompt

string

Shift + Return to add a new line

bad quality, distortions, unrealistic, distorted image, watermark, signaturebad quality, distortions, unrealistic, distorted image, watermark, signature

Negative prompt to use for editing

Default: "bad quality, distortions, unrealistic, distorted image, watermark, signature"

seed

integer

Random seed. Leave blank to randomize the seed

Run this model in Node.js with one line of code:

npx create-replicate --model=lucataco/diffusion-motion-transfer

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set 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 lucataco/diffusion-motion-transfer using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/diffusion-motion-transfer:6bc872d3b943a49517b30192852477de7bea271e9abb76e726704ab4d6ae6eb3",
  {
    input: {
      video: "https://replicate.delivery/pbxt/K7P4ZdV95HbR4aEof8ihr2j7UVWeFxHfoMWTG7H16gCy62Jf/demo.mp4",
      n_timesteps: 900,
      video_prompt: "Amazing quality, masterpiece, A locomotive rides in a forest",
      target_prompt: "Amazing quality, masterpiece, A motorbike driving in a forest",
      negative_prompt: "bad quality, distortions, unrealistic, distorted image, watermark, signature"
    }
  }
);

// 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 replicate

Set 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 replicate

Run lucataco/diffusion-motion-transfer using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/diffusion-motion-transfer:6bc872d3b943a49517b30192852477de7bea271e9abb76e726704ab4d6ae6eb3",
    input={
        "video": "https://replicate.delivery/pbxt/K7P4ZdV95HbR4aEof8ihr2j7UVWeFxHfoMWTG7H16gCy62Jf/demo.mp4",
        "n_timesteps": 900,
        "video_prompt": "Amazing quality, masterpiece, A locomotive rides in a forest",
        "target_prompt": "Amazing quality, masterpiece, A motorbike driving in a forest",
        "negative_prompt": "bad quality, distortions, unrealistic, distorted image, watermark, signature"
    }
)
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 lucataco/diffusion-motion-transfer 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": "lucataco/diffusion-motion-transfer:6bc872d3b943a49517b30192852477de7bea271e9abb76e726704ab4d6ae6eb3",
    "input": {
      "video": "https://replicate.delivery/pbxt/K7P4ZdV95HbR4aEof8ihr2j7UVWeFxHfoMWTG7H16gCy62Jf/demo.mp4",
      "n_timesteps": 900,
      "video_prompt": "Amazing quality, masterpiece, A locomotive rides in a forest",
      "target_prompt": "Amazing quality, masterpiece, A motorbike driving in a forest",
      "negative_prompt": "bad quality, distortions, unrealistic, distorted image, watermark, signature"
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

{
  "completed_at": "2023-12-26T23:00:11.795251Z",
  "created_at": "2023-12-26T22:49:56.255242Z",
  "data_removed": false,
  "error": null,
  "id": "kzt5qibbkfykg2eeddkqxuyrha",
  "input": {
    "video": "https://replicate.delivery/pbxt/K7P4ZdV95HbR4aEof8ihr2j7UVWeFxHfoMWTG7H16gCy62Jf/demo.mp4",
    "n_timesteps": 900,
    "video_prompt": "Amazing quality, masterpiece, A locomotive rides in a forest",
    "target_prompt": "Amazing quality, masterpiece, A motorbike driving in a forest",
    "negative_prompt": "bad quality, distortions, unrealistic, distorted image, watermark, signature"
  },
  "logs": "Using seed: 1676666084\nConverting input video to images\nffmpeg version 4.4.2-0ubuntu0.22.04.1 Copyright (c) 2000-2021 the FFmpeg developers\nbuilt with gcc 11 (Ubuntu 11.2.0-19ubuntu1)\nconfiguration: --prefix=/usr --extra-version=0ubuntu0.22.04.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libdav1d --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librabbitmq --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libsrt --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzimg --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-pocketsphinx --enable-librsvg --enable-libmfx --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared\nlibavutil      56. 70.100 / 56. 70.100\nlibavcodec     58.134.100 / 58.134.100\nlibavformat    58. 76.100 / 58. 76.100\nlibavdevice    58. 13.100 / 58. 13.100\nlibavfilter     7.110.100 /  7.110.100\nlibswscale      5.  9.100 /  5.  9.100\nlibswresample   3.  9.100 /  3.  9.100\nlibpostproc    55.  9.100 / 55.  9.100\nInput #0, mov,mp4,m4a,3gp,3g2,mj2, from '/tmp/tmp0hgv5r3xdemo.mp4':\nMetadata:\nmajor_brand     : isom\nminor_version   : 512\ncompatible_brands: isomiso2avc1mp41\nencoder         : Lavf60.3.100\nDuration: 00:00:01.00, start: 0.000000, bitrate: 1373 kb/s\nStream #0:0(und): Video: h264 (High) (avc1 / 0x31637661), yuv420p, 576x320, 1364 kb/s, 24 fps, 24 tbr, 12288 tbn, 48 tbc (default)\nMetadata:\nhandler_name    : VideoHandler\nvendor_id       : [0][0][0][0]\nencoder         : Lavc60.3.100 libx264\nStream mapping:\nStream #0:0 -> #0:0 (h264 (native) -> png (native))\nPress [q] to stop, [?] for help\nOutput #0, image2, to 'data/input/%05d.png':\nMetadata:\nmajor_brand     : isom\nminor_version   : 512\ncompatible_brands: isomiso2avc1mp41\nencoder         : Lavf58.76.100\nStream #0:0(und): Video: png, rgb24(pc, gbr/unknown/unknown, progressive), 576x320, q=2-31, 200 kb/s, 24 fps, 24 tbn (default)\nMetadata:\nhandler_name    : VideoHandler\nvendor_id       : [0][0][0][0]\nencoder         : Lavc58.134.100 png\nframe=    1 fps=0.0 q=0.0 size=N/A time=00:00:00.00 bitrate=N/A speed=   0x\nframe=   24 fps=0.0 q=-0.0 Lsize=N/A time=00:00:01.00 bitrate=N/A speed=12.5x\nvideo:10050kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: unknown\nRunning preprocessor script\nLoading video model\ntext_encoder/model.safetensors not found\nLoading pipeline components...:   0%|          | 0/5 [00:00<?, ?it/s]\nLoading pipeline components...:  20%|██        | 1/5 [00:02<00:10,  2.70s/it]\nLoading pipeline components...:  40%|████      | 2/5 [00:02<00:03,  1.26s/it]\nLoading pipeline components...:  80%|████████  | 4/5 [00:03<00:00,  1.90it/s]\nLoading pipeline components...: 100%|██████████| 5/5 [00:04<00:00,  1.42it/s]\nLoading pipeline components...: 100%|██████████| 5/5 [00:04<00:00,  1.18it/s]\nvideo model loaded\n/root/.pyenv/versions/3.9.18/lib/python3.9/site-packages/torchvision/io/video.py:83: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at ../torch/csrc/utils/tensor_new.cpp:245.)\nvideo_array = torch.as_tensor(video_array, dtype=torch.uint8).numpy()\n  0%|          | 0/900 [00:00<?, ?it/s]\n  0%|          | 1/900 [00:01<19:54,  1.33s/it]\n  0%|          | 2/900 [00:01<11:07,  1.35it/s]\n  0%|          | 3/900 [00:01<08:18,  1.80it/s]\n  0%|          | 4/900 [00:02<06:59,  2.14it/s]\n  1%|          | 5/900 [00:02<06:15,  2.39it/s]\n  1%|          | 6/900 [00:02<05:48,  2.56it/s]\n  1%|          | 7/900 [00:03<05:31,  2.69it/s]\n  1%|          | 8/900 [00:03<05:20,  2.78it/s]\n  1%|          | 9/900 [00:03<05:12,  2.85it/s]\n  1%|          | 10/900 [00:04<05:07,  2.90it/s]\n  1%|          | 11/900 [00:04<05:03,  2.93it/s]\n  1%|▏         | 12/900 [00:04<05:01,  2.95it/s]\n  1%|▏         | 13/900 [00:05<04:59,  2.96it/s]\n  2%|▏         | 14/900 [00:05<04:57,  2.97it/s]\n  2%|▏         | 15/900 [00:05<04:57,  2.98it/s]\n  2%|▏         | 16/900 [00:06<04:56,  2.99it/s]\n  2%|▏         | 17/900 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7.22s/it]\n  0%|          | 0/10 [00:00<?, ?it/s]\u001b[A\n 10%|█         | 1/10 [00:00<00:05,  1.68it/s]\u001b[A\n 20%|██        | 2/10 [00:01<00:04,  1.77it/s]\u001b[A\n 30%|███       | 3/10 [00:01<00:03,  1.81it/s]\u001b[A\n 40%|████      | 4/10 [00:02<00:03,  1.83it/s]\u001b[A\n 50%|█████     | 5/10 [00:02<00:02,  1.84it/s]\u001b[A\n 60%|██████    | 6/10 [00:03<00:02,  1.85it/s]\u001b[A\n 70%|███████   | 7/10 [00:03<00:01,  1.85it/s]\u001b[A\n 80%|████████  | 8/10 [00:04<00:01,  1.86it/s]\u001b[A\n 90%|█████████ | 9/10 [00:04<00:00,  1.86it/s]\u001b[A\n100%|██████████| 10/10 [00:05<00:00,  1.86it/s]\u001b[A\n100%|██████████| 10/10 [00:05<00:00,  1.84it/s]\nSampling:  22%|██▏       | 11/50 [01:19<04:41,  7.21s/it]\n  0%|          | 0/10 [00:00<?, ?it/s]\u001b[A\n 10%|█         | 1/10 [00:00<00:05,  1.58it/s]\u001b[A\n 20%|██        | 2/10 [00:01<00:04,  1.73it/s]\u001b[A\n 30%|███       | 3/10 [00:01<00:03,  1.79it/s]\u001b[A\n 40%|████      | 4/10 [00:02<00:03,  1.82it/s]\u001b[A\n 50%|█████     | 5/10 [00:02<00:02,  1.82it/s]\u001b[A\n 60%|██████    | 6/10 [00:03<00:02,  1.84it/s]\u001b[A\n 70%|███████   | 7/10 [00:03<00:01,  1.84it/s]\u001b[A\n 80%|████████  | 8/10 [00:04<00:01,  1.85it/s]\u001b[A\n 90%|█████████ | 9/10 [00:04<00:00,  1.85it/s]\u001b[A\n100%|██████████| 10/10 [00:05<00:00,  1.86it/s]\u001b[A\n100%|██████████| 10/10 [00:05<00:00,  1.83it/s]\nSampling:  24%|██▍       | 12/50 [01:27<04:35,  7.25s/it]\n  0%|          | 0/10 [00:00<?, ?it/s]\u001b[A\n 10%|█         | 1/10 [00:00<00:05,  1.61it/s]\u001b[A\n 20%|██        | 2/10 [00:01<00:04,  1.73it/s]\u001b[A\n 30%|███       | 3/10 [00:01<00:03,  1.78it/s]\u001b[A\n 40%|████      | 4/10 [00:02<00:03,  1.80it/s]\u001b[A\n 50%|█████     | 5/10 [00:02<00:02,  1.81it/s]\u001b[A\n 60%|██████    | 6/10 [00:03<00:02,  1.82it/s]\u001b[A\n 70%|███████   | 7/10 [00:03<00:01,  1.82it/s]\u001b[A\n 80%|████████  | 8/10 [00:04<00:01,  1.83it/s]\u001b[A\n 90%|█████████ | 9/10 [00:04<00:00,  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1.83it/s]\nSampling:  34%|███▍      | 17/50 [02:03<03:58,  7.23s/it]\n  0%|          | 0/10 [00:00<?, ?it/s]\u001b[A\n 10%|█         | 1/10 [00:00<00:05,  1.65it/s]\u001b[A\n 20%|██        | 2/10 [00:01<00:04,  1.76it/s]\u001b[A\n 30%|███       | 3/10 [00:01<00:03,  1.81it/s]\u001b[A\n 40%|████      | 4/10 [00:02<00:03,  1.83it/s]\u001b[A\n 50%|█████     | 5/10 [00:02<00:02,  1.84it/s]\u001b[A\n 60%|██████    | 6/10 [00:03<00:02,  1.84it/s]\u001b[A\n 70%|███████   | 7/10 [00:03<00:01,  1.85it/s]\u001b[A\n 80%|████████  | 8/10 [00:04<00:01,  1.85it/s]\u001b[A\n 90%|█████████ | 9/10 [00:04<00:00,  1.86it/s]\u001b[A\n100%|██████████| 10/10 [00:05<00:00,  1.86it/s]\u001b[A\n100%|██████████| 10/10 [00:05<00:00,  1.84it/s]\nSampling:  36%|███▌      | 18/50 [02:10<03:51,  7.22s/it]\n  0%|          | 0/10 [00:00<?, ?it/s]\u001b[A\n 10%|█         | 1/10 [00:00<00:05,  1.64it/s]\u001b[A\n 20%|██        | 2/10 [00:01<00:04,  1.76it/s]\u001b[A\n 30%|███       | 3/10 [00:01<00:03,  1.81it/s]\u001b[A\n 40%|████      | 4/10 [00:02<00:03,  1.83it/s]\u001b[A\n 50%|█████     | 5/10 [00:02<00:02,  1.84it/s]\u001b[A\n 60%|██████    | 6/10 [00:03<00:02,  1.84it/s]\u001b[A\n 70%|███████   | 7/10 [00:03<00:01,  1.85it/s]\u001b[A\n 80%|████████  | 8/10 [00:04<00:01,  1.85it/s]\u001b[A\n 90%|█████████ | 9/10 [00:04<00:00,  1.85it/s]\u001b[A\n100%|██████████| 10/10 [00:05<00:00,  1.85it/s]\u001b[A\n100%|██████████| 10/10 [00:05<00:00,  1.83it/s]\nSampling:  38%|███▊      | 19/50 [02:17<03:43,  7.21s/it]\n  0%|          | 0/10 [00:00<?, ?it/s]\u001b[A\n 10%|█         | 1/10 [00:00<00:05,  1.60it/s]\u001b[A\n 20%|██        | 2/10 [00:01<00:04,  1.74it/s]\u001b[A\n 30%|███       | 3/10 [00:01<00:03,  1.78it/s]\u001b[A\n 40%|████      | 4/10 [00:02<00:03,  1.81it/s]\u001b[A\n 50%|█████     | 5/10 [00:02<00:02,  1.83it/s]\u001b[A\n 60%|██████    | 6/10 [00:03<00:02,  1.84it/s]\u001b[A\n 70%|███████   | 7/10 [00:03<00:01,  1.84it/s]\u001b[A\n 80%|████████  | 8/10 [00:04<00:01,  1.85it/s]\u001b[A\n 90%|█████████ | 9/10 [00:04<00:00,  1.85it/s]\u001b[A\n100%|██████████| 10/10 [00:05<00:00,  1.85it/s]\u001b[A\n100%|██████████| 10/10 [00:05<00:00,  1.83it/s]\nSampling:  40%|████      | 20/50 [02:24<03:36,  7.20s/it]\nSampling:  42%|████▏     | 21/50 [02:26<02:39,  5.49s/it]\nSampling:  44%|████▍     | 22/50 [02:27<02:01,  4.35s/it]\nSampling:  46%|████▌     | 23/50 [02:29<01:35,  3.53s/it]\nSampling:  48%|████▊     | 24/50 [02:31<01:16,  2.95s/it]\nSampling:  50%|█████     | 25/50 [02:32<01:03,  2.54s/it]\nSampling:  52%|█████▏    | 26/50 [02:34<00:54,  2.26s/it]\nSampling:  54%|█████▍    | 27/50 [02:35<00:47,  2.05s/it]\nSampling:  56%|█████▌    | 28/50 [02:37<00:42,  1.91s/it]\nSampling:  58%|█████▊    | 29/50 [02:39<00:37,  1.78s/it]\nSampling:  60%|██████    | 30/50 [02:40<00:33,  1.70s/it]\nSampling:  62%|██████▏   | 31/50 [02:41<00:30,  1.63s/it]\nSampling:  64%|██████▍   | 32/50 [02:43<00:28,  1.59s/it]\nSampling:  66%|██████▌   | 33/50 [02:44<00:26,  1.56s/it]\nSampling:  68%|██████▊   | 34/50 [02:46<00:24,  1.53s/it]\nSampling:  70%|███████   | 35/50 [02:47<00:22,  1.52s/it]\nSampling:  72%|███████▏  | 36/50 [02:49<00:21,  1.51s/it]\nSampling:  74%|███████▍  | 37/50 [02:50<00:19,  1.50s/it]\nSampling:  76%|███████▌  | 38/50 [02:52<00:17,  1.49s/it]\nSampling:  78%|███████▊  | 39/50 [02:53<00:16,  1.49s/it]\nSampling:  80%|████████  | 40/50 [02:55<00:14,  1.48s/it]\nSampling:  82%|████████▏ | 41/50 [02:56<00:13,  1.48s/it]\nSampling:  84%|████████▍ | 42/50 [02:58<00:11,  1.48s/it]\nSampling:  86%|████████▌ | 43/50 [02:59<00:10,  1.47s/it]\nSampling:  88%|████████▊ | 44/50 [03:01<00:08,  1.48s/it]\nSampling:  90%|█████████ | 45/50 [03:02<00:07,  1.47s/it]\nSampling:  92%|█████████▏| 46/50 [03:04<00:05,  1.47s/it]\nSampling:  94%|█████████▍| 47/50 [03:05<00:04,  1.48s/it]\nSampling:  96%|█████████▌| 48/50 [03:07<00:02,  1.48s/it]\nSampling:  98%|█████████▊| 49/50 [03:08<00:01,  1.48s/it]\nSampling: 100%|██████████| 50/50 [03:09<00:00,  1.31s/it]\nSampling: 100%|██████████| 50/50 [03:09<00:00,  3.79s/it]",
  "metrics": {
    "predict_time": 528.967405,
    "total_time": 615.540009
  },
  "output": "https://replicate.delivery/pbxt/aEElw4dobuaDOpze2rtjDTNAz5egx3pBhxFVVGEfoRevPDZIB/result.mp4",
  "started_at": "2023-12-26T22:51:22.827846Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/kzt5qibbkfykg2eeddkqxuyrha",
    "cancel": "https://api.replicate.com/v1/predictions/kzt5qibbkfykg2eeddkqxuyrha/cancel"
  },
  "version": "6bc872d3b943a49517b30192852477de7bea271e9abb76e726704ab4d6ae6eb3"
}

Generated in

8 minutes 49 seconds

Tweak itReport

Using seed: 1676666084
Converting input video to images
ffmpeg version 4.4.2-0ubuntu0.22.04.1 Copyright (c) 2000-2021 the FFmpeg developers
built with gcc 11 (Ubuntu 11.2.0-19ubuntu1)
configuration: --prefix=/usr --extra-version=0ubuntu0.22.04.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libdav1d --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librabbitmq --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libsrt --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzimg --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-pocketsphinx --enable-librsvg --enable-libmfx --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared
libavutil      56. 70.100 / 56. 70.100
libavcodec     58.134.100 / 58.134.100
libavformat    58. 76.100 / 58. 76.100
libavdevice    58. 13.100 / 58. 13.100
libavfilter     7.110.100 /  7.110.100
libswscale      5.  9.100 /  5.  9.100
libswresample   3.  9.100 /  3.  9.100
libpostproc    55.  9.100 / 55.  9.100
Input #0, mov,mp4,m4a,3gp,3g2,mj2, from '/tmp/tmp0hgv5r3xdemo.mp4':
Metadata:
major_brand     : isom
minor_version   : 512
compatible_brands: isomiso2avc1mp41
encoder         : Lavf60.3.100
Duration: 00:00:01.00, start: 0.000000, bitrate: 1373 kb/s
Stream #0:0(und): Video: h264 (High) (avc1 / 0x31637661), yuv420p, 576x320, 1364 kb/s, 24 fps, 24 tbr, 12288 tbn, 48 tbc (default)
Metadata:
handler_name    : VideoHandler
vendor_id       : [0][0][0][0]
encoder         : Lavc60.3.100 libx264
Stream mapping:
Stream #0:0 -> #0:0 (h264 (native) -> png (native))
Press [q] to stop, [?] for help
Output #0, image2, to 'data/input/%05d.png':
Metadata:
major_brand     : isom
minor_version   : 512
compatible_brands: isomiso2avc1mp41
encoder         : Lavf58.76.100
Stream #0:0(und): Video: png, rgb24(pc, gbr/unknown/unknown, progressive), 576x320, q=2-31, 200 kb/s, 24 fps, 24 tbn (default)
Metadata:
handler_name    : VideoHandler
vendor_id       : [0][0][0][0]
encoder         : Lavc58.134.100 png
frame=    1 fps=0.0 q=0.0 size=N/A time=00:00:00.00 bitrate=N/A speed=   0x
frame=   24 fps=0.0 q=-0.0 Lsize=N/A time=00:00:01.00 bitrate=N/A speed=12.5x
video:10050kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: unknown
Running preprocessor script
Loading video model
text_encoder/model.safetensors not found
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video model loaded
/root/.pyenv/versions/3.9.18/lib/python3.9/site-packages/torchvision/io/video.py:83: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at ../torch/csrc/utils/tensor_new.cpp:245.)
video_array = torch.as_tensor(video_array, dtype=torch.uint8).numpy()
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Running editing script
Loading video model
unet/diffusion_pytorch_model.safetensors not found
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