Prediction

Model

tahercoolguy/diffutoon:c1981efb

wm5t9ejhb9rgm0chjxy8nfgexw

Status

Succeeded

Source

Web

Hardware

A40

Total duration

10m 28s

Created

over 1 year ago

Webhook

–

Input

input_video: https://replicate.delivery/pbxt/LWT4W9jAKsv5iAuHYe8jsfeb5t0Dze3Wgvs0FSSCfLkoWN1v/videoplayback%20%28online-video-cutter.com%29.mp4
prompt: best quality, perfect anime illustration
prompt_2: best quality, perfect anime illustration, light

{
  "input_video": "https://replicate.delivery/pbxt/LWT4W9jAKsv5iAuHYe8jsfeb5t0Dze3Wgvs0FSSCfLkoWN1v/videoplayback%20%28online-video-cutter.com%29.mp4",
  "prompt": "best quality, perfect anime illustration",
  "prompt_2": "best quality, perfect anime illustration, light"
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_Bqq**********************************

This is your API token. Keep it to yourself.

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run tahercoolguy/diffutoon using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "tahercoolguy/diffutoon:c1981efbe73ce88114364ca3634cc08d9e34934b02c75b68652efc7690867fc4",
  {
    input: {
      input_video: "https://replicate.delivery/pbxt/LWT4W9jAKsv5iAuHYe8jsfeb5t0Dze3Wgvs0FSSCfLkoWN1v/videoplayback%20%28online-video-cutter.com%29.mp4",
      prompt: "best quality, perfect anime illustration",
      prompt_2: "best quality, perfect anime illustration, light"
    }
  }
);

// 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=r8_Bqq**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run tahercoolguy/diffutoon using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "tahercoolguy/diffutoon:c1981efbe73ce88114364ca3634cc08d9e34934b02c75b68652efc7690867fc4",
    input={
        "input_video": "https://replicate.delivery/pbxt/LWT4W9jAKsv5iAuHYe8jsfeb5t0Dze3Wgvs0FSSCfLkoWN1v/videoplayback%20%28online-video-cutter.com%29.mp4",
        "prompt": "best quality, perfect anime illustration",
        "prompt_2": "best quality, perfect anime illustration, light"
    }
)

# To access the file URL:
print(output.url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output.read())

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=r8_Bqq**********************************

This is your API token. Keep it to yourself.

Run tahercoolguy/diffutoon 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": "tahercoolguy/diffutoon:c1981efbe73ce88114364ca3634cc08d9e34934b02c75b68652efc7690867fc4",
    "input": {
      "input_video": "https://replicate.delivery/pbxt/LWT4W9jAKsv5iAuHYe8jsfeb5t0Dze3Wgvs0FSSCfLkoWN1v/videoplayback%20%28online-video-cutter.com%29.mp4",
      "prompt": "best quality, perfect anime illustration",
      "prompt_2": "best quality, perfect anime illustration, light"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "id": "wm5t9ejhb9rgm0chjxy8nfgexw",
  "model": "tahercoolguy/diffutoon",
  "version": "c1981efbe73ce88114364ca3634cc08d9e34934b02c75b68652efc7690867fc4",
  "input": {
    "input_video": "https://replicate.delivery/pbxt/LWT4W9jAKsv5iAuHYe8jsfeb5t0Dze3Wgvs0FSSCfLkoWN1v/videoplayback%20%28online-video-cutter.com%29.mp4",
    "prompt": "best quality, perfect anime illustration",
    "prompt_2": "best quality, perfect anime illustration, light"
  },
  "logs": "Loading models from: models/stable_diffusion/aingdiffusion_v12.safetensors\nmodel_name: sd_text_encoder model_class: SDTextEncoder\nmodel_name: sd_unet model_class: SDUNet\nmodel_name: sd_vae_decoder model_class: SDVAEDecoder\nmodel_name: sd_vae_encoder model_class: SDVAEEncoder\nThe following models are loaded: ['sd_text_encoder', 'sd_unet', 'sd_vae_decoder', 'sd_vae_encoder'].\nLoading models from: models/ControlNet/control_v11p_sd15_softedge.pth\nmodel_name: sd_controlnet model_class: SDControlNet\n    The following models are loaded: ['sd_controlnet'].\nLoading models from: models/ControlNet/control_v11f1p_sd15_depth.pth\nmodel_name: sd_controlnet model_class: SDControlNet\n    The following models are loaded: ['sd_controlnet'].\nUsing sd_text_encoder from models/stable_diffusion/aingdiffusion_v12.safetensors.\nUsing sd_unet from models/stable_diffusion/aingdiffusion_v12.safetensors.\nUsing sd_vae_decoder from models/stable_diffusion/aingdiffusion_v12.safetensors.\nUsing sd_vae_encoder from models/stable_diffusion/aingdiffusion_v12.safetensors.\nUsing sd_controlnet from models/ControlNet/control_v11p_sd15_softedge.pth.\n/root/.pyenv/versions/3.10.14/lib/python3.10/site-packages/timm/models/_factory.py:117: UserWarning: Mapping deprecated model name vit_base_resnet50_384 to current vit_base_r50_s16_384.orig_in21k_ft_in1k.\nmodel = create_fn(\nUsing sd_controlnet from models/ControlNet/control_v11f1p_sd15_depth.pth.\nNo sd_ipadapter models available.\nNo sd_ipadapter_clip_image_encoder models available.\nNo sd_motion_modules models available.\nTextual inversion verybadimagenegative_v1.3 is enabled.\n  0%|          | 0/30 [00:00<?, ?it/s]\n 13%|█▎        | 4/30 [00:00<00:00, 35.27it/s]\n 33%|███▎      | 10/30 [00:00<00:00, 47.84it/s]\n 53%|█████▎    | 16/30 [00:00<00:00, 52.49it/s]\n 73%|███████▎  | 22/30 [00:00<00:00, 54.72it/s]\n 93%|█████████▎| 28/30 [00:00<00:00, 55.80it/s]\n100%|██████████| 30/30 [00:00<00:00, 53.08it/s]\n  0%|          | 0/30 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images:  13%|█▎        | 4/30 [00:00<00:02, 12.41it/s]\nSaving images:  20%|██        | 6/30 [00:00<00:01, 12.55it/s]\nSaving images:  27%|██▋       | 8/30 [00:00<00:01, 12.62it/s]\nSaving images:  33%|███▎      | 10/30 [00:00<00:01, 12.67it/s]\nSaving images:  40%|████      | 12/30 [00:00<00:01, 12.66it/s]\nSaving images:  47%|████▋     | 14/30 [00:01<00:01, 12.65it/s]\nSaving images:  53%|█████▎    | 16/30 [00:01<00:01, 12.60it/s]\nSaving images:  60%|██████    | 18/30 [00:01<00:00, 12.61it/s]\nSaving images:  67%|██████▋   | 20/30 [00:01<00:00, 12.61it/s]\nSaving images:  73%|███████▎  | 22/30 [00:01<00:00, 12.59it/s]\nSaving images:  80%|████████  | 24/30 [00:01<00:00, 12.57it/s]\nSaving images:  87%|████████▋ | 26/30 [00:02<00:00, 12.56it/s]\nSaving images:  93%|█████████▎| 28/30 [00:02<00:00, 12.56it/s]\nSaving images: 100%|██████████| 30/30 [00:02<00:00, 12.55it/s]\nSaving images: 100%|██████████| 30/30 [00:02<00:00, 12.58it/s]\nSaving video:   0%|          | 0/30 [00:00<?, ?it/s]\nSaving video:   3%|▎         | 1/30 [00:00<00:06,  4.52it/s]\nSaving video: 100%|██████████| 30/30 [00:00<00:00, 112.54it/s]\nLoading models from: models/stable_diffusion/aingdiffusion_v12.safetensors\nmodel_name: sd_text_encoder model_class: SDTextEncoder\nmodel_name: sd_unet model_class: SDUNet\nmodel_name: sd_vae_decoder model_class: SDVAEDecoder\nmodel_name: sd_vae_encoder model_class: SDVAEEncoder\nThe following models are loaded: ['sd_text_encoder', 'sd_unet', 'sd_vae_decoder', 'sd_vae_encoder'].\nLoading models from: models/AnimateDiff/mm_sd_v15_v2.ckpt\nmodel_name: sd_motion_modules model_class: SDMotionModel\n    The following models are loaded: ['sd_motion_modules'].\nLoading models from: models/ControlNet/control_v11f1e_sd15_tile.pth\nmodel_name: sd_controlnet model_class: SDControlNet\n    The following models are loaded: ['sd_controlnet'].\nLoading models from: models/ControlNet/control_v11p_sd15_lineart.pth\nmodel_name: sd_controlnet model_class: SDControlNet\n    The following models are loaded: ['sd_controlnet'].\nUsing sd_text_encoder from models/stable_diffusion/aingdiffusion_v12.safetensors.\nUsing sd_unet from models/stable_diffusion/aingdiffusion_v12.safetensors.\nUsing sd_vae_decoder from models/stable_diffusion/aingdiffusion_v12.safetensors.\nUsing sd_vae_encoder from models/stable_diffusion/aingdiffusion_v12.safetensors.\nUsing sd_controlnet from models/ControlNet/control_v11f1e_sd15_tile.pth.\nUsing sd_controlnet from models/ControlNet/control_v11p_sd15_lineart.pth.\nNo sd_ipadapter models available.\nNo sd_ipadapter_clip_image_encoder models available.\nUsing sd_motion_modules from models/AnimateDiff/mm_sd_v15_v2.ckpt.\nTextual inversion verybadimagenegative_v1.3 is enabled.\n  0%|          | 0/30 [00:00<?, ?it/s]\n 57%|█████▋    | 17/30 [00:00<00:00, 166.58it/s]\n100%|██████████| 30/30 [00:00<00:00, 180.05it/s]\n  0%|          | 0/30 [00:00<?, ?it/s]\n  3%|▎         | 1/30 [00:03<01:42,  3.52s/it]\n 10%|█         | 3/30 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  "output": "https://replicate.delivery/pbxt/ziy8T6relvVsS6dhIDzXPeuTncsqeexeTIRfJIz23zv60rx1E/video.mp4",
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2024-08-28T05:36:32.602Z",
  "started_at": "2024-08-28T05:39:34.641208Z",
  "completed_at": "2024-08-28T05:47:00.843157Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/wm5t9ejhb9rgm0chjxy8nfgexw/cancel",
    "get": "https://api.replicate.com/v1/predictions/wm5t9ejhb9rgm0chjxy8nfgexw",
    "web": "https://replicate.com/p/wm5t9ejhb9rgm0chjxy8nfgexw"
  },
  "metrics": {
    "predict_time": 446.201949052,
    "total_time": 628.241157
  }
}

Generated in

7 minutes 26 seconds

Tweak it Report

Loading models from: models/stable_diffusion/aingdiffusion_v12.safetensors model_name: sd_text_encoder model_class: SDTextEncoder model_name: sd_unet model_class: SDUNet model_name: sd_vae_decoder model_class: SDVAEDecoder model_name: sd_vae_encoder model_class: SDVAEEncoder The following models are loaded: ['sd_text_encoder', 'sd_unet', 'sd_vae_decoder', 'sd_vae_encoder']. Loading models from: models/ControlNet/control_v11p_sd15_softedge.pth model_name: sd_controlnet model_class: SDControlNet The following models are loaded: ['sd_controlnet']. Loading models from: models/ControlNet/control_v11f1p_sd15_depth.pth model_name: sd_controlnet model_class: SDControlNet The following models are loaded: ['sd_controlnet']. Using sd_text_encoder from models/stable_diffusion/aingdiffusion_v12.safetensors. Using sd_unet from models/stable_diffusion/aingdiffusion_v12.safetensors. Using sd_vae_decoder from models/stable_diffusion/aingdiffusion_v12.safetensors. Using sd_vae_encoder from models/stable_diffusion/aingdiffusion_v12.safetensors. Using sd_controlnet from models/ControlNet/control_v11p_sd15_softedge.pth. /root/.pyenv/versions/3.10.14/lib/python3.10/site-packages/timm/models/_factory.py:117: UserWarning: Mapping deprecated model name vit_base_resnet50_384 to current vit_base_r50_s16_384.orig_in21k_ft_in1k. model = create_fn( Using sd_controlnet from models/ControlNet/control_v11f1p_sd15_depth.pth. No sd_ipadapter models available. No sd_ipadapter_clip_image_encoder models available. No sd_motion_modules models available. 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12.55it/s] Saving images: 27%|██▋ | 8/30 [00:00<00:01, 12.62it/s] Saving images: 33%|███▎ | 10/30 [00:00<00:01, 12.67it/s] Saving images: 40%|████ | 12/30 [00:00<00:01, 12.66it/s] Saving images: 47%|████▋ | 14/30 [00:01<00:01, 12.65it/s] Saving images: 53%|█████▎ | 16/30 [00:01<00:01, 12.60it/s] Saving images: 60%|██████ | 18/30 [00:01<00:00, 12.61it/s] Saving images: 67%|██████▋ | 20/30 [00:01<00:00, 12.61it/s] Saving images: 73%|███████▎ | 22/30 [00:01<00:00, 12.59it/s] Saving images: 80%|████████ | 24/30 [00:01<00:00, 12.57it/s] Saving images: 87%|████████▋ | 26/30 [00:02<00:00, 12.56it/s] Saving images: 93%|█████████▎| 28/30 [00:02<00:00, 12.56it/s] Saving images: 100%|██████████| 30/30 [00:02<00:00, 12.55it/s] Saving images: 100%|██████████| 30/30 [00:02<00:00, 12.58it/s] Saving video: 0%| | 0/30 [00:00<?, ?it/s] Saving video: 3%|▎ | 1/30 [00:00<00:06, 4.52it/s] Saving video: 100%|██████████| 30/30 [00:00<00:00, 112.54it/s] Loading models from: models/stable_diffusion/aingdiffusion_v12.safetensors model_name: sd_text_encoder model_class: SDTextEncoder model_name: sd_unet model_class: SDUNet model_name: sd_vae_decoder model_class: SDVAEDecoder model_name: sd_vae_encoder model_class: SDVAEEncoder The following models are loaded: ['sd_text_encoder', 'sd_unet', 'sd_vae_decoder', 'sd_vae_encoder']. Loading models from: models/AnimateDiff/mm_sd_v15_v2.ckpt model_name: sd_motion_modules model_class: SDMotionModel The following models are loaded: ['sd_motion_modules']. Loading models from: models/ControlNet/control_v11f1e_sd15_tile.pth model_name: sd_controlnet model_class: SDControlNet The following models are loaded: ['sd_controlnet']. Loading models from: models/ControlNet/control_v11p_sd15_lineart.pth model_name: sd_controlnet model_class: SDControlNet The following models are loaded: ['sd_controlnet']. Using sd_text_encoder from models/stable_diffusion/aingdiffusion_v12.safetensors. Using sd_unet from models/stable_diffusion/aingdiffusion_v12.safetensors. Using sd_vae_decoder from models/stable_diffusion/aingdiffusion_v12.safetensors. Using sd_vae_encoder from models/stable_diffusion/aingdiffusion_v12.safetensors. Using sd_controlnet from models/ControlNet/control_v11f1e_sd15_tile.pth. Using sd_controlnet from models/ControlNet/control_v11p_sd15_lineart.pth. No sd_ipadapter models available. No sd_ipadapter_clip_image_encoder models available. Using sd_motion_modules from models/AnimateDiff/mm_sd_v15_v2.ckpt. 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