lucataco/demofusion-enhance:5bcfe110 – Run with an API on Replicate

Version

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lucataco /demofusion-enhance:5bcfe110

Playground API

Input

image

*file

Input image

scale

integer

Scale factor for input image

Default: 2

prompt

string

Shift + Return to add a new line

Input prompt

Default: "A high resolution photo"

auto_prompt

boolean

Select to use auto-generated CLIP prompt instead of using the above custom prompt

Default: false

negative_prompt

string

Shift + Return to add a new line

blurry, ugly, duplicate, poorly drawn, deformed, mosaicblurry, ugly, duplicate, poorly drawn, deformed, mosaic

Input Negative Prompt

Default: "blurry, ugly, duplicate, poorly drawn, deformed, mosaic"

num_inference_steps

integer

(minimum: 1, maximum: 500)

Number of denoising steps

Default: 40

guidance_scale

number

(minimum: 1, maximum: 50)

Scale for classifier-free guidance

Default: 8.5

view_batch_size

integer

The batch size for multiple denoising paths

Default: 16

stride

integer

The stride of moving local patches

Default: 64

cosine_scale_1

number

Control the strength of skip-residual

Default: 3

cosine_scale_2

number

Control the strength of dilated sampling

Default: 1

cosine_scale_3

number

Control the strength of the Gaussian filter

Default: 1

sigma

number

The standard value of the Gaussian filter

Default: 0.8

multi_decoder

boolean

Use multiple decoders

Default: false

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/demofusion-enhance

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/demofusion-enhance using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/demofusion-enhance:5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e",
  {
    input: {
      image: "https://replicate.delivery/pbxt/K10lBG3tNt90JMoDcWDbOozDrx7FoS5MUZwNe1cynZMMHvv4/GAdGE95XgAAYw5K.jpeg",
      scale: 2,
      sigma: 0.8,
      prompt: "A high resolution photo",
      stride: 64,
      auto_prompt: true,
      multi_decoder: false,
      cosine_scale_1: 3,
      cosine_scale_2: 1,
      cosine_scale_3: 1,
      guidance_scale: 8.5,
      negative_prompt: "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
      view_batch_size: 16,
      num_inference_steps: 40
    }
  }
);
console.log(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/demofusion-enhance using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/demofusion-enhance:5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e",
    input={
        "image": "https://replicate.delivery/pbxt/K10lBG3tNt90JMoDcWDbOozDrx7FoS5MUZwNe1cynZMMHvv4/GAdGE95XgAAYw5K.jpeg",
        "scale": 2,
        "sigma": 0.8,
        "prompt": "A high resolution photo",
        "stride": 64,
        "auto_prompt": True,
        "multi_decoder": False,
        "cosine_scale_1": 3,
        "cosine_scale_2": 1,
        "cosine_scale_3": 1,
        "guidance_scale": 8.5,
        "negative_prompt": "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
        "view_batch_size": 16,
        "num_inference_steps": 40
    }
)
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/demofusion-enhance 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": "5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e",
    "input": {
      "image": "https://replicate.delivery/pbxt/K10lBG3tNt90JMoDcWDbOozDrx7FoS5MUZwNe1cynZMMHvv4/GAdGE95XgAAYw5K.jpeg",
      "scale": 2,
      "sigma": 0.8,
      "prompt": "A high resolution photo",
      "stride": 64,
      "auto_prompt": true,
      "multi_decoder": false,
      "cosine_scale_1": 3,
      "cosine_scale_2": 1,
      "cosine_scale_3": 1,
      "guidance_scale": 8.5,
      "negative_prompt": "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
      "view_batch_size": 16,
      "num_inference_steps": 40
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2023-12-08T22:39:36.605614Z",
  "created_at": "2023-12-08T22:38:03.368552Z",
  "data_removed": false,
  "error": null,
  "id": "xuvor4dbpdflrg7g67gz3wjozy",
  "input": {
    "image": "https://replicate.delivery/pbxt/K10lBG3tNt90JMoDcWDbOozDrx7FoS5MUZwNe1cynZMMHvv4/GAdGE95XgAAYw5K.jpeg",
    "scale": 2,
    "sigma": 0.8,
    "stride": 64,
    "auto_prompt": true,
    "multi_decoder": false,
    "cosine_scale_1": 3,
    "cosine_scale_2": 1,
    "cosine_scale_3": 1,
    "guidance_scale": 8.5,
    "negative_prompt": "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
    "view_batch_size": 16,
    "num_inference_steps": 40
  },
  "logs": "Using seed: 2418900051\n  0%|          | 0/55 [00:00<?, ?it/s]\n 44%|████▎     | 24/55 [00:00<00:00, 234.03it/s]\n 91%|█████████ | 50/55 [00:00<00:00, 245.82it/s]\n100%|██████████| 55/55 [00:00<00:00, 245.46it/s]\nFlavor chain:   0%|          | 0/32 [00:00<?, ?it/s]\nFlavor chain:   3%|▎         | 1/32 [00:01<00:59,  1.93s/it]\nFlavor chain:   6%|▋         | 2/32 [00:03<00:58,  1.94s/it]\nFlavor chain:   9%|▉         | 3/32 [00:05<00:56,  1.96s/it]\nFlavor chain:  12%|█▎        | 4/32 [00:07<00:55,  1.97s/it]\nFlavor chain:  16%|█▌        | 5/32 [00:09<00:53,  1.99s/it]\nFlavor chain:  19%|█▉        | 6/32 [00:11<00:52,  2.01s/it]\nFlavor chain:  22%|██▏       | 7/32 [00:13<00:50,  2.02s/it]\nFlavor chain:  25%|██▌       | 8/32 [00:16<00:48,  2.04s/it]\nFlavor chain:  28%|██▊       | 9/32 [00:18<00:47,  2.06s/it]\nFlavor chain:  31%|███▏      | 10/32 [00:20<00:45,  2.08s/it]\nFlavor chain:  34%|███▍      | 11/32 [00:22<00:44,  2.10s/it]\nFlavor chain:  38%|███▊      | 12/32 [00:24<00:42,  2.13s/it]\nFlavor chain:  38%|███▊      | 12/32 [00:26<00:44,  2.24s/it]\n  0%|          | 0/55 [00:00<?, ?it/s]\n 45%|████▌     | 25/55 [00:00<00:00, 244.96it/s]\n 93%|█████████▎| 51/55 [00:00<00:00, 250.61it/s]\n100%|██████████| 55/55 [00:00<00:00, 250.56it/s]\n  0%|          | 0/6 [00:00<?, ?it/s]\n100%|██████████| 6/6 [00:00<00:00, 241.91it/s]\n  0%|          | 0/50 [00:00<?, ?it/s]\n 64%|██████▍   | 32/50 [00:00<00:00, 315.42it/s]\n100%|██████████| 50/50 [00:00<00:00, 318.89it/s]\nPrompt:  a close up of a person in a uniform holding a sword, syphon filter, wearing shiny black goggles, big boss, slightly pixelated, dark blue skin, early night, looking into the distance, 64x64, lower half of his body is snake, chilled out smirk on face, dark and stars in the background, centered shoulders up view\n### Phase Encoding ###\n  0%|          | 0/40 [00:00<?, ?it/s]\n0%|          | 0/40 [00:00<?, ?it/s]\n### Phase 1 Denoising ###\n  0%|          | 0/40 [00:00<?, ?it/s]\n  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40/40 [00:09<00:00,  4.30it/s]\n### Phase 2 Denoising ###\n  0%|          | 0/40 [00:00<?, ?it/s]\n  2%|▎         | 1/40 [00:01<00:50,  1.28s/it]\n  5%|▌         | 2/40 [00:02<00:48,  1.29s/it]\n  8%|▊         | 3/40 [00:03<00:47,  1.29s/it]\n 10%|█         | 4/40 [00:05<00:46,  1.29s/it]\n 12%|█▎        | 5/40 [00:06<00:45,  1.29s/it]\n 15%|█▌        | 6/40 [00:07<00:43,  1.29s/it]\n 18%|█▊        | 7/40 [00:09<00:42,  1.29s/it]\n 20%|██        | 8/40 [00:10<00:41,  1.29s/it]\n 22%|██▎       | 9/40 [00:11<00:39,  1.29s/it]\n 25%|██▌       | 10/40 [00:12<00:38,  1.29s/it]\n 28%|██▊       | 11/40 [00:14<00:37,  1.29s/it]\n 30%|███       | 12/40 [00:15<00:36,  1.29s/it]\n 32%|███▎      | 13/40 [00:16<00:34,  1.29s/it]\n 35%|███▌      | 14/40 [00:18<00:33,  1.29s/it]\n 38%|███▊      | 15/40 [00:19<00:32,  1.29s/it]\n 40%|████      | 16/40 [00:20<00:30,  1.29s/it]\n 42%|████▎     | 17/40 [00:21<00:29,  1.29s/it]\n 45%|████▌     | 18/40 [00:23<00:28,  1.29s/it]\n 48%|████▊     | 19/40 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1.29s/it]\n### Phase 2 Decoding ###\n100%|██████████| 40/40 [00:51<00:00,  1.29s/it]\n100%|██████████| 40/40 [00:52<00:00,  1.31s/it]",
  "metrics": {
    "predict_time": 93.199234,
    "total_time": 93.237062
  },
  "output": "https://replicate.delivery/pbxt/WjOeXFNnL6V2OyKBns3LWio01hsHKRpwmxy9tSILQ9sTaKAJA/out-2.png",
  "started_at": "2023-12-08T22:38:03.406380Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/xuvor4dbpdflrg7g67gz3wjozy",
    "cancel": "https://api.replicate.com/v1/predictions/xuvor4dbpdflrg7g67gz3wjozy/cancel"
  },
  "version": "5bcfe11066c820e8c08232c6efa3c8a7ab2cd667ad136ca173633f352170691e"
}

Generated in

1 minute 33 seconds

Tweak itReport

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Prompt:  a close up of a person in a uniform holding a sword, syphon filter, wearing shiny black goggles, big boss, slightly pixelated, dark blue skin, early night, looking into the distance, 64x64, lower half of his body is snake, chilled out smirk on face, dark and stars in the background, centered shoulders up view
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 95%|█████████▌| 38/40 [00:08<00:00,  4.41it/s]
 98%|█████████▊| 39/40 [00:08<00:00,  4.41it/s]
### Phase 1 Decoding ###
100%|██████████| 40/40 [00:09<00:00,  4.41it/s]
100%|██████████| 40/40 [00:09<00:00,  4.30it/s]
### Phase 2 Denoising ###
  0%|          | 0/40 [00:00<?, ?it/s]
  2%|▎         | 1/40 [00:01<00:50,  1.28s/it]
  5%|▌         | 2/40 [00:02<00:48,  1.29s/it]
  8%|▊         | 3/40 [00:03<00:47,  1.29s/it]
 10%|█         | 4/40 [00:05<00:46,  1.29s/it]
 12%|█▎        | 5/40 [00:06<00:45,  1.29s/it]
 15%|█▌        | 6/40 [00:07<00:43,  1.29s/it]
 18%|█▊        | 7/40 [00:09<00:42,  1.29s/it]
 20%|██        | 8/40 [00:10<00:41,  1.29s/it]
 22%|██▎       | 9/40 [00:11<00:39,  1.29s/it]
 25%|██▌       | 10/40 [00:12<00:38,  1.29s/it]
 28%|██▊       | 11/40 [00:14<00:37,  1.29s/it]
 30%|███       | 12/40 [00:15<00:36,  1.29s/it]
 32%|███▎      | 13/40 [00:16<00:34,  1.29s/it]
 35%|███▌      | 14/40 [00:18<00:33,  1.29s/it]
 38%|███▊      | 15/40 [00:19<00:32,  1.29s/it]
 40%|████      | 16/40 [00:20<00:30,  1.29s/it]
 42%|████▎     | 17/40 [00:21<00:29,  1.29s/it]
 45%|████▌     | 18/40 [00:23<00:28,  1.29s/it]
 48%|████▊     | 19/40 [00:24<00:27,  1.29s/it]
 50%|█████     | 20/40 [00:25<00:25,  1.29s/it]
 52%|█████▎    | 21/40 [00:27<00:24,  1.29s/it]
 55%|█████▌    | 22/40 [00:28<00:23,  1.29s/it]
 57%|█████▊    | 23/40 [00:29<00:21,  1.29s/it]
 60%|██████    | 24/40 [00:30<00:20,  1.29s/it]
 62%|██████▎   | 25/40 [00:32<00:19,  1.29s/it]
 65%|██████▌   | 26/40 [00:33<00:18,  1.29s/it]
 68%|██████▊   | 27/40 [00:34<00:16,  1.29s/it]
 70%|███████   | 28/40 [00:36<00:15,  1.29s/it]
 72%|███████▎  | 29/40 [00:37<00:14,  1.29s/it]
 75%|███████▌  | 30/40 [00:38<00:12,  1.29s/it]
 78%|███████▊  | 31/40 [00:39<00:11,  1.29s/it]
 80%|████████  | 32/40 [00:41<00:10,  1.29s/it]
 82%|████████▎ | 33/40 [00:42<00:09,  1.29s/it]
 85%|████████▌ | 34/40 [00:43<00:07,  1.29s/it]
 88%|████████▊ | 35/40 [00:45<00:06,  1.29s/it]
 90%|█████████ | 36/40 [00:46<00:05,  1.29s/it]
 92%|█████████▎| 37/40 [00:47<00:03,  1.29s/it]
 95%|█████████▌| 38/40 [00:48<00:02,  1.29s/it]
 98%|█████████▊| 39/40 [00:50<00:01,  1.29s/it]
### Phase 2 Decoding ###
100%|██████████| 40/40 [00:51<00:00,  1.29s/it]
100%|██████████| 40/40 [00:52<00:00,  1.31s/it]