iordcalin/material-transfer:2f640c88 – Run with an API on Replicate

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iordcalin /material-transfer:2f640c88

Playground API

Input

material_image

*file

Preview

Material to transfer to the input image

subject_image

*file

Preview

Subject image to transfer the material to

prompt

string

Shift + Return to add a new line

Use a prompt that describe the image when the material is applied

Default: "marble sculpture"

negative_prompt

string

Shift + Return to add a new line

What you do not want to see in the image

Default: ""

guidance_scale

number

(minimum: 1, maximum: 10)

Guidance scale for the diffusion process

Default: 2

steps

integer

Number of steps. 6 steps gives good results, but try increasing to 15 or 20 if you need more detail

Default: 6

max_width

integer

Max width of the output image

Default: 1920

max_height

integer

Max height of the output image

Default: 1920

material_strength

string

Strength of the material

Default: "medium"

return_intermediate_images

boolean

Return intermediate images like mask, and annotated images. Useful for debugging.

Default: false

seed

integer

Set a seed for reproducibility. Random by default.

output_format

string

Format of the output images

Default: "webp"

output_quality

integer

(minimum: 0, maximum: 100)

Quality of the output images, from 0 to 100. 100 is best quality, 0 is lowest quality.

Default: 80

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

npx create-replicate --model=iordcalin/material-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 iordcalin/material-transfer using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "iordcalin/material-transfer:2f640c887323bae445f8b5154d010b2d31c336dd5f3a1d85acd5ae04d215dea0",
  {
    input: {
      steps: 12,
      prompt: "stone sculpture, lava",
      max_width: 1920,
      max_height: 1920,
      output_format: "webp",
      subject_image: "https://replicate.delivery/pbxt/KqN31nhKDQaptRlVx3KPeBZNTJLgRVucfitwWhTScFEQ4IuA/0_3.webp",
      guidance_scale: 2,
      material_image: "https://replicate.delivery/pbxt/KqN31hxUxRUgIGgX2L0YMXblKlh5omIIW3L1rxQydEVEU5lf/8J8vDdmH.png",
      output_quality: 80,
      negative_prompt: "hair",
      material_strength: "medium",
      return_intermediate_images: false
    }
  }
);
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 iordcalin/material-transfer using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "iordcalin/material-transfer:2f640c887323bae445f8b5154d010b2d31c336dd5f3a1d85acd5ae04d215dea0",
    input={
        "steps": 12,
        "prompt": "stone sculpture, lava",
        "max_width": 1920,
        "max_height": 1920,
        "output_format": "webp",
        "subject_image": "https://replicate.delivery/pbxt/KqN31nhKDQaptRlVx3KPeBZNTJLgRVucfitwWhTScFEQ4IuA/0_3.webp",
        "guidance_scale": 2,
        "material_image": "https://replicate.delivery/pbxt/KqN31hxUxRUgIGgX2L0YMXblKlh5omIIW3L1rxQydEVEU5lf/8J8vDdmH.png",
        "output_quality": 80,
        "negative_prompt": "hair",
        "material_strength": "medium",
        "return_intermediate_images": False
    }
)
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 iordcalin/material-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": "2f640c887323bae445f8b5154d010b2d31c336dd5f3a1d85acd5ae04d215dea0",
    "input": {
      "steps": 12,
      "prompt": "stone sculpture, lava",
      "max_width": 1920,
      "max_height": 1920,
      "output_format": "webp",
      "subject_image": "https://replicate.delivery/pbxt/KqN31nhKDQaptRlVx3KPeBZNTJLgRVucfitwWhTScFEQ4IuA/0_3.webp",
      "guidance_scale": 2,
      "material_image": "https://replicate.delivery/pbxt/KqN31hxUxRUgIGgX2L0YMXblKlh5omIIW3L1rxQydEVEU5lf/8J8vDdmH.png",
      "output_quality": 80,
      "negative_prompt": "hair",
      "material_strength": "medium",
      "return_intermediate_images": false
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Install Cog

brew install cog

If you don’t have Homebrew, there are other installation options available.

Pull and run iordcalin/material-transfer using Cog (this will download the full model and run it in your local environment):

cog predict r8.im/fofr/material-transfer@sha256:2f640c887323bae445f8b5154d010b2d31c336dd5f3a1d85acd5ae04d215dea0 \
  -i 'steps=12' \
  -i 'prompt="stone sculpture, lava"' \
  -i 'max_width=1920' \
  -i 'max_height=1920' \
  -i 'output_format="webp"' \
  -i 'subject_image="https://replicate.delivery/pbxt/KqN31nhKDQaptRlVx3KPeBZNTJLgRVucfitwWhTScFEQ4IuA/0_3.webp"' \
  -i 'guidance_scale=2' \
  -i 'material_image="https://replicate.delivery/pbxt/KqN31hxUxRUgIGgX2L0YMXblKlh5omIIW3L1rxQydEVEU5lf/8J8vDdmH.png"' \
  -i 'output_quality=80' \
  -i 'negative_prompt="hair"' \
  -i 'material_strength="medium"' \
  -i 'return_intermediate_images=false'

To learn more, take a look at the Cog documentation.

Pull and run iordcalin/material-transfer using Docker (this will download the full model and run it in your local environment):

docker run -d -p 5000:5000 --gpus=all r8.im/fofr/material-transfer@sha256:2f640c887323bae445f8b5154d010b2d31c336dd5f3a1d85acd5ae04d215dea0
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "steps": 12,
      "prompt": "stone sculpture, lava",
      "max_width": 1920,
      "max_height": 1920,
      "output_format": "webp",
      "subject_image": "https://replicate.delivery/pbxt/KqN31nhKDQaptRlVx3KPeBZNTJLgRVucfitwWhTScFEQ4IuA/0_3.webp",
      "guidance_scale": 2,
      "material_image": "https://replicate.delivery/pbxt/KqN31hxUxRUgIGgX2L0YMXblKlh5omIIW3L1rxQydEVEU5lf/8J8vDdmH.png",
      "output_quality": 80,
      "negative_prompt": "hair",
      "material_strength": "medium",
      "return_intermediate_images": false
    }
  }' \
  http://localhost:5000/predictions

Output

{
  "completed_at": "2024-05-01T15:15:16.647086Z",
  "created_at": "2024-05-01T15:15:07.203000Z",
  "data_removed": false,
  "error": null,
  "id": "grve9et18drgj0cf6jws1h7ger",
  "input": {
    "steps": 12,
    "prompt": "stone sculpture, lava",
    "max_width": 1920,
    "max_height": 1920,
    "output_format": "webp",
    "subject_image": "https://replicate.delivery/pbxt/KqN31nhKDQaptRlVx3KPeBZNTJLgRVucfitwWhTScFEQ4IuA/0_3.webp",
    "guidance_scale": 2,
    "material_image": "https://replicate.delivery/pbxt/KqN31hxUxRUgIGgX2L0YMXblKlh5omIIW3L1rxQydEVEU5lf/8J8vDdmH.png",
    "output_quality": 80,
    "negative_prompt": "hair",
    "material_strength": "medium",
    "return_intermediate_images": false
  },
  "logs": "Random seed set to: 2831156950\nChecking inputs\n✅ /tmp/inputs/subject.png\n✅ /tmp/inputs/material.png\n====================================\nChecking weights\nIncluding weights for IPAdapter preset: STANDARD (medium strength)\n✅ depth_anything_vits14.pth\n✅ sk_model.pth\n✅ juggernautXL_juggernautX.safetensors\n✅ depth_anything_vitl14.pth\n✅ CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors\n✅ ip-adapter_sdxl_vit-h.safetensors\n✅ ip-adapter_sd15.safetensors\n✅ t2i-adapter_diffusers_xl_lineart.safetensors\n✅ depth_anything_vitb14.pth\n✅ t2i-adapter_diffusers_xl_depth_midas.safetensors\n✅ sk_model2.pth\n====================================\nRunning workflow\ngot prompt\nExecuting node 10, title: KSampler (Efficient), class type: KSampler (Efficient)\n  0%|          | 0/12 [00:00<?, ?it/s]\n  8%|▊         | 1/12 [00:00<00:08,  1.31it/s]\n 17%|█▋        | 2/12 [00:01<00:05,  1.74it/s]\n 25%|██▌       | 3/12 [00:01<00:04,  1.94it/s]\n 33%|███▎      | 4/12 [00:02<00:03,  2.05it/s]\n 42%|████▏     | 5/12 [00:02<00:03,  2.12it/s]\n 50%|█████     | 6/12 [00:02<00:02,  2.15it/s]\n 58%|█████▊    | 7/12 [00:03<00:02,  2.19it/s]\n 67%|██████▋   | 8/12 [00:03<00:01,  2.22it/s]\n 75%|███████▌  | 9/12 [00:04<00:01,  2.24it/s]\n 83%|████████▎ | 10/12 [00:04<00:00,  2.28it/s]\n 92%|█████████▏| 11/12 [00:05<00:00,  2.33it/s]\n100%|██████████| 12/12 [00:05<00:00,  2.77it/s]\n100%|██████████| 12/12 [00:05<00:00,  2.25it/s]\nExecuting node 9, title: Save Image, class type: SaveImage\nPrompt executed in 5.86 seconds\noutputs:  {'56': {'images': [{'filename': 'ComfyUI_temp_pgjop_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '57': {'images': [{'filename': 'ComfyUI_temp_fxoap_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '39': {'images': [{'filename': 'ComfyUI_temp_eiuhe_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '40': {'images': [{'filename': 'ComfyUI_temp_uypkg_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '58': {'images': [{'filename': 'ComfyUI_temp_npmga_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '10': {'images': [{'filename': 'ComfyUI_temp_xbbkc_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '9': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nContents of /tmp/outputs:\nComfyUI_00001_.png",
  "metrics": {
    "predict_time": 9.390225,
    "total_time": 9.444086
  },
  "output": [
    "https://replicate.delivery/pbxt/hFlz5CYcDfW5XSGXvm3RtZWFB9WE8UeGT50es3LzYhoH0BglA/ComfyUI_00001_.webp"
  ],
  "started_at": "2024-05-01T15:15:07.256861Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/grve9et18drgj0cf6jws1h7ger",
    "cancel": "https://api.replicate.com/v1/predictions/grve9et18drgj0cf6jws1h7ger/cancel"
  },
  "version": "2f640c887323bae445f8b5154d010b2d31c336dd5f3a1d85acd5ae04d215dea0"
}

Generated in

9.4 seconds

Tweak it ShareReport

Random seed set to: 2831156950
Checking inputs
✅ /tmp/inputs/subject.png
✅ /tmp/inputs/material.png
====================================
Checking weights
Including weights for IPAdapter preset: STANDARD (medium strength)
✅ depth_anything_vits14.pth
✅ sk_model.pth
✅ juggernautXL_juggernautX.safetensors
✅ depth_anything_vitl14.pth
✅ CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors
✅ ip-adapter_sdxl_vit-h.safetensors
✅ ip-adapter_sd15.safetensors
✅ t2i-adapter_diffusers_xl_lineart.safetensors
✅ depth_anything_vitb14.pth
✅ t2i-adapter_diffusers_xl_depth_midas.safetensors
✅ sk_model2.pth
====================================
Running workflow
got prompt
Executing node 10, title: KSampler (Efficient), class type: KSampler (Efficient)
  0%|          | 0/12 [00:00<?, ?it/s]
  8%|▊         | 1/12 [00:00<00:08,  1.31it/s]
 17%|█▋        | 2/12 [00:01<00:05,  1.74it/s]
 25%|██▌       | 3/12 [00:01<00:04,  1.94it/s]
 33%|███▎      | 4/12 [00:02<00:03,  2.05it/s]
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 50%|█████     | 6/12 [00:02<00:02,  2.15it/s]
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 67%|██████▋   | 8/12 [00:03<00:01,  2.22it/s]
 75%|███████▌  | 9/12 [00:04<00:01,  2.24it/s]
 83%|████████▎ | 10/12 [00:04<00:00,  2.28it/s]
 92%|█████████▏| 11/12 [00:05<00:00,  2.33it/s]
100%|██████████| 12/12 [00:05<00:00,  2.77it/s]
100%|██████████| 12/12 [00:05<00:00,  2.25it/s]
Executing node 9, title: Save Image, class type: SaveImage
Prompt executed in 5.86 seconds
outputs:  {'56': {'images': [{'filename': 'ComfyUI_temp_pgjop_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '57': {'images': [{'filename': 'ComfyUI_temp_fxoap_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '39': {'images': [{'filename': 'ComfyUI_temp_eiuhe_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '40': {'images': [{'filename': 'ComfyUI_temp_uypkg_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '58': {'images': [{'filename': 'ComfyUI_temp_npmga_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '10': {'images': [{'filename': 'ComfyUI_temp_xbbkc_00001_.png', 'subfolder': '', 'type': 'temp'}]}, '9': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}}
====================================
Contents of /tmp/outputs:
ComfyUI_00001_.png