Prediction

Model

fofr/style-transfer:f1023890

t71z6mcv6hrma0cke9xrtyzm1w

Status

Succeeded

Source

Web

Hardware

L40S

Total duration

5.9s

Created

about 1 year ago by fofr

Webhook

–

Input

style_image: https://replicate.delivery/pbxt/KlTqluRakBzt7N5mm1WExEQCc4J3usa7E3n5dhttcayTqFRm/van-gogh.jpeg
prompt: An astronaut riding a unicorn
negative_prompt: Empty string
width: 1024
height: 1024
model: fast
number_of_images: 1
structure_depth_strength: 1
structure_denoising_strength: 0.65
output_format: webp
output_quality: 80

{
  "height": 1024,
  "model": "fast",
  "negative_prompt": "",
  "number_of_images": 1,
  "output_format": "webp",
  "output_quality": 80,
  "prompt": "An astronaut riding a unicorn",
  "structure_denoising_strength": 0.65,
  "structure_depth_strength": 1,
  "style_image": "https://replicate.delivery/pbxt/KlTqluRakBzt7N5mm1WExEQCc4J3usa7E3n5dhttcayTqFRm/van-gogh.jpeg",
  "width": 1024
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_3NY**********************************

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

const output = await replicate.run(
  "fofr/style-transfer:f1023890703bc0a5a3a2c21b5e498833be5f6ef6e70e9daf6b9b3a4fd8309cf0",
  {
    input: {
      height: 1024,
      model: "fast",
      negative_prompt: "",
      number_of_images: 1,
      output_format: "webp",
      output_quality: 80,
      prompt: "An astronaut riding a unicorn",
      structure_denoising_strength: 0.65,
      structure_depth_strength: 1,
      style_image: "https://replicate.delivery/pbxt/KlTqluRakBzt7N5mm1WExEQCc4J3usa7E3n5dhttcayTqFRm/van-gogh.jpeg",
      width: 1024
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

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_3NY**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

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

output = replicate.run(
    "fofr/style-transfer:f1023890703bc0a5a3a2c21b5e498833be5f6ef6e70e9daf6b9b3a4fd8309cf0",
    input={
        "height": 1024,
        "model": "fast",
        "negative_prompt": "",
        "number_of_images": 1,
        "output_format": "webp",
        "output_quality": 80,
        "prompt": "An astronaut riding a unicorn",
        "structure_denoising_strength": 0.65,
        "structure_depth_strength": 1,
        "style_image": "https://replicate.delivery/pbxt/KlTqluRakBzt7N5mm1WExEQCc4J3usa7E3n5dhttcayTqFRm/van-gogh.jpeg",
        "width": 1024
    }
)

# To access the file URL:
print(output[0].url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output[0].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_3NY**********************************

This is your API token. Keep it to yourself.

Run fofr/style-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": "fofr/style-transfer:f1023890703bc0a5a3a2c21b5e498833be5f6ef6e70e9daf6b9b3a4fd8309cf0",
    "input": {
      "height": 1024,
      "model": "fast",
      "negative_prompt": "",
      "number_of_images": 1,
      "output_format": "webp",
      "output_quality": 80,
      "prompt": "An astronaut riding a unicorn",
      "structure_denoising_strength": 0.65,
      "structure_depth_strength": 1,
      "style_image": "https://replicate.delivery/pbxt/KlTqluRakBzt7N5mm1WExEQCc4J3usa7E3n5dhttcayTqFRm/van-gogh.jpeg",
      "width": 1024
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "id": "t71z6mcv6hrma0cke9xrtyzm1w",
  "model": "fofr/style-transfer",
  "version": "f1023890703bc0a5a3a2c21b5e498833be5f6ef6e70e9daf6b9b3a4fd8309cf0",
  "input": {
    "height": 1024,
    "model": "fast",
    "negative_prompt": "",
    "number_of_images": 1,
    "output_format": "webp",
    "output_quality": 80,
    "prompt": "An astronaut riding a unicorn",
    "structure_denoising_strength": 0.65,
    "structure_depth_strength": 1,
    "style_image": "https://replicate.delivery/pbxt/KlTqluRakBzt7N5mm1WExEQCc4J3usa7E3n5dhttcayTqFRm/van-gogh.jpeg",
    "width": 1024
  },
  "logs": "Random seed set to: 1640868803\nChecking weights\nIncluding weights for IPAdapter preset: PLUS (high strength)\n✅ ip-adapter-plus_sdxl_vit-h.safetensors\n✅ CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors\n✅ dreamshaperXL_lightningDPMSDE.safetensors\n====================================\nRunning workflow\ngot prompt\nExecuting node 2, title: Load Checkpoint, class type: CheckpointLoaderSimple\nmodel_type EPS\nUsing pytorch attention in VAE\nUsing pytorch attention in VAE\nclip missing: ['clip_l.logit_scale', 'clip_l.transformer.text_projection.weight']\nloaded straight to GPU\nRequested to load SDXL\nLoading 1 new model\nExecuting node 1, title: IPAdapter Unified Loader, class type: IPAdapterUnifiedLoader\n\u001b[33mINFO: Clip Vision model loaded from /src/ComfyUI/models/clip_vision/CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors\u001b[0m\n\u001b[33mINFO: IPAdapter model loaded from /src/ComfyUI/models/ipadapter/ip-adapter-plus_sdxl_vit-h.safetensors\u001b[0m\nExecuting node 5, title: Load Image, class type: LoadImage\n\u001b[33mINFO: the IPAdapter reference image is not a square, CLIPImageProcessor will resize and crop it at the center. If the main focus of the picture is not in the middle the result might not be what you are expecting.\u001b[0m\nExecuting node 4, title: IPAdapter, class type: IPAdapter\nRequested to load CLIPVisionModelProjection\nLoading 1 new model\nExecuting node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nRequested to load SDXLClipModel\nLoading 1 new model\nExecuting node 7, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nExecuting node 10, title: Empty Latent Image, class type: EmptyLatentImage\nExecuting node 3, title: KSampler, class type: KSampler\nRequested to load SDXL\nLoading 1 new model\n  0%|          | 0/4 [00:00<?, ?it/s]/root/.pyenv/versions/3.10.6/lib/python3.10/site-packages/torchsde/_brownian/brownian_interval.py:608: UserWarning: Should have tb<=t1 but got tb=14.614644050598145 and t1=14.614643.\nwarnings.warn(f\"Should have {tb_name}<=t1 but got {tb_name}={tb} and t1={self._end}.\")\n 25%|██▌       | 1/4 [00:00<00:01,  2.99it/s]\n 50%|█████     | 2/4 [00:00<00:00,  3.64it/s]\n 75%|███████▌  | 3/4 [00:00<00:00,  3.94it/s]\n100%|██████████| 4/4 [00:00<00:00,  5.05it/s]\n100%|██████████| 4/4 [00:00<00:00,  4.40it/s]\nRequested to load AutoencoderKL\nLoading 1 new model\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 9, title: Save Image, class type: SaveImage\nPrompt executed in 5.15 seconds\noutputs:  {'9': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nComfyUI_00001_.png",
  "output": [
    "https://replicate.delivery/xezq/OgPfUK3cTWSYF6ZKr30ItkZClxuuf3INMygNv48O47wRLg1TA/ComfyUI_00001_.webp"
  ],
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2024-11-28T11:15:23.572Z",
  "started_at": "2024-11-28T11:15:23.583714Z",
  "completed_at": "2024-11-28T11:15:29.481256Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/t71z6mcv6hrma0cke9xrtyzm1w/cancel",
    "get": "https://api.replicate.com/v1/predictions/t71z6mcv6hrma0cke9xrtyzm1w",
    "stream": "https://stream.replicate.com/v1/files/bcwr-ylw2cq4qmhgzi5wukon7sd7n2euktdfpoled6mp6tqvfknt5xnqq",
    "web": "https://replicate.com/p/t71z6mcv6hrma0cke9xrtyzm1w"
  },
  "metrics": {
    "predict_time": 5.8975421279999996,
    "total_time": 5.909256
  }
}

Generated in

5.9 seconds

Tweak it Report

Random seed set to: 1640868803 Checking weights Including weights for IPAdapter preset: PLUS (high strength) ✅ ip-adapter-plus_sdxl_vit-h.safetensors ✅ CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors ✅ dreamshaperXL_lightningDPMSDE.safetensors ==================================== Running workflow got prompt Executing node 2, title: Load Checkpoint, class type: CheckpointLoaderSimple model_type EPS Using pytorch attention in VAE Using pytorch attention in VAE clip missing: ['clip_l.logit_scale', 'clip_l.transformer.text_projection.weight'] loaded straight to GPU Requested to load SDXL Loading 1 new model Executing node 1, title: IPAdapter Unified Loader, class type: IPAdapterUnifiedLoader [33mINFO: Clip Vision model loaded from /src/ComfyUI/models/clip_vision/CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors[0m [33mINFO: IPAdapter model loaded from /src/ComfyUI/models/ipadapter/ip-adapter-plus_sdxl_vit-h.safetensors[0m Executing node 5, title: Load Image, class type: LoadImage [33mINFO: the IPAdapter reference image is not a square, CLIPImageProcessor will resize and crop it at the center. If the main focus of the picture is not in the middle the result might not be what you are expecting.[0m Executing node 4, title: IPAdapter, class type: IPAdapter Requested to load CLIPVisionModelProjection Loading 1 new model Executing node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode Requested to load SDXLClipModel Loading 1 new model Executing node 7, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode Executing node 10, title: Empty Latent Image, class type: EmptyLatentImage Executing node 3, title: KSampler, class type: KSampler Requested to load SDXL Loading 1 new model 0%| | 0/4 [00:00<?, ?it/s]/root/.pyenv/versions/3.10.6/lib/python3.10/site-packages/torchsde/_brownian/brownian_interval.py:608: UserWarning: Should have tb<=t1 but got tb=14.614644050598145 and t1=14.614643. warnings.warn(f"Should have {tb_name}<=t1 but got {tb_name}={tb} and t1={self._end}.") 25%|██▌ | 1/4 [00:00<00:01, 2.99it/s] 50%|█████ | 2/4 [00:00<00:00, 3.64it/s] 75%|███████▌ | 3/4 [00:00<00:00, 3.94it/s] 100%|██████████| 4/4 [00:00<00:00, 5.05it/s] 100%|██████████| 4/4 [00:00<00:00, 4.40it/s] Requested to load AutoencoderKL Loading 1 new model Executing node 8, title: VAE Decode, class type: VAEDecode Executing node 9, title: Save Image, class type: SaveImage Prompt executed in 5.15 seconds outputs: {'9': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}} ==================================== ComfyUI_00001_.png