Prediction

Model

emaph/in-and-outpaint-union:3a23360c

739bc641dsrgj0cgzc7s09k8ar

Status

Succeeded

Source

Web

Hardware

A40

Total duration

2m 59s

Created

over 1 year ago

Webhook

–

Input

prompt: a man wearing a pink shirt, in the middle of a foggy new york, skyscrapers on the side
negative_prompt: text, watermark
image: https://replicate.delivery/pbxt/LLgbi97wIWxt0nUNa0wu9lZbSb0UjRnkX7Xijy6NNmZaTEdL/inoutin.png
mask: https://replicate.delivery/pbxt/LLgbikVFw1CPcptesJFntZIbdDTdJgT96TgSkmInPPiAwQAp/clipspace-mask-36011.png
left: 300
right: 300
top: 150
bottom: 150
steps: 20
cfg: 4
output_format: webp
output_quality: 80

{
  "bottom": 150,
  "cfg": 4,
  "image": "https://replicate.delivery/pbxt/LLgbi97wIWxt0nUNa0wu9lZbSb0UjRnkX7Xijy6NNmZaTEdL/inoutin.png",
  "left": 300,
  "mask": "https://replicate.delivery/pbxt/LLgbikVFw1CPcptesJFntZIbdDTdJgT96TgSkmInPPiAwQAp/clipspace-mask-36011.png",
  "negative_prompt": "text, watermark",
  "output_format": "webp",
  "output_quality": 80,
  "prompt": "a man wearing a pink shirt, in the middle of a foggy new york, skyscrapers on the side",
  "right": 300,
  "steps": 20,
  "top": 150
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_Unq**********************************

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 emaph/in-and-outpaint-union using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "emaph/in-and-outpaint-union:3a23360cf7a5675e7f812b477f8c6b0e02266ddc23dbebb3acfa9abd46042f69",
  {
    input: {
      bottom: 150,
      cfg: 4,
      image: "https://replicate.delivery/pbxt/LLgbi97wIWxt0nUNa0wu9lZbSb0UjRnkX7Xijy6NNmZaTEdL/inoutin.png",
      left: 300,
      mask: "https://replicate.delivery/pbxt/LLgbikVFw1CPcptesJFntZIbdDTdJgT96TgSkmInPPiAwQAp/clipspace-mask-36011.png",
      negative_prompt: "text, watermark",
      output_format: "webp",
      output_quality: 80,
      prompt: "a man wearing a pink shirt, in the middle of a foggy new york, skyscrapers on the side",
      right: 300,
      steps: 20,
      top: 150
    }
  }
);

// 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_Unq**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run emaph/in-and-outpaint-union using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "emaph/in-and-outpaint-union:3a23360cf7a5675e7f812b477f8c6b0e02266ddc23dbebb3acfa9abd46042f69",
    input={
        "bottom": 150,
        "cfg": 4,
        "image": "https://replicate.delivery/pbxt/LLgbi97wIWxt0nUNa0wu9lZbSb0UjRnkX7Xijy6NNmZaTEdL/inoutin.png",
        "left": 300,
        "mask": "https://replicate.delivery/pbxt/LLgbikVFw1CPcptesJFntZIbdDTdJgT96TgSkmInPPiAwQAp/clipspace-mask-36011.png",
        "negative_prompt": "text, watermark",
        "output_format": "webp",
        "output_quality": 80,
        "prompt": "a man wearing a pink shirt, in the middle of a foggy new york, skyscrapers on the side",
        "right": 300,
        "steps": 20,
        "top": 150
    }
)

# 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_Unq**********************************

This is your API token. Keep it to yourself.

Run emaph/in-and-outpaint-union 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": "emaph/in-and-outpaint-union:3a23360cf7a5675e7f812b477f8c6b0e02266ddc23dbebb3acfa9abd46042f69",
    "input": {
      "bottom": 150,
      "cfg": 4,
      "image": "https://replicate.delivery/pbxt/LLgbi97wIWxt0nUNa0wu9lZbSb0UjRnkX7Xijy6NNmZaTEdL/inoutin.png",
      "left": 300,
      "mask": "https://replicate.delivery/pbxt/LLgbikVFw1CPcptesJFntZIbdDTdJgT96TgSkmInPPiAwQAp/clipspace-mask-36011.png",
      "negative_prompt": "text, watermark",
      "output_format": "webp",
      "output_quality": 80,
      "prompt": "a man wearing a pink shirt, in the middle of a foggy new york, skyscrapers on the side",
      "right": 300,
      "steps": 20,
      "top": 150
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "id": "739bc641dsrgj0cgzc7s09k8ar",
  "model": "emaph/in-and-outpaint-union",
  "version": "3a23360cf7a5675e7f812b477f8c6b0e02266ddc23dbebb3acfa9abd46042f69",
  "input": {
    "bottom": 150,
    "cfg": 4,
    "image": "https://replicate.delivery/pbxt/LLgbi97wIWxt0nUNa0wu9lZbSb0UjRnkX7Xijy6NNmZaTEdL/inoutin.png",
    "left": 300,
    "mask": "https://replicate.delivery/pbxt/LLgbikVFw1CPcptesJFntZIbdDTdJgT96TgSkmInPPiAwQAp/clipspace-mask-36011.png",
    "negative_prompt": "text, watermark",
    "output_format": "webp",
    "output_quality": 80,
    "prompt": "a man wearing a pink shirt, in the middle of a foggy new york, skyscrapers on the side",
    "right": 300,
    "steps": 20,
    "top": 150
  },
  "logs": "Random seed set to: 286931823\nChecking inputs\n✅ /tmp/inputs/image.png\n✅ /tmp/inputs/mask.png\n====================================\nChecking weights\n✅ diffusion_pytorch_model_promax.safetensors exists in ComfyUI/models/controlnet\n✅ juggernautXL_v8Rundiffusion.safetensors exists in ComfyUI/models/checkpoints\n====================================\nRunning workflow\ngot prompt\nExecuting node 4, title: Load Checkpoint, class type: CheckpointLoaderSimple\nmodel_type EPS\nUsing pytorch attention in VAE\nUsing pytorch attention in VAE\nloaded straight to GPU\nRequested to load SDXL\nLoading 1 new model\nExecuting node 6, title: Positive, class type: CLIPTextEncode\nRequested to load SDXLClipModel\nLoading 1 new model\nExecuting node 7, title: Negetive, class type: CLIPTextEncode\nExecuting node 16, title: Load ControlNet Model, class type: ControlNetLoader\nExecuting node 17, title: SetUnionControlNetType, class type: SetUnionControlNetType\nExecuting node 11, title: Load Image, class type: LoadImage\nExecuting node 71, title: Load Image Mask, class type: LoadImage\nExecuting node 50, title: InvertMask, class type: InvertMask\nExecuting node 48, title: Convert Mask to Image, class type: MaskToImage\nExecuting node 54, title: ImageCompositeMasked, class type: ImageCompositeMasked\nExecuting node 75, title: Pad Image for Outpainting, class type: ImagePadForOutpaint\nExecuting node 78, title: InvertMask, class type: InvertMask\nExecuting node 77, title: Convert Mask to Image, class type: MaskToImage\nExecuting node 79, title: ImageCompositeMasked, class type: ImageCompositeMasked\nExecuting node 15, title: Apply ControlNet (Advanced), class type: ControlNetApplyAdvanced\nExecuting node 51, title: VAE Encode, class type: VAEEncode\nRequested to load AutoencoderKL\nLoading 1 new model\nRequested to load ControlNet\nLoading 1 new model\nExecuting node 3, title: KSampler, class type: KSampler\n  0%|          | 0/20 [00:00<?, ?it/s]\n  5%|▌         | 1/20 [00:00<00:12,  1.57it/s]\n 10%|█         | 2/20 [00:01<00:10,  1.68it/s]\n 15%|█▌        | 3/20 [00:01<00:09,  1.72it/s]\n 20%|██        | 4/20 [00:02<00:09,  1.74it/s]\n 25%|██▌       | 5/20 [00:02<00:08,  1.75it/s]\n 30%|███       | 6/20 [00:03<00:07,  1.75it/s]\n 35%|███▌      | 7/20 [00:04<00:07,  1.76it/s]\n 40%|████      | 8/20 [00:04<00:06,  1.76it/s]\n 45%|████▌     | 9/20 [00:05<00:06,  1.76it/s]\n 50%|█████     | 10/20 [00:05<00:05,  1.76it/s]\n 55%|█████▌    | 11/20 [00:06<00:05,  1.76it/s]\n 60%|██████    | 12/20 [00:06<00:04,  1.76it/s]\n 65%|██████▌   | 13/20 [00:07<00:03,  1.77it/s]\n 70%|███████   | 14/20 [00:07<00:03,  1.77it/s]\n 75%|███████▌  | 15/20 [00:08<00:02,  1.77it/s]\n 80%|████████  | 16/20 [00:09<00:02,  1.58it/s]\n 85%|████████▌ | 17/20 [00:09<00:01,  1.62it/s]\n 90%|█████████ | 18/20 [00:10<00:01,  1.46it/s]\n 95%|█████████▌| 19/20 [00:11<00:00,  1.41it/s]\n100%|██████████| 20/20 [00:12<00:00,  1.50it/s]\n100%|██████████| 20/20 [00:12<00:00,  1.65it/s]\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 74, title: Save Image, class type: SaveImage\nPrompt executed in 16.87 seconds\noutputs:  {'74': {'images': [{'filename': 'edited_00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nedited_00001_.png",
  "output": [
    "https://replicate.delivery/pbxt/1UGdvhFDzDZKNl6pb4Jbzaq98cRvACBesCLlH24TLIIN9imJA/edited_00001_.webp"
  ],
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2024-07-28T20:36:55.79Z",
  "started_at": "2024-07-28T20:39:34.305319Z",
  "completed_at": "2024-07-28T20:39:55.149341Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/739bc641dsrgj0cgzc7s09k8ar/cancel",
    "get": "https://api.replicate.com/v1/predictions/739bc641dsrgj0cgzc7s09k8ar",
    "web": "https://replicate.com/p/739bc641dsrgj0cgzc7s09k8ar"
  },
  "metrics": {
    "predict_time": 20.844022075,
    "total_time": 179.359341
  }
}

Generated in

20.9 seconds

Tweak it Report

Random seed set to: 286931823 Checking inputs ✅ /tmp/inputs/image.png ✅ /tmp/inputs/mask.png ==================================== Checking weights ✅ diffusion_pytorch_model_promax.safetensors exists in ComfyUI/models/controlnet ✅ juggernautXL_v8Rundiffusion.safetensors exists in ComfyUI/models/checkpoints ==================================== Running workflow got prompt Executing node 4, title: Load Checkpoint, class type: CheckpointLoaderSimple model_type EPS Using pytorch attention in VAE Using pytorch attention in VAE loaded straight to GPU Requested to load SDXL Loading 1 new model Executing node 6, title: Positive, class type: CLIPTextEncode Requested to load SDXLClipModel Loading 1 new model Executing node 7, title: Negetive, class type: CLIPTextEncode Executing node 16, title: Load ControlNet Model, class type: ControlNetLoader Executing node 17, title: SetUnionControlNetType, class type: SetUnionControlNetType Executing node 11, title: Load Image, class type: LoadImage Executing node 71, title: Load Image Mask, class type: LoadImage Executing node 50, title: InvertMask, class type: InvertMask Executing node 48, title: Convert Mask to Image, class type: MaskToImage Executing node 54, title: ImageCompositeMasked, class type: ImageCompositeMasked Executing node 75, title: Pad Image for Outpainting, class type: ImagePadForOutpaint Executing node 78, title: InvertMask, class type: InvertMask Executing node 77, title: Convert Mask to Image, class type: MaskToImage Executing node 79, title: ImageCompositeMasked, class type: ImageCompositeMasked Executing node 15, title: Apply ControlNet (Advanced), class type: ControlNetApplyAdvanced Executing node 51, title: VAE Encode, class type: VAEEncode Requested to load AutoencoderKL Loading 1 new model Requested to load ControlNet Loading 1 new model Executing node 3, title: KSampler, class type: KSampler 0%| | 0/20 [00:00<?, ?it/s] 5%|▌ | 1/20 [00:00<00:12, 1.57it/s] 10%|█ | 2/20 [00:01<00:10, 1.68it/s] 15%|█▌ | 3/20 [00:01<00:09, 1.72it/s] 20%|██ | 4/20 [00:02<00:09, 1.74it/s] 25%|██▌ | 5/20 [00:02<00:08, 1.75it/s] 30%|███ | 6/20 [00:03<00:07, 1.75it/s] 35%|███▌ | 7/20 [00:04<00:07, 1.76it/s] 40%|████ | 8/20 [00:04<00:06, 1.76it/s] 45%|████▌ | 9/20 [00:05<00:06, 1.76it/s] 50%|█████ | 10/20 [00:05<00:05, 1.76it/s] 55%|█████▌ | 11/20 [00:06<00:05, 1.76it/s] 60%|██████ | 12/20 [00:06<00:04, 1.76it/s] 65%|██████▌ | 13/20 [00:07<00:03, 1.77it/s] 70%|███████ | 14/20 [00:07<00:03, 1.77it/s] 75%|███████▌ | 15/20 [00:08<00:02, 1.77it/s] 80%|████████ | 16/20 [00:09<00:02, 1.58it/s] 85%|████████▌ | 17/20 [00:09<00:01, 1.62it/s] 90%|█████████ | 18/20 [00:10<00:01, 1.46it/s] 95%|█████████▌| 19/20 [00:11<00:00, 1.41it/s] 100%|██████████| 20/20 [00:12<00:00, 1.50it/s] 100%|██████████| 20/20 [00:12<00:00, 1.65it/s] Executing node 8, title: VAE Decode, class type: VAEDecode Executing node 74, title: Save Image, class type: SaveImage Prompt executed in 16.87 seconds outputs: {'74': {'images': [{'filename': 'edited_00001_.png', 'subfolder': '', 'type': 'output'}]}} ==================================== edited_00001_.png