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emaph /in-and-outpaint-union:3a23360c
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=emaph/in-and-outpaint-union
or set up a project from scratch
npm install replicateSet the
REPLICATE_API_TOKEN environment variableexport 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 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: {
cfg: 4,
top: 150,
left: 300,
mask: "https://replicate.delivery/pbxt/LLgbikVFw1CPcptesJFntZIbdDTdJgT96TgSkmInPPiAwQAp/clipspace-mask-36011.png",
image: "https://replicate.delivery/pbxt/LLgbi97wIWxt0nUNa0wu9lZbSb0UjRnkX7Xijy6NNmZaTEdL/inoutin.png",
right: 300,
steps: 20,
bottom: 150,
prompt: "a man wearing a pink shirt, in the middle of a foggy new york, skyscrapers on the side",
output_format: "webp",
output_quality: 80,
negative_prompt: "text, watermark"
}
}
);
console.log(output);To learn more, take a look at the guide on getting started with Node.js.
pip install replicateSet the
REPLICATE_API_TOKEN environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client
import replicateRun 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={
"cfg": 4,
"top": 150,
"left": 300,
"mask": "https://replicate.delivery/pbxt/LLgbikVFw1CPcptesJFntZIbdDTdJgT96TgSkmInPPiAwQAp/clipspace-mask-36011.png",
"image": "https://replicate.delivery/pbxt/LLgbi97wIWxt0nUNa0wu9lZbSb0UjRnkX7Xijy6NNmZaTEdL/inoutin.png",
"right": 300,
"steps": 20,
"bottom": 150,
"prompt": "a man wearing a pink shirt, in the middle of a foggy new york, skyscrapers on the side",
"output_format": "webp",
"output_quality": 80,
"negative_prompt": "text, watermark"
}
)
print(output)To learn more, take a look at the guide on getting started with Python.
Set the
REPLICATE_API_TOKEN environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
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": "3a23360cf7a5675e7f812b477f8c6b0e02266ddc23dbebb3acfa9abd46042f69",
"input": {
"cfg": 4,
"top": 150,
"left": 300,
"mask": "https://replicate.delivery/pbxt/LLgbikVFw1CPcptesJFntZIbdDTdJgT96TgSkmInPPiAwQAp/clipspace-mask-36011.png",
"image": "https://replicate.delivery/pbxt/LLgbi97wIWxt0nUNa0wu9lZbSb0UjRnkX7Xijy6NNmZaTEdL/inoutin.png",
"right": 300,
"steps": 20,
"bottom": 150,
"prompt": "a man wearing a pink shirt, in the middle of a foggy new york, skyscrapers on the side",
"output_format": "webp",
"output_quality": 80,
"negative_prompt": "text, watermark"
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Install Cog
brew install cogIf you don’t have Homebrew, there are other installation options available.
Pull and run emaph/in-and-outpaint-union using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/emaph/in-and-outpaint-union@sha256:3a23360cf7a5675e7f812b477f8c6b0e02266ddc23dbebb3acfa9abd46042f69 \
-i 'cfg=4' \
-i 'top=150' \
-i 'left=300' \
-i 'mask="https://replicate.delivery/pbxt/LLgbikVFw1CPcptesJFntZIbdDTdJgT96TgSkmInPPiAwQAp/clipspace-mask-36011.png"' \
-i 'image="https://replicate.delivery/pbxt/LLgbi97wIWxt0nUNa0wu9lZbSb0UjRnkX7Xijy6NNmZaTEdL/inoutin.png"' \
-i 'right=300' \
-i 'steps=20' \
-i 'bottom=150' \
-i 'prompt="a man wearing a pink shirt, in the middle of a foggy new york, skyscrapers on the side"' \
-i 'output_format="webp"' \
-i 'output_quality=80' \
-i 'negative_prompt="text, watermark"'To learn more, take a look at the Cog documentation.
Pull and run emaph/in-and-outpaint-union 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/emaph/in-and-outpaint-union@sha256:3a23360cf7a5675e7f812b477f8c6b0e02266ddc23dbebb3acfa9abd46042f69curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "cfg": 4, "top": 150, "left": 300, "mask": "https://replicate.delivery/pbxt/LLgbikVFw1CPcptesJFntZIbdDTdJgT96TgSkmInPPiAwQAp/clipspace-mask-36011.png", "image": "https://replicate.delivery/pbxt/LLgbi97wIWxt0nUNa0wu9lZbSb0UjRnkX7Xijy6NNmZaTEdL/inoutin.png", "right": 300, "steps": 20, "bottom": 150, "prompt": "a man wearing a pink shirt, in the middle of a foggy new york, skyscrapers on the side", "output_format": "webp", "output_quality": 80, "negative_prompt": "text, watermark" } }' \ http://localhost:5000/predictions
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Output
{
"completed_at": "2024-07-28T20:39:55.149341Z",
"created_at": "2024-07-28T20:36:55.790000Z",
"data_removed": false,
"error": null,
"id": "739bc641dsrgj0cgzc7s09k8ar",
"input": {
"cfg": 4,
"top": 150,
"left": 300,
"mask": "https://replicate.delivery/pbxt/LLgbikVFw1CPcptesJFntZIbdDTdJgT96TgSkmInPPiAwQAp/clipspace-mask-36011.png",
"image": "https://replicate.delivery/pbxt/LLgbi97wIWxt0nUNa0wu9lZbSb0UjRnkX7Xijy6NNmZaTEdL/inoutin.png",
"right": 300,
"steps": 20,
"bottom": 150,
"prompt": "a man wearing a pink shirt, in the middle of a foggy new york, skyscrapers on the side",
"output_format": "webp",
"output_quality": 80,
"negative_prompt": "text, watermark"
},
"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",
"metrics": {
"predict_time": 20.844022075,
"total_time": 179.359341
},
"output": [
"https://replicate.delivery/pbxt/1UGdvhFDzDZKNl6pb4Jbzaq98cRvACBesCLlH24TLIIN9imJA/edited_00001_.webp"
],
"started_at": "2024-07-28T20:39:34.305319Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/739bc641dsrgj0cgzc7s09k8ar",
"cancel": "https://api.replicate.com/v1/predictions/739bc641dsrgj0cgzc7s09k8ar/cancel"
},
"version": "3a23360cf7a5675e7f812b477f8c6b0e02266ddc23dbebb3acfa9abd46042f69"
}Generated in
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
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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