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Upscale Portrait Images with ControlNet Tile (Updated 1 year, 6 months ago)
Run this model in Node.js with one line of code:
npm install replicate
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import Replicate from "replicate";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run juergengunz/ultimate-portrait-upscale using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"juergengunz/ultimate-portrait-upscale:f7fdace4ec7adab7fa02688a160eee8057f070ead7fbb84e0904864fd2324be5",
{
input: {
cfg: 8,
image: "https://replicate.delivery/pbxt/K1jy8x3lgsayBRp1SwKmFoQrFGoEOvQ56VcwGIHM6giTiyPm/test.png",
steps: 20,
denoise: 0.1,
upscaler: "4x-UltraSharp",
mask_blur: 8,
mode_type: "Linear",
scheduler: "normal",
tile_width: 512,
upscale_by: 2,
tile_height: 512,
sampler_name: "euler",
tile_padding: 32,
seam_fix_mode: "None",
seam_fix_width: 64,
negative_prompt: "cartoon, cgi, render, painting, illustration, drawing",
positive_prompt: "business portrait of a man, detailed skin, perfect skin, soft lighting, beautiful blue eyes, photorealistic",
seam_fix_denoise: 1,
seam_fix_padding: 16,
seam_fix_mask_blur: 8,
controlnet_strength: 1,
force_uniform_tiles: true,
use_controlnet_tile: true
}
}
);
// To access the file URL:
console.log(output.url()); //=> "http://example.com"
// To write the file to disk:
fs.writeFile("my-image.png", output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import replicate
Run juergengunz/ultimate-portrait-upscale using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"juergengunz/ultimate-portrait-upscale:f7fdace4ec7adab7fa02688a160eee8057f070ead7fbb84e0904864fd2324be5",
input={
"cfg": 8,
"image": "https://replicate.delivery/pbxt/K1jy8x3lgsayBRp1SwKmFoQrFGoEOvQ56VcwGIHM6giTiyPm/test.png",
"steps": 20,
"denoise": 0.1,
"upscaler": "4x-UltraSharp",
"mask_blur": 8,
"mode_type": "Linear",
"scheduler": "normal",
"tile_width": 512,
"upscale_by": 2,
"tile_height": 512,
"sampler_name": "euler",
"tile_padding": 32,
"seam_fix_mode": "None",
"seam_fix_width": 64,
"negative_prompt": "cartoon, cgi, render, painting, illustration, drawing",
"positive_prompt": "business portrait of a man, detailed skin, perfect skin, soft lighting, beautiful blue eyes, photorealistic",
"seam_fix_denoise": 1,
"seam_fix_padding": 16,
"seam_fix_mask_blur": 8,
"controlnet_strength": 1,
"force_uniform_tiles": True,
"use_controlnet_tile": True
}
)
print(output)
To learn more, take a look at the guide on getting started with Python.
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run juergengunz/ultimate-portrait-upscale 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": "juergengunz/ultimate-portrait-upscale:f7fdace4ec7adab7fa02688a160eee8057f070ead7fbb84e0904864fd2324be5",
"input": {
"cfg": 8,
"image": "https://replicate.delivery/pbxt/K1jy8x3lgsayBRp1SwKmFoQrFGoEOvQ56VcwGIHM6giTiyPm/test.png",
"steps": 20,
"denoise": 0.1,
"upscaler": "4x-UltraSharp",
"mask_blur": 8,
"mode_type": "Linear",
"scheduler": "normal",
"tile_width": 512,
"upscale_by": 2,
"tile_height": 512,
"sampler_name": "euler",
"tile_padding": 32,
"seam_fix_mode": "None",
"seam_fix_width": 64,
"negative_prompt": "cartoon, cgi, render, painting, illustration, drawing",
"positive_prompt": "business portrait of a man, detailed skin, perfect skin, soft lighting, beautiful blue eyes, photorealistic",
"seam_fix_denoise": 1,
"seam_fix_padding": 16,
"seam_fix_mask_blur": 8,
"controlnet_strength": 1,
"force_uniform_tiles": true,
"use_controlnet_tile": true
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/juergengunz/ultimate-portrait-upscale@sha256:f7fdace4ec7adab7fa02688a160eee8057f070ead7fbb84e0904864fd2324be5 \
-i 'cfg=8' \
-i 'image="https://replicate.delivery/pbxt/K1jy8x3lgsayBRp1SwKmFoQrFGoEOvQ56VcwGIHM6giTiyPm/test.png"' \
-i 'steps=20' \
-i 'denoise=0.1' \
-i 'upscaler="4x-UltraSharp"' \
-i 'mask_blur=8' \
-i 'mode_type="Linear"' \
-i 'scheduler="normal"' \
-i 'tile_width=512' \
-i 'upscale_by=2' \
-i 'tile_height=512' \
-i 'sampler_name="euler"' \
-i 'tile_padding=32' \
-i 'seam_fix_mode="None"' \
-i 'seam_fix_width=64' \
-i 'negative_prompt="cartoon, cgi, render, painting, illustration, drawing"' \
-i 'positive_prompt="business portrait of a man, detailed skin, perfect skin, soft lighting, beautiful blue eyes, photorealistic"' \
-i 'seam_fix_denoise=1' \
-i 'seam_fix_padding=16' \
-i 'seam_fix_mask_blur=8' \
-i 'controlnet_strength=1' \
-i 'force_uniform_tiles=true' \
-i 'use_controlnet_tile=true'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/juergengunz/ultimate-portrait-upscale@sha256:f7fdace4ec7adab7fa02688a160eee8057f070ead7fbb84e0904864fd2324be5
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "cfg": 8, "image": "https://replicate.delivery/pbxt/K1jy8x3lgsayBRp1SwKmFoQrFGoEOvQ56VcwGIHM6giTiyPm/test.png", "steps": 20, "denoise": 0.1, "upscaler": "4x-UltraSharp", "mask_blur": 8, "mode_type": "Linear", "scheduler": "normal", "tile_width": 512, "upscale_by": 2, "tile_height": 512, "sampler_name": "euler", "tile_padding": 32, "seam_fix_mode": "None", "seam_fix_width": 64, "negative_prompt": "cartoon, cgi, render, painting, illustration, drawing", "positive_prompt": "business portrait of a man, detailed skin, perfect skin, soft lighting, beautiful blue eyes, photorealistic", "seam_fix_denoise": 1, "seam_fix_padding": 16, "seam_fix_mask_blur": 8, "controlnet_strength": 1, "force_uniform_tiles": true, "use_controlnet_tile": true } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Add a payment method to run this model.
Each run costs approximately $0.14. Alternatively, try out our featured models for free.
By signing in, you agree to our
terms of service and privacy policy
We were unable to load these images. Please make sure the URLs are valid.
{ "input": "https://replicate.delivery/pbxt/K1jy8x3lgsayBRp1SwKmFoQrFGoEOvQ56VcwGIHM6giTiyPm/test.png", "outut": "https://replicate.delivery/pbxt/EykrnMfm3RwgWiLVz5iZV39V0iBqu2MtkeuDj0GDMXFmIABSA/out-1926293.png" }
{
"completed_at": "2023-12-10T23:56:22.876546Z",
"created_at": "2023-12-10T23:56:13.187729Z",
"data_removed": false,
"error": null,
"id": "d2wp6xdboshn2nanm7hghzq6gm",
"input": {
"cfg": 8,
"image": "https://replicate.delivery/pbxt/K1jy8x3lgsayBRp1SwKmFoQrFGoEOvQ56VcwGIHM6giTiyPm/test.png",
"steps": 20,
"denoise": 0.1,
"upscaler": "4x-UltraSharp",
"mask_blur": 8,
"mode_type": "Linear",
"scheduler": "normal",
"tile_width": 512,
"upscale_by": 2,
"tile_height": 512,
"sampler_name": "euler",
"tile_padding": 32,
"seam_fix_mode": "None",
"seam_fix_width": 64,
"negative_prompt": "cartoon, cgi, render, painting, illustration, drawing",
"positive_prompt": "business portrait of a man, detailed skin, perfect skin, soft lighting, beautiful blue eyes, photorealistic",
"seam_fix_denoise": 1,
"seam_fix_padding": 16,
"seam_fix_mask_blur": 8,
"controlnet_strength": 1,
"force_uniform_tiles": true,
"use_controlnet_tile": true
},
"logs": "Using seed: 1926293\nUsing ControlNet tile with Ultimate SD Upscale\ngot prompt\nCanva size: 800x1072\nImage size: 400x533\nScale factor: 3\nUpscaling iteration 1 with scale factor 3\nTile size: 512x512\nTiles amount: 6\nGrid: 3x2\nRedraw enabled: True\nSeams fix mode: NONE\nRequested to load ControlNet\nLoading 1 new model\n 0%| | 0/20 [00:00<?, ?it/s]\n 10%|█ | 2/20 [00:00<00:00, 18.57it/s]\n 25%|██▌ | 5/20 [00:00<00:00, 19.62it/s]\n 40%|████ | 8/20 [00:00<00:00, 20.05it/s]\n 50%|█████ | 10/20 [00:00<00:00, 19.82it/s]\n 65%|██████▌ | 13/20 [00:00<00:00, 19.71it/s]\n 75%|███████▌ | 15/20 [00:00<00:00, 19.76it/s]\n 90%|█████████ | 18/20 [00:00<00:00, 20.00it/s]\n100%|██████████| 20/20 [00:01<00:00, 19.94it/s]\n100%|██████████| 20/20 [00:01<00:00, 19.83it/s]\nRequested to load ControlNet\nLoading 1 new model\nunload clone 2\n 0%| | 0/20 [00:00<?, ?it/s]\n 10%|█ | 2/20 [00:00<00:00, 19.90it/s]\n 25%|██▌ | 5/20 [00:00<00:00, 20.09it/s]\n 40%|████ | 8/20 [00:00<00:00, 20.15it/s]\n 55%|█████▌ | 11/20 [00:00<00:00, 20.27it/s]\n 70%|███████ | 14/20 [00:00<00:00, 20.35it/s]\n 85%|████████▌ | 17/20 [00:00<00:00, 19.85it/s]\n100%|██████████| 20/20 [00:00<00:00, 20.09it/s]\n100%|██████████| 20/20 [00:00<00:00, 20.11it/s]\nRequested to load ControlNet\nLoading 1 new model\nunload clone 2\n 0%| | 0/20 [00:00<?, ?it/s]\n 10%|█ | 2/20 [00:00<00:00, 19.61it/s]\n 25%|██▌ | 5/20 [00:00<00:00, 20.10it/s]\n 40%|████ | 8/20 [00:00<00:00, 20.25it/s]\n 55%|█████▌ | 11/20 [00:00<00:00, 19.64it/s]\n 70%|███████ | 14/20 [00:00<00:00, 19.94it/s]\n 85%|████████▌ | 17/20 [00:00<00:00, 20.07it/s]\n100%|██████████| 20/20 [00:00<00:00, 20.17it/s]\n100%|██████████| 20/20 [00:00<00:00, 20.05it/s]\nRequested to load ControlNet\nLoading 1 new model\nunload clone 2\n 0%| | 0/20 [00:00<?, ?it/s]\n 10%|█ | 2/20 [00:00<00:01, 17.92it/s]\n 20%|██ | 4/20 [00:00<00:00, 18.92it/s]\n 35%|███▌ | 7/20 [00:00<00:00, 19.76it/s]\n 50%|█████ | 10/20 [00:00<00:00, 19.95it/s]\n 65%|██████▌ | 13/20 [00:00<00:00, 20.15it/s]\n 80%|████████ | 16/20 [00:00<00:00, 20.17it/s]\n 95%|█████████▌| 19/20 [00:00<00:00, 20.24it/s]\n100%|██████████| 20/20 [00:01<00:00, 19.98it/s]\nRequested to load ControlNet\nLoading 1 new model\nunload clone 2\n 0%| | 0/20 [00:00<?, ?it/s]\n 10%|█ | 2/20 [00:00<00:00, 19.62it/s]\n 25%|██▌ | 5/20 [00:00<00:00, 19.91it/s]\n 40%|████ | 8/20 [00:00<00:00, 20.07it/s]\n 55%|█████▌ | 11/20 [00:00<00:00, 20.25it/s]\n 70%|███████ | 14/20 [00:00<00:00, 20.28it/s]\n 85%|████████▌ | 17/20 [00:00<00:00, 20.21it/s]\n100%|██████████| 20/20 [00:00<00:00, 20.15it/s]\n100%|██████████| 20/20 [00:00<00:00, 20.14it/s]\nRequested to load ControlNet\nLoading 1 new model\nunload clone 2\n 0%| | 0/20 [00:00<?, ?it/s]\n 10%|█ | 2/20 [00:00<00:00, 19.84it/s]\n 25%|██▌ | 5/20 [00:00<00:00, 20.24it/s]\n 40%|████ | 8/20 [00:00<00:00, 20.12it/s]\n 55%|█████▌ | 11/20 [00:00<00:00, 19.81it/s]\n 70%|███████ | 14/20 [00:00<00:00, 20.08it/s]\n 85%|████████▌ | 17/20 [00:00<00:00, 20.20it/s]\n100%|██████████| 20/20 [00:00<00:00, 20.25it/s]\n100%|██████████| 20/20 [00:00<00:00, 20.15it/s]\nPrompt executed in 8.69 seconds\nnode output: {'images': [{'filename': 'ComfyUI_00035_.png', 'subfolder': '', 'type': 'output'}]}\noutput",
"metrics": {
"predict_time": 9.670054,
"total_time": 9.688817
},
"output": "https://replicate.delivery/pbxt/EykrnMfm3RwgWiLVz5iZV39V0iBqu2MtkeuDj0GDMXFmIABSA/out-1926293.png",
"started_at": "2023-12-10T23:56:13.206492Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/d2wp6xdboshn2nanm7hghzq6gm",
"cancel": "https://api.replicate.com/v1/predictions/d2wp6xdboshn2nanm7hghzq6gm/cancel"
},
"version": "f7fdace4ec7adab7fa02688a160eee8057f070ead7fbb84e0904864fd2324be5"
}
Using seed: 1926293
Using ControlNet tile with Ultimate SD Upscale
got prompt
Canva size: 800x1072
Image size: 400x533
Scale factor: 3
Upscaling iteration 1 with scale factor 3
Tile size: 512x512
Tiles amount: 6
Grid: 3x2
Redraw enabled: True
Seams fix mode: NONE
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Prompt executed in 8.69 seconds
node output: {'images': [{'filename': 'ComfyUI_00035_.png', 'subfolder': '', 'type': 'output'}]}
output
This model costs approximately $0.14 to run on Replicate, or 7 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.
This model runs on Nvidia A100 (80GB) GPU hardware. Predictions typically complete within 98 seconds. The predict time for this model varies significantly based on the inputs.
This model doesn't have a readme.
This model is cold. You'll get a fast response if the model is warm and already running, and a slower response if the model is cold and starting up.
Choose a file from your machine
Hint: you can also drag files onto the input
Using seed: 1926293
Using ControlNet tile with Ultimate SD Upscale
got prompt
Canva size: 800x1072
Image size: 400x533
Scale factor: 3
Upscaling iteration 1 with scale factor 3
Tile size: 512x512
Tiles amount: 6
Grid: 3x2
Redraw enabled: True
Seams fix mode: NONE
Requested to load ControlNet
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node output: {'images': [{'filename': 'ComfyUI_00035_.png', 'subfolder': '', 'type': 'output'}]}
output