Prediction
fewjative/ultimate-sd-upscale:5daf1012d946160622cd1bd45ed8f12d9675d24659276ccfe24804035f3b3ad7ID
b6cyhgbby63wrboy5xe4t3ufii
Status
Succeeded
Source
Web
Hardware
A100 (40GB)
Total duration
Created
by @fofr
Input
- cfg
- 8
- image
- steps
- 20
- denoise
- 0.4
- upscaler
- 4x-UltraSharp
- mask_blur
- 8
- mode_type
- Linear
- scheduler
- karras
- 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
- ugly, broken, weird
- positive_prompt
- a portrait photo of a cat in a green hoodie
- seam_fix_denoise
- 1
- seam_fix_padding
- 16
- seam_fix_mask_blur
- 8
- controlnet_strength
- 1
- force_uniform_tiles
- use_controlnet_tile
{
"cfg": 8,
"image": "https://replicate.delivery/pbxt/KKOaCNy9baG5cUZfK3YvvePBqZeTxyvytifSo7pFOKLySQN2/ComfyUI_00004_.png",
"steps": 20,
"denoise": 0.4,
"upscaler": "4x-UltraSharp",
"mask_blur": 8,
"mode_type": "Linear",
"scheduler": "karras",
"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": "ugly, broken, weird",
"positive_prompt": "a portrait photo of a cat in a green hoodie",
"seam_fix_denoise": 1,
"seam_fix_padding": 16,
"seam_fix_mask_blur": 8,
"controlnet_strength": 1,
"force_uniform_tiles": true,
"use_controlnet_tile": true
}Install Replicate’s Node.js client library:
npm install replicateSet 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 fewjative/ultimate-sd-upscale using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"fewjative/ultimate-sd-upscale:5daf1012d946160622cd1bd45ed8f12d9675d24659276ccfe24804035f3b3ad7",
{
input: {
cfg: 8,
image: "https://replicate.delivery/pbxt/KKOaCNy9baG5cUZfK3YvvePBqZeTxyvytifSo7pFOKLySQN2/ComfyUI_00004_.png",
steps: 20,
denoise: 0.4,
upscaler: "4x-UltraSharp",
mask_blur: 8,
mode_type: "Linear",
scheduler: "karras",
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: "ugly, broken, weird",
positive_prompt: "a portrait photo of a cat in a green hoodie",
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.
Install Replicate’s Python client library:
pip install replicateSet 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 replicateRun fewjative/ultimate-sd-upscale using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"fewjative/ultimate-sd-upscale:5daf1012d946160622cd1bd45ed8f12d9675d24659276ccfe24804035f3b3ad7",
input={
"cfg": 8,
"image": "https://replicate.delivery/pbxt/KKOaCNy9baG5cUZfK3YvvePBqZeTxyvytifSo7pFOKLySQN2/ComfyUI_00004_.png",
"steps": 20,
"denoise": 0.4,
"upscaler": "4x-UltraSharp",
"mask_blur": 8,
"mode_type": "Linear",
"scheduler": "karras",
"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": "ugly, broken, weird",
"positive_prompt": "a portrait photo of a cat in a green hoodie",
"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.
Set the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run fewjative/ultimate-sd-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": "5daf1012d946160622cd1bd45ed8f12d9675d24659276ccfe24804035f3b3ad7",
"input": {
"cfg": 8,
"image": "https://replicate.delivery/pbxt/KKOaCNy9baG5cUZfK3YvvePBqZeTxyvytifSo7pFOKLySQN2/ComfyUI_00004_.png",
"steps": 20,
"denoise": 0.4,
"upscaler": "4x-UltraSharp",
"mask_blur": 8,
"mode_type": "Linear",
"scheduler": "karras",
"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": "ugly, broken, weird",
"positive_prompt": "a portrait photo of a cat in a green hoodie",
"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/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:
brew install cogIf 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/fewjative/ultimate-sd-upscale@sha256:5daf1012d946160622cd1bd45ed8f12d9675d24659276ccfe24804035f3b3ad7 \
-i 'cfg=8' \
-i 'image="https://replicate.delivery/pbxt/KKOaCNy9baG5cUZfK3YvvePBqZeTxyvytifSo7pFOKLySQN2/ComfyUI_00004_.png"' \
-i 'steps=20' \
-i 'denoise=0.4' \
-i 'upscaler="4x-UltraSharp"' \
-i 'mask_blur=8' \
-i 'mode_type="Linear"' \
-i 'scheduler="karras"' \
-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="ugly, broken, weird"' \
-i 'positive_prompt="a portrait photo of a cat in a green hoodie"' \
-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/fewjative/ultimate-sd-upscale@sha256:5daf1012d946160622cd1bd45ed8f12d9675d24659276ccfe24804035f3b3ad7curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "cfg": 8, "image": "https://replicate.delivery/pbxt/KKOaCNy9baG5cUZfK3YvvePBqZeTxyvytifSo7pFOKLySQN2/ComfyUI_00004_.png", "steps": 20, "denoise": 0.4, "upscaler": "4x-UltraSharp", "mask_blur": 8, "mode_type": "Linear", "scheduler": "karras", "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": "ugly, broken, weird", "positive_prompt": "a portrait photo of a cat in a green hoodie", "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.
Output
We were unable to load these images. Please make sure the URLs are valid.
{
"input": "https://replicate.delivery/pbxt/KKOaCNy9baG5cUZfK3YvvePBqZeTxyvytifSo7pFOKLySQN2/ComfyUI_00004_.png",
"outut": "https://replicate.delivery/pbxt/exJgejTPB2o58UJd7WNxWrLeenaoQSJXidu8uC2ySx0wDTJJB/out-1071452.png"
}{
"completed_at": "2024-02-01T13:18:53.221646Z",
"created_at": "2024-02-01T13:16:46.354677Z",
"data_removed": false,
"error": null,
"id": "b6cyhgbby63wrboy5xe4t3ufii",
"input": {
"cfg": 8,
"image": "https://replicate.delivery/pbxt/KKOaCNy9baG5cUZfK3YvvePBqZeTxyvytifSo7pFOKLySQN2/ComfyUI_00004_.png",
"steps": 20,
"denoise": 0.4,
"upscaler": "4x-UltraSharp",
"mask_blur": 8,
"mode_type": "Linear",
"scheduler": "karras",
"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": "ugly, broken, weird",
"positive_prompt": "a portrait photo of a cat in a green hoodie",
"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: 1071452\nUsing ControlNet tile with Ultimate SD Upscale\ngot prompt\nmodel_type EPS\nadm 0\nUsing pytorch attention in VAE\nWorking with z of shape (1, 4, 32, 32) = 4096 dimensions.\nUsing pytorch attention in VAE\nmissing {'cond_stage_model.clip_l.text_projection', 'cond_stage_model.clip_l.logit_scale'}\nleft over keys: dict_keys(['cond_stage_model.clip_l.transformer.text_model.embeddings.position_ids'])\nRequested to load SD1ClipModel\nLoading 1 new model\n/root/.pyenv/versions/3.10.6/lib/python3.10/site-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\nreturn self.fget.__get__(instance, owner)()\n[] []\nCanva size: 2048x2048\nImage size: 1024x1024\nScale factor: 2\nUpscaling iteration 1 with scale factor 2\nTile size: 512x512\nTiles amount: 16\nGrid: 4x4\nRedraw enabled: True\nSeams fix mode: NONE\nRequested to load BaseModel\nRequested to load ControlNet\nLoading 2 new models\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:07, 2.47it/s]\n 15%|█▌ | 3/20 [00:00<00:02, 6.50it/s]\n 25%|██▌ | 5/20 [00:00<00:01, 9.17it/s]\n 35%|███▌ | 7/20 [00:00<00:01, 11.13it/s]\n 45%|████▌ | 9/20 [00:00<00:00, 12.52it/s]\n 55%|█████▌ | 11/20 [00:01<00:00, 13.49it/s]\n 65%|██████▌ | 13/20 [00:01<00:00, 14.14it/s]\n 75%|███████▌ | 15/20 [00:01<00:00, 14.67it/s]\n 85%|████████▌ | 17/20 [00:01<00:00, 14.00it/s]\n 95%|█████████▌| 19/20 [00:01<00:00, 14.57it/s]\n100%|██████████| 20/20 [00:01<00:00, 12.12it/s]\nRequested to load ControlNet\nLoading 1 new 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output: {'images': [{'filename': 'ComfyUI_00007_.png', 'subfolder': '', 'type': 'output'}]}\noutput",
"metrics": {
"predict_time": 49.736541,
"total_time": 126.866969
},
"output": "https://replicate.delivery/pbxt/exJgejTPB2o58UJd7WNxWrLeenaoQSJXidu8uC2ySx0wDTJJB/out-1071452.png",
"started_at": "2024-02-01T13:18:03.485105Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/b6cyhgbby63wrboy5xe4t3ufii",
"cancel": "https://api.replicate.com/v1/predictions/b6cyhgbby63wrboy5xe4t3ufii/cancel"
},
"version": "5daf1012d946160622cd1bd45ed8f12d9675d24659276ccfe24804035f3b3ad7"
}Generated in
Using seed: 1071452
Using ControlNet tile with Ultimate SD Upscale
got prompt
model_type EPS
adm 0
Using pytorch attention in VAE
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
Using pytorch attention in VAE
missing {'cond_stage_model.clip_l.text_projection', 'cond_stage_model.clip_l.logit_scale'}
left over keys: dict_keys(['cond_stage_model.clip_l.transformer.text_model.embeddings.position_ids'])
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/root/.pyenv/versions/3.10.6/lib/python3.10/site-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()
return self.fget.__get__(instance, owner)()
[] []
Canva size: 2048x2048
Image size: 1024x1024
Scale factor: 2
Upscaling iteration 1 with scale factor 2
Tile size: 512x512
Tiles amount: 16
Grid: 4x4
Redraw enabled: True
Seams fix mode: NONE
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node output: {'images': [{'filename': 'ComfyUI_00007_.png', 'subfolder': '', 'type': 'output'}]}
output