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Depth of Field Slider - LoRA

Prompt
Prompt
Prompt
photo of a man smiling in the forest, beard
Negative Prompt
cartoon, cgi, render, illustration, painting, drawing, bad quality, grainy, low resolution
Prompt
photo of a man smiling in the forest, beard
Negative Prompt
cartoon, cgi, render, illustration, painting, drawing, bad quality, grainy, low resolution
Prompt
photo of a woman with light brown hair, posing for a photo, centered streets of big city
Negative Prompt
hat, nude, cartoon, cgi, render, illustration, painting, drawing, bad quality, grainy, low resolution
Prompt
photo of a woman with light brown hair, posing for a photo, centered streets of big city
Negative Prompt
hat, nude, cartoon, cgi, render, illustration, painting, drawing, bad quality, grainy, low resolution

Model description

  • weight: -8.0 to 8.0 ( or way more or less )

  • positive: large DOF (sharp background)

  • negative: narrow DOF (blurry background)

UPDATE:

The original file had an sdxl meta tag that makes automatic1111 web ui only show it for sdxl. I have uploaded one with the correct meta tag. If you are having issues, download and replace the previous one with the new one and refresh your network modules.

Weight depends on starting photo, if it already has a shallow depth of field, you may need to go pretty high to remove it (10.0 to 15.0), but -5.0 to 5.0 works for most images. The image stays pretty stable even at extreme values, though it will change the composition.

Download model

Weights for this model are available in Safetensors format.

Download them in the Files & versions tab.

Use it with the 🧨 diffusers library

from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained('runwayml/stable-diffusion-v1-5', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('ostris/depth-of-field-slider-lora', weight_name='depth_of_field_slider_v1.safetensors')
image = pipeline('photo of a woman with light brown hair, posing for a photo, centered streets of big city ').images[0]

For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers

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