Image-to-Image
Diffusers
text-to-image
lora
template:diffusion-lora
art
object-remover
photo-cleanser
Instructions to use prithivMLmods/PhotoCleanser-i2i with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use prithivMLmods/PhotoCleanser-i2i with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("prithivMLmods/PhotoCleanser-i2i") prompt = "[photo content], remove the embroidered pattern from the image while preserving the background and remaining elements, maintaining realism and original details." input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
Update README.md
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README.md
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widget:
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- src: images/1.jpg
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text: >-
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[photo content], remove the
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background and remaining elements, maintaining realism and original details.
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prompt: >
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[photo content], remove the
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background and remaining elements, maintaining realism and original details.
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output:
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url: images/2.webp
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base_model: black-forest-labs/FLUX.1-Kontext-dev
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widget:
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- src: images/1.jpg
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text: >-
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[photo content], remove the embroidered pattern from the image while preserving the background and remaining elements, maintaining realism and original details.
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prompt: >
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[photo content], remove the embroidered pattern from the image while preserving the background and remaining elements, maintaining realism and original details.
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output:
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url: images/2.webp
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base_model: black-forest-labs/FLUX.1-Kontext-dev
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