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alpercanberk/erasedraw
erasedraw is a image-to-image model from alpercanberk. Use it when you need one image transformed into another. It is set up for diffusers. The card lists the license as mit.
These are the model weights for EraseDraw.
Downloads · 30 days
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.safetensors4.3 GB · 100%
From the Hugging Face model README
These are the model weights for EraseDraw.
<img src="https://erasedraw.cs.columbia.edu/static/img/samples_overview.png" alt="Sample Overview">To use this model, install diffusers using main for now. The API is the same as that of InstructPix2Pix
pip install diffusers accelerate safetensors transformers
import PIL
import requests
import torch
from diffusers import StableDiffusionInstructPix2PixPipeline, EulerAncestralDiscreteScheduler
model_id = "alpercanberk/erasedraw"
pipe = StableDiffusionInstructPix2PixPipeline.from_pretrained(model_id, torch_dtype=torch.float16, safety_checker=None)
pipe.to("cuda")
pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
url = "https://raw.githubusercontent.com/timothybrooks/instruct-pix2pix/main/imgs/example.jpg"
def download_image(url):
image = PIL.Image.open(requests.get(url, stream=True).raw)
image = PIL.ImageOps.exif_transpose(image)
image = image.convert("RGB")
return image
image = download_image(url)
prompt = "add sunglasses"
images = pipe(prompt, image=image, num_inference_steps=10, image_guidance_scale=1).images
images[0]
Code and data are coming soon to GitHub (find link on website) .