Diffusers documentation

Text-Guided Image-to-Image Generation

You are viewing v0.14.0 version. A newer version v0.31.0 is available.
Hugging Face's logo
Join the Hugging Face community

and get access to the augmented documentation experience

to get started

Text-Guided Image-to-Image Generation

The StableDiffusionDepth2ImgPipeline lets you pass a text prompt and an initial image to condition the generation of new images as well as a depth_map to preserve the images’ structure. If no depth_map is provided, the pipeline will automatically predict the depth via an integrated depth-estimation model.

import torch
import requests
from PIL import Image

from diffusers import StableDiffusionDepth2ImgPipeline

pipe = StableDiffusionDepth2ImgPipeline.from_pretrained(
    "stabilityai/stable-diffusion-2-depth",
    torch_dtype=torch.float16,
).to("cuda")


url = "http://images.cocodataset.org/val2017/000000039769.jpg"
init_image = Image.open(requests.get(url, stream=True).raw)
prompt = "two tigers"
n_prompt = "bad, deformed, ugly, bad anatomy"
image = pipe(prompt=prompt, image=init_image, negative_prompt=n_prompt, strength=0.7).images[0]