Closed bigmover closed 8 months ago
Hi, our models are applicable to text-guided image-to-image translation using StableDiffusionImg2ImgPipeline. Please check out the example below if you are interested.
Example from Hugging Face:
import requests import torch from PIL import Image from io import BytesIO from diffusers import StableDiffusionImg2ImgPipeline device = "cuda" # model_id_or_path = "runwayml/stable-diffusion-v1-5" # file_name = "output_sd1.5" model_id_or_path = "nota-ai/bk-sdm-base" file_name = "output_bk-sdm-base" pipe = StableDiffusionImg2ImgPipeline.from_pretrained(model_id_or_path, torch_dtype=torch.float16) pipe = pipe.to(device) url = "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/assets/stable-samples/img2img/sketch-mountains-input.jpg" response = requests.get(url) init_image = Image.open(BytesIO(response.content)).convert("RGB") init_image = init_image.resize((768, 512)) init_image.save("input.png") prompt = "A fantasy landscape, trending on artstation" images = pipe(prompt=prompt, image=init_image, strength=0.75, guidance_scale=7.5).images images[0].save(f"{file_name}.png")
Hi, our models are applicable to text-guided image-to-image translation using StableDiffusionImg2ImgPipeline. Please check out the example below if you are interested.
Example from Hugging Face: