metadata
license: cc-by-nc-4.0
Recommended version of diffusers is 0.20.2 or 0.24.0 with torch 2.
Usage Example:
import copy
import torch
import requests
from PIL import Image
from diffusers import DiffusionPipeline, EulerAncestralDiscreteScheduler, ControlNetModel
# Load the pipeline
pipeline: DiffusionPipeline = DiffusionPipeline.from_pretrained(
"sudo-ai/zero123plus-v1.2", custom_pipeline="sudo-ai/zero123plus-pipeline",
torch_dtype=torch.float16
)
normal_pipeline = copy.copy(pipeline)
normal_pipeline.add_controlnet(ControlNetModel.from_pretrained(
"sudo-ai/controlnet-zp12-normal-gen-v1", torch_dtype=torch.float16
), conditioning_scale=1.0)
pipeline.to("cuda:0", torch.float16)
normal_pipeline.to("cuda:0", torch.float16)
# Run the pipeline
cond = Image.open(requests.get("https://d.skis.ltd/nrp/sample-data/0_cond.png", stream=True).raw)
genimg = pipeline(
cond,
prompt='', guidance_scale=4, num_inference_steps=75, width=640, height=960
).images[0]
normalimg = normal_pipeline(
cond, depth_image=genimg,
prompt='', guidance_scale=1, num_inference_steps=50, width=640, height=960
).images[0]
genimg.save("colors.png")
normalimg.save("normals.png")