| | |
| | import torch |
| | import os |
| | from huggingface_hub import HfApi |
| | from pathlib import Path |
| | from diffusers.utils import load_image |
| | from controlnet_aux import NormalBaeDetector |
| |
|
| | from diffusers import ( |
| | ControlNetModel, |
| | StableDiffusionControlNetPipeline, |
| | UniPCMultistepScheduler, |
| | ) |
| | import sys |
| |
|
| | checkpoint = sys.argv[1] |
| |
|
| | url = "https://github.com/lllyasviel/ControlNet-v1-1-nightly/raw/main/test_imgs/person-leaves.png" |
| | image = load_image(url) |
| |
|
| | prompt = "A head full of roses" |
| |
|
| |
|
| | processor = NormalBaeDetector.from_pretrained("lllyasviel/Annotators") |
| | image = processor(image) |
| |
|
| | controlnet = ControlNetModel.from_pretrained(checkpoint, torch_dtype=torch.float16) |
| | pipe = StableDiffusionControlNetPipeline.from_pretrained( |
| | "runwayml/stable-diffusion-v1-5", controlnet=controlnet, torch_dtype=torch.float16 |
| | ) |
| |
|
| | pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config) |
| | pipe.enable_model_cpu_offload() |
| |
|
| | generator = torch.manual_seed(33) |
| | out_image = pipe(prompt, num_inference_steps=20, generator=generator, image=image).images[0] |
| |
|
| | path = os.path.join(Path.home(), "images", "aa.png") |
| | out_image.save(path) |
| |
|
| | api = HfApi() |
| |
|
| | api.upload_file( |
| | path_or_fileobj=path, |
| | path_in_repo=path.split("/")[-1], |
| | repo_id="patrickvonplaten/images", |
| | repo_type="dataset", |
| | ) |
| | print("https://huggingface.co/datasets/patrickvonplaten/images/blob/main/aa.png") |
| |
|
