安装anaconda环境
python
conda env create -f environment.yaml
conda activate ldm
安装依赖
python
conda install pytorch==1.12.1 torchvision==0.13.1 torchaudio==0.12.1 cudatoolkit=11.3 -c pytorch
pip install transformers==4.19.2 diffusers invisible-watermark
pip install -e .
安装xformers加速
xformers安装包
找到符合自己python,pytorch和cuda版本的xformers安装包
python
wget https://anaconda.org/xformers/xformers/0.0.16/download/linux-64/xformers-0.0.16-py39_cu11.3_pyt1.12.1.tar.bz2
conda install xformers-0.0.16-py310_cu11.3_pyt1.12.1.tar.bz2
python -m xformers.info
安装成功为下述图片
源码
下载预训练模型权重
文生图
SD2.1-v
Image Inpainting with Stable Diffusion
512-inpainting-ema.ckpt
从Hugging Face下载encoding
当我们运行scripts/txt2img.py时,会发现还需要从hugging face下载encoding,但是国内无法下载,这时候我们会科学上网,同时安装下述依赖,这样就可以下载了
python
os.environ["http_proxy"] = "http://ip:7890"
os.environ["https_proxy"] = "https://ip:7890"
pip install urllib3==1.25.11
pip install requests==2.27.1
文生图
python
python scripts/txt2img.py
--prompt
"a professional photograph of an astronaut riding a horse"
--ckpt
/devdata/chengan/stablediffusion/v2-1_768-ema-pruned.ckpt
--config
configs/stable-diffusion/v2-inference-v.yaml
--H
768
--W
768
--device
cuda
注意: --device 默认为cpu,要换成 cuda,否则报错
python
RuntimeError: expected scalar type BFloat16 but found Float
图生图
图生图使用到Gradio依赖,但是会缺少一个文件,使用下述命令补全
python
wget https://cdn-media.huggingface.co/frpc-gradio-0.2/frpc_linux_amd64
mv frpc_linux_amd64 frpc_linux_amd64_v0.2
mv frpc_linux_amd64_v0.2 /home/chengan/anaconda3/envs/llm/lib/python3.9/site-packages/gradio
chmod +x /home/chengan/anaconda3/envs/llm/lib/python3.9/site-packages/gradio/frpc_linux_amd64_v0.2
当部署项目到服务器,本地浏览器无法打开Gradio链接,修改inpainting.py文件最后一行
python
block.launch(server_name="0.0.0.0", server_port=7896, share=True)
python
python scripts/gradio/inpainting.py configs/stable-diffusion/v2-inpainting-inference.yaml /devdata/chengan/stablediffusion/512-inpainting-ema.ckpt
api
depth2image
python
pip install -U git+https://github.com/huggingface/transformers.git
pip install diffusers transformers accelerate scipy safetensors
python
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_propmt = "bad, deformed, ugly, bad anotomy"
image = pipe(prompt=prompt, image=init_image, negative_prompt=n_propmt, strength=0.7).images[0]
inpaint image
python
pipe = StableDiffusionInpaintPipeline.from_pretrained(
"stabilityai/stable-diffusion-2-inpainting",
torch_dtype=torch.float16,
)
pipe.to("cuda")
prompt = "two tigers"
# image and mask_image should be PIL images.
# The mask structure is white for inpainting and black for keeping as is
url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)
mask_image = np.ones(image.size)
img = pipe(prompt=prompt, image=image, mask_image=mask_image).images[0]
plt.imshow(img)
plt.show()