File size: 814 Bytes
0f0010b 3a018f7 c78b4f8 3a018f7 c78b4f8 3a018f7 0f0010b c78b4f8 3a018f7 2de85a6 0f0010b 3a018f7 c78b4f8 0f0010b 2de85a6 fba0bc3 0f0010b 3a018f7 2de85a6 c78b4f8 0f0010b c78b4f8 0f0010b 2de85a6 c78b4f8 3a018f7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | import os
import gradio as gr
import torch
from diffusers import StableDiffusionPipeline
hf_token = os.getenv("HF_TOKEN")
# 模型ID可以根据需求更改
model_id = "runwayml/stable-diffusion-v1-5"
device = "cuda" if torch.cuda.is_available() else "cpu"
dtype = torch.float16 if device == "cuda" else torch.float32
# 加载模型
pipe = StableDiffusionPipeline.from_pretrained(
model_id,
dtype=dtype, # 使用 dtype
token=hf_token,
safety_checker=None
).to(device)
# 生成图像的回调函数
def generate_image(prompt):
image = pipe(prompt).images[0]
return image
# 设置 Gradio 界面
demo = gr.Interface(
fn=generate_image,
inputs="text", # 输入是一个文本框
outputs="image", # 输出是生成的图像
title="SD1.5 文生图 Demo"
)
demo.launch()
|