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import gradio as gr
import numpy as np
import random
import logging
import sys
import os
from PIL import Image as PILImage
# 设置日志记录
logging.basicConfig(level=logging.INFO,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
stream=sys.stdout)
logger = logging.getLogger(__name__)
# 创建一个简单的示例图像
def create_dummy_image():
logger.info("Creating dummy image")
img = PILImage.new('RGB', (256, 256), color = (255, 100, 100))
return img
# 使用小型模型减轻负担
def get_model():
try:
from diffusers import StableDiffusionPipeline
import torch
logger.info("Loading smaller model: runwayml/stable-diffusion-v1-5")
model_id = "runwayml/stable-diffusion-v1-5"
device = "cuda" if torch.cuda.is_available() else "cpu"
logger.info(f"Using device: {device}")
if torch.cuda.is_available():
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to(device)
pipe.enable_attention_slicing()
else:
pipe = StableDiffusionPipeline.from_pretrained(model_id)
pipe = pipe.to(device)
logger.info("Model loaded successfully")
return pipe
except Exception as e:
logger.error(f"Failed to load model: {e}")
return None
# 全局变量
pipe = None
# 非常简单的功能实现
def generate(prompt):
global pipe
# 如果提示为空，使用默认提示
if not prompt or prompt.strip() == "":
prompt = "a beautiful landscape"
logger.info(f"Received prompt: {prompt}")
# 第一次调用时加载模型
if pipe is None:
pipe = get_model()
# 如果模型加载失败，返回示例图像
if pipe is None:
return create_dummy_image()
try:
logger.info("Starting image generation")
# 使用最小的计算量生成图像
image = pipe(
prompt=prompt,
num_inference_steps=1,
guidance_scale=7.0,
height=256,
width=256
).images[0]
logger.info("Image generated successfully")
return image
except Exception as e:
logger.error(f"Generation failed: {e}")
return create_dummy_image()
# 极简界面
iface = gr.Interface(
fn=generate,
inputs="text",
outputs="image",
title="Simple Text-to-Image",
description="Type a prompt to generate an image.",
examples=["a cat", "mountain landscape"]
)
# 启动应用
if __name__ == "__main__":
try:
logger.info("Starting Gradio interface")
iface.launch(server_name="0.0.0.0")
except Exception as e:
logger.error(f"Failed to launch: {e}")
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