app.py

import gradio as gr
from PIL import Image
import os
import spaces

# os.environ['CUDA_VISIBLE_DEVICES'] = '7'

from OmniGen import OmniGenPipeline

pipe = OmniGenPipeline.from_pretrained("shitao/tmp-preview")
pipe.to("cuda")

# 示例处理函数：生成图像
@spaces.GPU
def generate_image(text, img1, img2, img3, height, width, guidance_scale):
    input_images = [img1, img2, img3]
    # 去除 None
    input_images = [img for img in input_images if img is not None]
    if len(input_images) == 0:
        input_images = None

    output = pipe(
        prompt=text,
        input_images=input_images,
        height=height,
        width=width,
        guidance_scale=guidance_scale, 
        img_guidance_scale=1.6,
        separate_cfg_infer=True,
        use_kv_cache=False
    )
    img = output[0]
    return img

# Gradio 接口
with gr.Blocks() as demo:
    gr.Markdown("## Text + Multiple Images to Image Generator")
    
    with gr.Row():
        with gr.Column():
            # 文本输入框
            prompt_input = gr.Textbox(label="Enter your prompt", placeholder="Type your prompt here...")
            
            # 图片上传框
            image_input_1 = gr.Image(label="<img><|image_1|></img>", type="filepath")
            image_input_2 = gr.Image(label="<img><|image_2|></img>", type="filepath")
            image_input_3 = gr.Image(label="<img><|image_3|></img>", type="filepath")
            
            # 高度和宽度滑块
            height_input = gr.Slider(label="Height", minimum=256, maximum=2048, value=1024, step=16)
            width_input = gr.Slider(label="Width", minimum=256, maximum=2048, value=1024, step=16)
            
            # 引导尺度输入
            guidance_scale_input = gr.Slider(label="Guidance Scale", minimum=1.0, maximum=10.0, value=3.0, step=0.1)
            
            # 生成按钮
            generate_button = gr.Button("Generate Image")
        
        with gr.Column():
            # 输出图像框
            output_image = gr.Image(label="Output Image")

    # 按钮点击事件
    generate_button.click(
        generate_image,
        inputs=[prompt_input, image_input_1, image_input_2, image_input_3, height_input, width_input, guidance_scale_input],
        outputs=output_image
    )

# 启动应用
demo.launch()