app.py

import gradio as gr
import torch
import json
from diffusers import AutoPipelineForInpainting, StableDiffusionPipeline
from PIL import Image

# ==========================
# 模型ID映射
# ==========================
MODEL_LIST = {
    "SD1.5 局部重绘": "runwayml/stable-diffusion-inpainting",
    "SD1.5 基础通用": "runwayml/stable-diffusion-v1-5",
    "游戏资产贴图专用": "Yntec/GameAsset",
    "2D手绘场景贴图": "Yaeger/Flat2D",
    "低多边形LowPoly": "NiamaOfficial/LowPolyStyle",
    "体素Voxel艺术": "VoxelArtModels/VoxelBase15",
    "唯美插画风": "andite/pastel-mix",
    "轻量二次元V3": "gsdf/Counterfeit-V3.0",
    "吉卜力手绘动画": "nitrosocke/Ghibli-Style",
    "原神二次元场景": "Linaqruf/giant-squid-ai",
    "王者荣耀国风原画": "WarriorMama777/AbyssOrangeMix2",
    "塞尔达旷野手绘风": "andite/pastel-mix",
    "复古像素艺术": "OnodoAI/PixelArtModel",
    "RPG像素场景贴图": "ZinPixel/RPGMakerTiles",
    "写实建筑场景": "XpucT/Deliberate",
    "写实环境无VAE": "SG161222/Realistic_Vision_V5.1_noVAE",
    "卡通写实融合": "lilpotat/ToonYou",
    "FastSD 极速CPU": "rupeshs/fastsdcpu",
    "BK-SDM 轻量化": "nota-ai/bk-sdm-small",
    "SD-Turbo 超快出图": "stabilityai/sd-turbo"
}

def load_prompt_presets():
    try:
        with open("prompts.json", "r", encoding="utf-8") as f:
            return json.load(f)
    except:
        return {}

PROMPT_PRESETS = load_prompt_presets()
pipe_cache = {}

def get_pipe(model_name, mode="txt2img"):
    cache_key = f"{model_name}_{mode}"
    if cache_key in pipe_cache:
        return pipe_cache[cache_key]
    model_id = MODEL_LIST[model_name]
    device = "cuda" if torch.cuda.is_available() else "cpu"
    dtype = torch.float16 if device == "cuda" else torch.float32
    if mode == "inpaint":
        pipe = AutoPipelineForInpainting.from_pretrained(
            model_id, torch_dtype=dtype, low_cpu_mem_usage=True
        ).to(device)
    else:
        pipe = StableDiffusionPipeline.from_pretrained(
            model_id, torch_dtype=dtype, low_cpu_mem_usage=True
        ).to(device)
    pipe_cache[cache_key] = pipe
    return pipe

def update_prompts(model_name):
    preset = PROMPT_PRESETS.get(model_name, {})
    return gr.update(value=preset.get("positive", "")), gr.update(value=preset.get("negative", ""))

def toggle_input_mode(mode):
    if mode == "文生图（纯文本）":
        return gr.update(visible=False), gr.update(visible=True, value="✨ 文生图模式：无需上传图片，直接使用提示词生成")
    else:
        return gr.update(visible=True), gr.update(visible=False, value="")

def update_slider_visibility(mode):
    return gr.update(visible=(mode == "图像编辑（重绘）"))

def generate_image(image_data, prompt, neg_prompt, model_name, mode, denoise_str, steps, cfg):
    try:
        device = "cuda" if torch.cuda.is_available() else "cpu"
        if mode == "文生图（纯文本）":
            pipe = get_pipe(model_name, mode="txt2img")
            output = pipe(
                prompt=prompt,
                negative_prompt=neg_prompt,
                num_inference_steps=steps,
                guidance_scale=cfg
            ).images[0]
        else:
            if not image_data or "image" not in image_data:
                return None
            img = image_data["image"].convert("RGB").resize((512, 512))
            mask = image_data["mask"].convert("L").resize((512, 512)) if image_data.get("mask") else None
            pipe = get_pipe(model_name, mode="inpaint")
            output = pipe(
                prompt=prompt,
                negative_prompt=neg_prompt,
                image=img,
                mask_image=mask,
                strength=denoise_str,
                num_inference_steps=steps,
                guidance_scale=cfg
            ).images[0]
        return output
    except Exception as e:
        print(f"生成错误: {e}")
        return None

with gr.Blocks(title="全风格AI图像工具", theme=gr.themes.Soft()) as demo:
    gr.Markdown("# 🎨 全风格AI图像生成 + 重绘工具")
    with gr.Row():
        with gr.Column(scale=1):
            mode_radio = gr.Radio(
                choices=["文生图（纯文本）", "图像编辑（重绘）"],
                label="✨ 选择生成模式",
                value="图像编辑（重绘）"
            )
            mode_hint = gr.Markdown("", visible=False)
            input_img = gr.ImageEditor(
                label="上传图片 + 涂抹重绘区域（重绘模式）",
                type="pil",
                height=420,
                visible=True
            )
            model_select = gr.Dropdown(
                label="🎮 选择风格模型",
                choices=list(MODEL_LIST.keys()),
                value="游戏资产贴图专用"
            )
            prompt = gr.Textbox(label="正向提示词（可追加修改）", lines=3)
            neg_prompt = gr.Textbox(label="反向提示词（可追加修改）", lines=2)
        with gr.Column(scale=1):
            denoise_str = gr.Slider(label="重绘强度", minimum=0.1, maximum=0.9, value=0.5, visible=True)
            steps = gr.Slider(label="采样步数", minimum=10, maximum=30, value=20)
            cfg = gr.Slider(label="提示词强度", minimum=1, maximum=15, value=7)
            generate_btn = gr.Button("✨ 一键生成", variant="primary")
            output_img = gr.Image(label="生成结果", height=420)

    mode_radio.change(toggle_input_mode, inputs=mode_radio, outputs=[input_img, mode_hint])
    mode_radio.change(update_slider_visibility, inputs=mode_radio, outputs=denoise_str)
    model_select.change(update_prompts, inputs=model_select, outputs=[prompt, neg_prompt])
    demo.load(fn=lambda: update_prompts("游戏资产贴图专用"), outputs=[prompt, neg_prompt])
    generate_btn.click(
        fn=generate_image,
        inputs=[input_img, prompt, neg_prompt, model_select, mode_radio, denoise_str, steps, cfg],
        outputs=output_img
    )

demo.launch(server_name="0.0.0.0", server_port=7860, share=True)