Delete app.py with huggingface_hub

app.py

@@ -1,231 +0,0 @@
-import os
-import torch
-import gradio as gr
-from diffusers import StableDiffusionXLPipeline, AutoencoderKL
-from diffusers.schedulers import EulerAncestralDiscreteScheduler
-from transformers import CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
-from safetensors.torch import load_file
-import gc
-
-# ─── Config ──────────────────────────────────────────────────────────
-MODEL_ID = "NoobAI-XL/NoobAI-XL-1.1-SDNQ-UINT4"  # HF repo
-DEVICE = "cpu"
-DTYPE = torch.float32  # CPU 用 fp32 更稳
-DEFAULT_W, DEFAULT_H = 640, 960
-DEFAULT_STEPS = 20
-DEFAULT_GUIDANCE = 5.0
-
-# ─── Prompt enhancement (Chinese → English + quality tags) ───────────
-QUALITY_TAGS = (
-    "masterpiece, best quality, ultra high res, "
-    "dynamic composition, dramatic lighting, "
-    "detailed background, manga style, anime style, "
-    "sharp focus, vivid colors, professional illustration"
-)
-
-NEGATIVE_PROMPT = (
-    "low quality, worst quality, bad anatomy, bad composition, "
-    "blurry, pixelated, watermark, text, signature, logo, "
-    "ugly, deformed, noise, artifacts, lowres, error, "
-    "missing fingers, extra digits, fewer digits, cropped, "
-    "jpeg artifacts, out of frame, mutation, mutated, "
-    "extra limbs, malformed limbs, long neck, disfigured"
-)
-
-STYLE_PROMPTS = {
-    "Manga / Anime": "manga style, anime style, screentone, ink lines, dynamic panel composition",
-    "Western Comics": "western comic style, bold outlines, halftone dots, vibrant colors, dynamic action",
-    "Manhwa": "manhwa style, webtoon style, clean lines, soft shading, vertical composition",
-    "Sketch / Lineart": "sketch style, lineart, black and white, pencil drawing, detailed strokes",
-}
-
-def enhance_prompt(user_prompt: str, style: str) -> str:
-    """中文场景 → 英文提示词 + 质量标签 + 风格标签"""
-    # 简单的中文关键词映射（可扩展为更完整的翻译/扩写）
-    cn_en_map = {
-        "恐龙": "dinosaur",
-        "霸王龙": "T-Rex",
-        "暴雨": "heavy rain",
-        "史前森林": "prehistoric forest",
-        "仰头": "looking up",
-        "怒吼": "roaring",
-        "闪电": "lightning",
-        "照亮": "illuminating",
-        "天空": "sky",
-        "低角度": "low angle",
-        "镜头": "camera angle",
-        "强烈": "intense",
-        "漫画": "manga",
-        "构图": "composition",
-        "动态": "dynamic",
-        "线条": "lines",
-        "丰富": "rich",
-        "背景": "background",
-        "细节": "details",
-        "愤怒": "angry",
-        "站在": "standing in",
-        "里": "in",
-        "的": "",
-        "一只": "a",
-        "在": "in",
-        "中": "in",
-        "和": "and",
-        "与": "and",
-    }
-    # 粗略翻译：把常见中文词替换成英文
-    translated = user_prompt
-    for cn, en in cn_en_map.items():
-        translated = translated.replace(cn, en)
-    # 如果全是中文，做简单拼接；如果已经有英文，保留
-    if any('\u4e00' <= c <= '\u9fff' for c in translated):
-        # 还含有中文，简单处理
-        prompt_en = translated
-    else:
-        prompt_en = translated
-    style_tag = STYLE_PROMPTS.get(style, STYLE_PROMPTS["Manga / Anime"])
-    return f"{prompt_en}, {style_tag}, {QUALITY_TAGS}"
-
-# ─── Load pipeline (lazy, cached) ────────────────────────────────────
-_pipe = None
-
-def get_pipeline():
-    global _pipe
-    if _pipe is not None:
-        return _pipe
-
-    print("Loading NoobAI-XL SDNQ pipeline on CPU...")
-
-    # 1) VAE (单独加载，启用 slicing)
-    vae = AutoencoderKL.from_pretrained(
-        MODEL_ID,
-        subfolder="vae",
-        torch_dtype=DTYPE,
-        low_cpu_mem_usage=True,
-    )
-    vae.enable_slicing()
-    vae.enable_tiling()
-
-    # 2) Text encoders & tokenizers (SDXL 双编码器)
-    tokenizer_1 = CLIPTokenizer.from_pretrained(MODEL_ID, subfolder="tokenizer")
-    tokenizer_2 = CLIPTokenizer.from_pretrained(MODEL_ID, subfolder="tokenizer_2")
-    text_encoder_1 = CLIPTextModel.from_pretrained(
-        MODEL_ID, subfolder="text_encoder", torch_dtype=DTYPE, low_cpu_mem_usage=True
-    )
-    text_encoder_2 = CLIPTextModelWithProjection.from_pretrained(
-        MODEL_ID, subfolder="text_encoder_2", torch_dtype=DTYPE, low_cpu_mem_usage=True
-    )
-
-    # 3) Pipeline
-    pipe = StableDiffusionXLPipeline.from_pretrained(
-        MODEL_ID,
-        vae=vae,
-        text_encoder=text_encoder_1,
-        text_encoder_2=text_encoder_2,
-        tokenizer=tokenizer_1,
-        tokenizer_2=tokenizer_2,
-        scheduler=EulerAncestralDiscreteScheduler.from_pretrained(MODEL_ID, subfolder="scheduler"),
-        torch_dtype=DTYPE,
-        low_cpu_mem_usage=True,
-        variant="fp16" if DTYPE == torch.float16 else None,
-    )
-
-    # CPU 优化
-    pipe.enable_model_cpu_offload()           # 逐层卸载到 CPU
-    pipe.enable_vae_slicing()
-    pipe.enable_vae_tiling()
-    pipe.enable_attention_slicing("auto")     # 注意力切片
-    # 关闭 xformers / flash attention（CPU 不支持）
-    try:
-        pipe.disable_xformers_memory_efficient_attention()
-    except Exception:
-        pass
-
-    pipe.to(DEVICE)
-    _pipe = pipe
-    print("Pipeline ready.")
-    return pipe
-
-# ─── Generation ──────────────────────────────────────────────────────
-def generate(prompt, style, width, height, steps, guidance, progress=gr.Progress()):
-    if not prompt.strip():
-        return None, "请输入场景描述"
-
-    progress(0.1, desc="增强提示词...")
-    full_prompt = enhance_prompt(prompt, style)
-
-    progress(0.2, desc="加载模型...")
-    pipe = get_pipeline()
-
-    progress(0.4, desc="生成中（CPU 慢，请耐心等待）...")
-    with torch.inference_mode():
-        image = pipe(
-            prompt=full_prompt,
-            negative_prompt=NEGATIVE_PROMPT,
-            width=width,
-            height=height,
-            num_inference_steps=steps,
-            guidance_scale=guidance,
-            num_images_per_prompt=1,
-        ).images[0]
-
-    progress(0.9, desc="保存 PNG...")
-    # 保存到临时文件供 Gradio 返回
-    out_path = "/tmp/comic_scene.png"
-    image.save(out_path, "PNG")
-    progress(1.0, desc="完成")
-    gc.collect()
-    torch.cuda.empty_cache() if torch.cuda.is_available() else None
-    return out_path, f"✅ 生成完成\nPrompt: {full_prompt[:200]}..."
-
-# ─── Gradio UI ───────────────────────────────────────────────────────
-css = """
-#title { text-align: center; font-size: 1.5rem; font-weight: 700; margin-bottom: 0.5rem; }
-#subtitle { text-align: center; color: #666; margin-bottom: 1rem; }
-.generate-btn { background: linear-gradient(90deg, #667eea 0%, #764ba2 100%) !important; }
-"""
-
-with gr.Blocks(css=css, title="Comic Scene Generator") as demo:
-    gr.HTML('<div id="title">🎨 Comic Scene Generator</div>')
-    gr.HTML('<div id="subtitle">输入一句中文场景 → 自动扩写 → NoobAI-XL 生成漫画场景图</div>')
-
-    with gr.Row():
-        with gr.Column(scale=1):
-            prompt = gr.Textbox(
-                label="Scene",
-                placeholder="例：一只愤怒的霸王龙站在暴雨中的史前森林里仰头怒吼，闪电照亮天空，低角度镜头，强烈的漫画构图，动态线条，丰富背景细节",
-                lines=4,
-            )
-            style = gr.Dropdown(
-                label="Style",
-                choices=list(STYLE_PROMPTS.keys()),
-                value="Manga / Anime",
-            )
-            with gr.Row():
-                width = gr.Number(label="Width", value=DEFAULT_W, precision=0, minimum=320, maximum=1024, step=64)
-                height = gr.Number(label="Height", value=DEFAULT_H, precision=0, minimum=320, maximum=1536, step=64)
-            steps = gr.Slider(label="Steps", minimum=10, maximum=50, value=DEFAULT_STEPS, step=1)
-            guidance = gr.Slider(label="Guidance Scale", minimum=1.0, maximum=15.0, value=DEFAULT_GUIDANCE, step=0.5)
-            btn = gr.Button("Generate", elem_classes="generate-btn", variant="primary")
-
-        with gr.Column(scale=1):
-            output_img = gr.Image(label="生成的漫画场景", type="filepath", interactive=False)
-            status = gr.Textbox(label="Status", interactive=False)
-
-    btn.click(
-        generate,
-        inputs=[prompt, style, width, height, steps, guidance],
-        outputs=[output_img, status],
-    )
-
-    # 示例
-    gr.Examples(
-        examples=[
-            ["一只愤怒的霸王龙站在暴雨中的史前森林里仰头怒吼，闪电照亮天空，低角度镜头，强烈的漫画构图，动态线条，丰富背景细节", "Manga / Anime", 640, 960, 20, 5.0],
-            ["赛博朋克城市夜晚，霓虹灯招牌倒映在湿漉漉的街道上，孤独的少女撑着透明伞，电影感构图", "Manga / Anime", 640, 960, 20, 5.0],
-            ["古风仙侠，白衣剑仙御剑飞行穿越云海，日出金光洒在云层上，宏大壮观，工笔画风", "Manga / Anime", 640, 960, 25, 5.5],
-        ],
-        inputs=[prompt, style, width, height, steps, guidance],
-    )
-
-if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=7860, show_error=True)