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Dockerfile

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+# ---- Base (CUDA) ----
+FROM nvidia/cuda:12.1.1-devel-ubuntu22.04
+
+ENV DEBIAN_FRONTEND=noninteractive \
+    PIP_DISABLE_PIP_VERSION_CHECK=1 \
+    PYTHONUNBUFFERED=1 \
+    HF_HOME=/root/.cache/huggingface
+
+# ---- System deps ----
+RUN apt-get update && apt-get install -y \
+    python3 python3-pip python3-venv git wget curl ca-certificates \
+    libgl1 libglib2.0-0 libx11-6 libxext6 libxi6 libxrender1 libxrandr2 \
+    libxxf86vm1 libsm6 libxfixes3 xvfb xauth x11-apps \
+    ffmpeg unzip && \
+    rm -rf /var/lib/apt/lists/*
+
+# ---- Blender (headless) ----
+# 안정적인 최신 릴리스로 교체 가능: https://ftp.nluug.nl/pub/graphics/blender/release/
+ARG BLENDER_VER=4.1.1
+RUN wget -q https://download.blender.org/release/Blender${BLENDER_VER%.*}/blender-${BLENDER_VER}-linux-x64.tar.xz && \
+    tar -xJf blender-${BLENDER_VER}-linux-x64.tar.xz && \
+    mv blender-${BLENDER_VER}-linux-x64 /opt/blender && \
+    ln -s /opt/blender/blender /usr/local/bin/blender && \
+    rm blender-${BLENDER_VER}-linux-x64.tar.xz
+
+# ---- Workdir & Python deps ----
+WORKDIR /workspace
+COPY requirements.txt .
+RUN python3 -m pip install --upgrade pip && pip install -r requirements.txt
+
+# ---- App ----
+COPY . /workspace
+
+# HF Spaces: expose Gradio on $PORT
+ENV PORT=7860
+CMD ["bash", "-lc", "python3 app.py --server.port $PORT --server.address 0.0.0.0"]

README.md

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----
-title: Genshin
-emoji: 👀
-colorFrom: gray
-colorTo: yellow
-sdk: gradio
-sdk_version: 5.42.0
-app_file: app.py
-pinned: false
-license: mit
-short_description: genshin
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: Pixel→Genshin 3D (ZeroGPU)
+emoji: 🧩
+colorFrom: indigo
+colorTo: green
+sdk: gradio
+sdk_version: 5.42.0
+app_file: app.py
+pinned: false
+license: mit
+---

app.py

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+# app.py  (ZeroGPU/Gradio Space용: Blender 제외, 오토리깅 ZIP 생성 포함)
+# - 입력 PNG → 배경제거 → (체크) 무기 자동 제거 → (체크) 원신풍 리드로우
+#   → (체크) T-포즈 정렬(손가락 21점 MediaPipe로 합성 가능)
+#   → Hunyuan3D 2.1 원격 호출(GLB) → 6뷰 렌더(가능 시) → 오토리깅 번들 ZIP 생성
+# - SDK: Gradio, Space 유형: Gradio(ZeroGPU 호환)
+# - t_pose_openpose.png 기본 경로: assets/t_pose_openpose.png
+
+import os, io, json, gc, math, tempfile, zipfile, shutil, subprocess
+import numpy as np
+from PIL import Image, ImageDraw
+import gradio as gr
+
+# -------------------------------------------------------
+# 설정
+# -------------------------------------------------------
+DEFAULT_POSE_PATH = os.path.join("assets", "t_pose_openpose.png")
+HUNYUAN3D_SPACE_ID = "tencent/Hunyuan3D-2.1"  # 원격 호출
+USE_GPU = False  # ZeroGPU에서는 런타임이 알아서 GPU를 붙여줌. torch.cuda.is_available() 체크로 자동 전환.
+
+# -------------------------------------------------------
+# 유틸
+# -------------------------------------------------------
+def to_rgba(img: Image.Image) -> Image.Image:
+    return img.convert("RGBA")
+
+def save_tmp(img: Image.Image, suffix=".png"):
+    f = tempfile.NamedTemporaryFile(delete=False, suffix=suffix)
+    img.save(f.name)
+    return f.name
+
+# -------------------------------------------------------
+# 1) 배경 제거 (알파 유지)
+# -------------------------------------------------------
+from rembg import remove as rembg_remove
+def remove_bg_keep_alpha(pil_img: Image.Image) -> Image.Image:
+    arr = np.array(pil_img.convert("RGBA"))
+    out = rembg_remove(arr)
+    return Image.fromarray(out).convert("RGBA")
+
+# -------------------------------------------------------
+# 2) 무기 자동 제거: GroundingDINO + SAM + LaMa
+# -------------------------------------------------------
+import torch
+from transformers import AutoProcessor, AutoModelForObjectDetection, SamProcessor, SamModel
+from simple_lama_inpainting import SimpleLama
+
+GDINO_ID = "IDEA-Research/grounding-dino-base"
+SAM_ID   = "facebook/sam-vit-huge"
+
+_gdino_proc=_gdino=_sam_proc=_sam=_lama=None
+def _lazy_det_models():
+    global _gdino_proc,_gdino,_sam_proc,_sam,_lama
+    if _gdino_proc is None:
+        _gdino_proc = AutoProcessor.from_pretrained(GDINO_ID)
+        _gdino = AutoModelForObjectDetection.from_pretrained(GDINO_ID)
+    if _sam_proc is None:
+        _sam_proc = SamProcessor.from_pretrained(SAM_ID)
+        _sam = SamModel.from_pretrained(SAM_ID)
+    if _lama is None:
+        _lama = SimpleLama()
+
+DEFAULT_WEAPON_TERMS = [
+    "sword","greatsword","katana","dagger","knife","axe","halberd",
+    "spear","lance","polearm","staff","wand","bow","crossbow",
+    "gun","pistol","rifle","shield","hammer","mace","scythe","whip"
+]
+def load_weapon_terms():
+    p = os.path.join("assets","weapons.txt")
+    if os.path.exists(p):
+        with open(p,"r",encoding="utf-8") as f:
+            t=[x.strip() for x in f if x.strip()]
+            if t: return t
+    return DEFAULT_WEAPON_TERMS
+
+def detect_weapon_boxes(pil_img: Image.Image, query: str):
+    _lazy_det_models()
+    inputs = _gdino_proc(images=pil_img.convert("RGB"), text=query, return_tensors="pt")
+    outputs = _gdino(**inputs)
+    target_sizes = torch.tensor([pil_img.size[::-1]])
+    if hasattr(_gdino_proc,"post_process_grounded_object_detection"):
+        res = _gdino_proc.post_process_grounded_object_detection(
+            outputs, target_sizes=target_sizes, box_threshold=0.25, text_threshold=0.25
+        )[0]
+        return res["boxes"]
+    if hasattr(_gdino_proc,"post_process_object_detection"):
+        res = _gdino_proc.post_process_object_detection(
+            outputs, threshold=0.25, target_sizes=target_sizes
+        )[0]
+        return res["boxes"]
+    return None
+
+def mask_from_boxes_with_sam(pil_img: Image.Image, boxes_xyxy: torch.Tensor):
+    _lazy_det_models()
+    image = np.array(pil_img.convert("RGB"))
+    inputs = _sam_proc(images=image, input_boxes=[boxes_xyxy], return_tensors="pt")
+    with torch.no_grad():
+        outputs = _sam(**inputs)
+    masks = _sam_proc.post_process_masks(
+        outputs.pred_masks, inputs["original_sizes"], inputs["reshaped_input_sizes"]
+    )[0]
+    m = masks.squeeze(1).sum(dim=0).clamp(0,1).cpu().numpy().astype(np.uint8)*255
+    return Image.fromarray(m, mode="L")
+
+def inpaint_lama(pil_img: Image.Image, mask_img: Image.Image) -> Image.Image:
+    with tempfile.TemporaryDirectory() as td:
+        ip = os.path.join(td,"in.png"); mp = os.path.join(td,"m.png"); op = os.path.join(td,"out.png")
+        pil_img.convert("RGB").save(ip); mask_img.convert("L").save(mp)
+        _lama(ip, mp, op); out = Image.open(op).convert("RGBA")
+    base = pil_img.copy()
+    final_rgb = Image.composite(out.convert("RGB"), base.convert("RGB"), mask_img.convert("L"))
+    final_rgba = final_rgb.convert("RGBA"); final_rgba.putalpha(pil_img.split()[-1])
+    return final_rgba
+
+def auto_remove_weapons(pil_img: Image.Image) -> Image.Image:
+    boxes = detect_weapon_boxes(pil_img, ", ".join(load_weapon_terms()))
+    if boxes is None or (hasattr(boxes,"shape") and boxes.shape[0]==0): return pil_img
+    mask = mask_from_boxes_with_sam(pil_img, boxes)
+    if np.array(mask).max()==0: return pil_img
+    return inpaint_lama(pil_img, mask)
+
+# -------------------------------------------------------
+# 3) 원신풍 리드로우 (픽셀감 제거) : SD1.5 + ControlNet Canny
+# -------------------------------------------------------
+from diffusers import StableDiffusionControlNetImg2ImgPipeline, ControlNetModel
+import cv2
+
+CN_CANNY_ID = "lllyasviel/control_v11p_sd15_canny"
+SD15_ID     = "runwayml/stable-diffusion-v1-5"
+
+_cn_canny=_img2img=None
+def _lazy_redraw():
+    global _cn_canny,_img2img
+    if _cn_canny is None:
+        _cn_canny = ControlNetModel.from_pretrained(CN_CANNY_ID, torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32)
+    if _img2img is None:
+        _img2img = StableDiffusionControlNetImg2ImgPipeline.from_pretrained(
+            SD15_ID, controlnet=_cn_canny, torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32
+        )
+        if torch.cuda.is_available():
+            _img2img.enable_xformers_memory_efficient_attention()
+            _img2img.to("cuda")
+
+PROMPT = ("masterpiece, best quality, clean lineart, anime style, genshin impact style, "
+          "flat color with soft shading, detailed costume, symmetrical, full body")
+NEG    = ("low quality, worst quality, jpeg artifacts, extra limbs, deformed, "
+          "pixelated, mosaic, noisy, text, watermark, logo")
+
+def canny_map(pil):
+    rgb = np.array(pil.convert("RGB"))
+    edges = cv2.Canny(rgb, 100, 200)
+    return Image.fromarray(edges).convert("RGB")
+
+def redraw_to_clean_anime(pil_img: Image.Image, strength=0.55, scale=6.5, steps=24) -> Image.Image:
+    _lazy_redraw()
+    cn = canny_map(pil_img)
+    res = _img2img(
+        prompt=PROMPT, negative_prompt=NEG,
+        image=pil_img.convert("RGB"), control_image=cn,
+        num_inference_steps=steps, strength=strength, guidance_scale=scale,
+    )
+    out = res.images[0].convert("RGBA")
+    out.putalpha(pil_img.split()[-1])
+    return out
+
+# -------------------------------------------------------
+# 4) T-포즈 정렬(옵션) : OpenPose ControlNet + MediaPipe Hands(정확한 21점 합성)
+# -------------------------------------------------------
+from diffusers import StableDiffusionControlNetPipeline, ControlNetModel as CModel2
+import mediapipe as mp
+
+CONTROLNET_POSE = "lllyasviel/control_v11p_sd15_openpose"
+_sd_pose=_cn_pose=None
+
+_mp_hands = mp.solutions.hands.Hands(
+    static_image_mode=True,
+    max_num_hands=2,
+    model_complexity=1,
+    min_detection_confidence=0.3,
+    min_tracking_confidence=0.3
+)
+
+HAND_COL = {
+    "thumb":  (255,105,180),
+    "index":  (  0,191,255),
+    "middle": ( 50,205, 50),
+    "ring":   (255,140,  0),
+    "little": (186, 85,211),
+}
+FINGERS = {
+    "thumb":  [0,1,2,3,4],
+    "index":  [0,5,6,7,8],
+    "middle": [0,9,10,11,12],
+    "ring":   [0,13,14,15,16],
+    "little": [0,17,18,19,20],
+}
+
+def _lazy_pose():
+    global _sd_pose,_cn_pose
+    if _cn_pose is None:
+        _cn_pose = CModel2.from_pretrained(CONTROLNET_POSE, torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32)
+    if _sd_pose is None:
+        _sd_pose = StableDiffusionControlNetPipeline.from_pretrained(
+            SD15_ID, controlnet=_cn_pose, torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32
+        )
+        if torch.cuda.is_available():
+            _sd_pose.enable_xformers_memory_efficient_attention()
+            _sd_pose.to("cuda")
+
+def detect_hands_xy(pil_img: Image.Image):
+    img_rgb = np.array(pil_img.convert("RGB"))
+    h, w, _ = img_rgb.shape
+    res = _mp_hands.process(img_rgb)
+    hands = []
+    if res.multi_hand_landmarks:
+        for lm, handed in zip(res.multi_hand_landmarks, res.multi_handedness):
+            pts = []
+            for p in lm.landmark:
+                pts.append([p.x*w, p.y*h])
+            pts = np.array(pts, dtype=np.float32)  # (21,2)
+            handedness = handed.classification[0].label.lower()  # 'left' or 'right'
+            hands.append((pts, handedness))
+    return hands
+
+def _angle(p0, p1):
+    return math.atan2(p1[1]-p0[1], p1[0]-p0[0] + 1e-8)
+
+def place_hand_on_pose(canvas: Image.Image, src_pts: np.ndarray, target_wrist_xy, facing_hint: str=None, scale_px=110):
+    draw = ImageDraw.Draw(canvas)
+    wrist = src_pts[0]
+    up_vec = src_pts[9] - wrist
+    theta = _angle([0,0], up_vec)
+    R = np.array([[math.cos(-theta-math.pi/2), -math.sin(-theta-math.pi/2)],
+                  [math.sin(-theta-math.pi/2),  math.cos(-theta-math.pi/2)]], dtype=np.float32)
+    norm = (src_pts - wrist) @ R.T
+    thumb_dir = norm[2][0]
+    sx = 1.0
+    if facing_hint == "left":
+        sx = -1.0
+    elif facing_hint == "right":
+        sx = 1.0
+    else:
+        sx = 1.0 if thumb_dir > 0 else -1.0
+    norm[:,0] *= sx
+    size_ref = np.linalg.norm(norm[12] - np.array([0,0],dtype=np.float32)) + 1e-6
+    s = scale_px / size_ref
+    norm *= s
+    placed = norm + np.array(target_wrist_xy, dtype=np.float32)
+
+    r = 3
+    for name, idxs in FINGERS.items():
+        col = HAND_COL[name]
+        last = None
+        for k in idxs:
+            x,y = placed[k]
+            draw.ellipse((x-r,y-r,x+r,y+r), fill=col)
+            if last is not None:
+                draw.line((last[0],last[1],x,y), fill=col, width=3)
+            last = (x,y)
+
+def estimate_wrist_xy_from_map(posemap_rgb: Image.Image):
+    W,H = posemap_rgb.size
+    y = int(H*0.33)
+    left = (int(W*0.20), y)
+    right = (int(W*0.80), y)
+    return left, right
+
+def build_pose_control_image(base_pose_png: Image.Image,
+                             input_image_for_hands: Image.Image,
+                             add_hands_with_mediapipe=True):
+    pose = base_pose_png.convert("RGB").copy()
+    if not add_hands_with_mediapipe:
+        return pose
+    lw, rw = estimate_wrist_xy_from_map(pose)
+    hands = detect_hands_xy(input_image_for_hands)
+    if not hands:
+        return pose
+    W,_ = input_image_for_hands.size
+    for pts, handed in hands:
+        cx = pts[:,0].mean()
+        if cx < W/2:
+            place_hand_on_pose(pose, pts, lw, facing_hint="left")
+        else:
+            place_hand_on_pose(pose, pts, rw, facing_hint="right")
+    return pose
+
+def force_tpose(pil_img: Image.Image, pose_control_img: Image.Image, strength=0.25, scale=5.0) -> Image.Image:
+    _lazy_pose()
+    r = _sd_pose(
+        prompt="", image=pil_img.convert("RGB"), control_image=pose_control_img,
+        num_inference_steps=20, strength=strength, guidance_scale=scale
+    )
+    out = r.images[0].convert("RGBA"); out.putalpha(pil_img.split()[-1])
+    return out
+
+# -------------------------------------------------------
+# 5) Hunyuan3D 2.1 호출 (원격 Space)
+# -------------------------------------------------------
+from gradio_client import Client, handle_file
+
+def run_hunyuan3d(pil_rgba: Image.Image) -> str:
+    client = Client(HUNYUAN3D_SPACE_ID, hf_token=os.environ.get("HF_TOKEN"))
+    apis = client.view_api(all_endpoints=True)
+    api = apis[0]["api_name"] if apis else "/predict"
+    path = save_tmp(pil_rgba, ".png")
+    r = client.predict(image=handle_file(path), api_name=api)
+    def pick(x):
+        if isinstance(x,str) and x.lower().endswith(".glb"): return x
+        if hasattr(x,"name") and str(x.name).lower().endswith(".glb"): return x.name
+    if isinstance(r,(list,tuple)):
+        for it in r:
+            g = pick(it)
+            if g: return g
+    g = pick(r)
+    if g: return g
+    raise gr.Error("Hunyuan3D GLB 결과를 찾지 못했습니다.")
+
+# -------------------------------------------------------
+# 6) 6뷰 렌더 (가능 시: pyrender/OSMesa 필요)
+# -------------------------------------------------------
+def sixview_render(glb_path: str, size=1024):
+    try:
+        import trimesh, pyrender
+        scene_or_mesh = trimesh.load(glb_path, force='scene')
+        if isinstance(scene_or_mesh, trimesh.Scene):
+            geos=[g for g in scene_or_mesh.geometry.values() if isinstance(g,trimesh.Trimesh)]
+            mesh = trimesh.util.concatenate(geos) if geos else scene_or_mesh.dump().sum()
+        else:
+            mesh = scene_or_mesh
+        scene = pyrender.Scene(ambient_light=[.6,.6,.6,1], bg_color=[0,0,0,0])
+        mnode = scene.add(pyrender.Mesh.from_trimesh(mesh, smooth=False))
+        cam = pyrender.OrthographicCamera(xmag=1, ymag=1, znear=0.01, zfar=1000)
+        cnode = scene.add(cam, pose=np.eye(4))
+        lnode = scene.add(pyrender.DirectionalLight(intensity=3.0), pose=np.eye(4))
+        bbox=mesh.bounds; size3=(bbox[1]-bbox[0]); scale=float(np.max(size3))
+        views=[("front",(0,0)),("left",(90,0)),("right",(-90,0)),("back",(180,0)),("top",(0,90)),("bottom",(0,-90))]
+        def pose(yaw,pitch,dist):
+            y=math.radians(yaw); p=math.radians(pitch)
+            x=dist*math.cos(p)*math.cos(y); yy=dist*math.sin(p); z=dist*math.cos(p)*math.sin(y)
+            eye=np.array([x,yy,z]); at=np.array([0,0,0]); up=np.array([0,1,0])
+            f=(at-eye); f=f/np.linalg.norm(f); s=np.cross(f,up); s=s/np.linalg.norm(s); u=np.cross(s,f)
+            M=np.eye(4); M[:3,0]=s; M[:3,1]=u; M[:3,2]=-f; M[:3,3]=eye; return M
+        r=pyrender.OffscreenRenderer(size,size); imgs=[]
+        dist=scale*2.0+1e-6
+        for _,(yaw,pitch) in views:
+            scene.set_pose(cnode, pose=pose(yaw,pitch,dist))
+            scene.set_pose(lnode, pose=pose(yaw,pitch,dist))
+            color,_=r.render(scene, flags=pyrender.RenderFlags.RGBA)
+            imgs.append(Image.fromarray(color).convert("RGBA"))
+        r.delete()
+        return imgs
+    except Exception as e:
+        print("[WARN] sixview_render skipped:", e)
+        return []
+
+# -------------------------------------------------------
+# 7) 오토리깅 번들 ZIP 생성 (Blender는 포함하지 않음)
+# -------------------------------------------------------
+AUTORIG_SCRIPT = r'''<AUTORIG_PIPELINE_PY_PLACEHOLDER>'''
+# 위 자리에는 이전에 제공한 blender/autorig_pipeline.py 전체본을 그대로 붙여 넣으세요.
+# (메시지 길이 제약상 플레이스홀더 처리)
+
+RUN_SH = r'''#!/usr/bin/env bash
+BLENDER=${BLENDER:-blender}
+IN=${1:-model.glb}
+OUT=${2:-rigged_toon.fbx}
+$BLENDER -b --python blender/autorig_pipeline.py -- \
+  --in "$IN" --out "$OUT" --export fbx \
+  --outline --toon --surface_deform --limit_cloth_bones --try_faceit
+'''
+RUN_BAT = r'''@echo off
+set BLENDER=blender
+set IN=%1
+if "%IN%"=="" set IN=model.glb
+set OUT=%2
+if "%OUT%"=="" set OUT=rigged_toon.fbx
+%BLENDER% -b --python blender\autorig_pipeline.py -- ^
+  --in "%IN%" --out "%OUT%" --export fbx ^
+  --outline --toon --surface_deform --limit_cloth_bones --try_faceit
+'''
+README_AUTORIG = r'''자동 리깅 번들 사용법
+1) Blender 설치(4.x 권장)
+2) 터미널(또는 더블클릭)로 다음 실행
+   - Linux/Mac:  ./run_blender_local.sh  model.glb  rigged_toon.fbx
+   - Windows:    run_blender_local.bat  model.glb  rigged_toon.fbx
+3) 완료되면 rigged_toon.fbx(또는 glb)이 생성됩니다.
+* 의복은 Surface Deform 기반으로 바디를 추종(본 가중치 최소화), Toon/Outline 적용, 표정키(플레이스홀더) 생성.
+'''
+
+def make_autorig_bundle(glb_path: str) -> str:
+    out_dir = tempfile.mkdtemp()
+    # 디렉토리 구성
+    os.makedirs(os.path.join(out_dir,"blender"), exist_ok=True)
+    # 파일 쓰기
+    with open(os.path.join(out_dir,"blender","autorig_pipeline.py"),"w",encoding="utf-8") as f:
+        f.write(AUTORIG_SCRIPT)
+    with open(os.path.join(out_dir,"run_blender_local.sh"),"w",encoding="utf-8") as f:
+        f.write(RUN_SH)
+    os.chmod(os.path.join(out_dir,"run_blender_local.sh"), 0o755)
+    with open(os.path.join(out_dir,"run_blender_local.bat"),"w",encoding="utf-8") as f:
+        f.write(RUN_BAT)
+    with open(os.path.join(out_dir,"README_AUTORIG.txt"),"w",encoding="utf-8") as f:
+        f.write(README_AUTORIG)
+    # GLB 포함
+    shutil.copy2(glb_path, os.path.join(out_dir,"model.glb"))
+    # ZIP으로 묶기
+    zipf=os.path.join(out_dir,"autorig_bundle.zip")
+    with zipfile.ZipFile(zipf,"w",zipfile.ZIP_DEFLATED) as z:
+        for root,_,files in os.walk(out_dir):
+            for name in files:
+                if name.endswith(".zip"): continue
+                full=os.path.join(root,name)
+                arc=os.path.relpath(full, out_dir)
+                z.write(full, arcname=arc)
+    return zipf
+
+# -------------------------------------------------------
+# 8) 파이프라인
+# -------------------------------------------------------
+def pipeline(image, has_weapon: bool, do_redraw: bool,
+             force_pose: bool, add_hand_details: bool,
+             user_pose_map):
+    if image is None:
+        return None, None, [], None, None
+
+    img=image.convert("RGBA")
+
+    # a) 배경제거
+    clean=remove_bg_keep_alpha(img)
+
+    # b) 무기 자동 제거
+    if has_weapon:
+        try: clean=auto_remove_weapons(clean)
+        except Exception as e: print("[WARN] weapon removal:", e)
+
+    # c) 원신풍 리드로우
+    if do_redraw:
+        try: clean=redraw_to_clean_anime(clean, strength=0.55, scale=6.5, steps=24)
+        except Exception as e: print("[WARN] redraw:", e)
+
+    # d) T-포즈 컨트롤맵 생성(+손 디테일)
+    pose_src = user_pose_map or (Image.open(DEFAULT_POSE_PATH).convert("RGB") if os.path.exists(DEFAULT_POSE_PATH) else None)
+    if force_pose and pose_src is not None:
+        try:
+            pose_control = build_pose_control_image(
+                base_pose_png=pose_src,
+                input_image_for_hands=clean,
+                add_hands_with_mediapipe=add_hand_details
+            )
+            clean = force_tpose(clean, pose_control, strength=0.25, scale=5.0)
+        except Exception as e:
+            print("[WARN] tpose:", e)
+
+    # e) Hunyuan3D → GLB
+    glb_path=run_hunyuan3d(clean)
+
+    # f) 6뷰 (환경에 따라 생략될 수 있음)
+    views=sixview_render(glb_path, size=1024)
+
+    # g) 오토리깅 번들 ZIP (Blender는 포함 안 함)
+    zip_path = make_autorig_bundle(glb_path)
+
+    return clean, glb_path, views, zip_path, pose_src
+
+# -------------------------------------------------------
+# 9) UI
+# -------------------------------------------------------
+with gr.Blocks() as demo:
+    gr.Markdown("### Pixel→(BG/Weapon)→Clean Anime Redraw→(OpenPose+Hands)→Hunyuan3D→6View→AutoRig ZIP (ZeroGPU)")
+    with gr.Row():
+        inp=gr.Image(type="pil", label="입력 이미지 (PNG, 알파 가능)")
+        with gr.Column():
+            c1=gr.Checkbox(label="자동 무기 제거 (GroundingDINO + SAM + LaMa)", value=True)
+            c2=gr.Checkbox(label="원신풍 리드로우 (픽셀감 제거)", value=True)
+            c3=gr.Checkbox(label="T-포즈 강제 (OpenPose ControlNet)", value=True)
+            c4=gr.Checkbox(label="손가락 디테일 자동 추가 (MediaPipe 21점)", value=True)
+            pose_upload = gr.Image(type="pil", label="T-포즈 OpenPose 맵 (선택, 미제공이면 assets/t_pose_openpose.png 사용)")
+            btn=gr.Button("실행", variant="primary")
+    out_clean=gr.Image(label="전처리/리드로우/T-포즈 결과(알파)")
+    out_glb=gr.File(label="3D 모델 (GLB, Hunyuan3D)")
+    out_views=gr.Gallery(label="6뷰(정/좌/우/후/상/하, 투명)", columns=3)
+    out_zip=gr.File(label="AutoRig 번들 ZIP (Blender 스크립트/런처 + model.glb)")
+    out_pose=gr.Image(label="사용된 T-포즈 컨트롤맵(미리보기)", visible=True)
+
+    btn.click(pipeline, [inp,c1,c2,c3,c4,pose_upload],
+              [out_clean,out_glb,out_views,out_zip,out_pose])
+
+if __name__=="__main__":
+    demo.launch()

assets/weapons.txt

@@ -0,0 +1,20 @@
+sword
+greatsword
+katana
+dagger
+knife
+dual blades
+axe
+halberd
+spear
+lance
+polearm
+staff
+wand
+bow
+crossbow
+gun
+pistol
+rifle
+shield
+hammer

blender/autorig_pipeline.py

@@ -0,0 +1,360 @@
+# blender/autorig_pipeline.py
+# 헤드리스(배치) 사용 예:
+# blender -b --python blender/autorig_pipeline.py -- \
+#   --in model.glb --out rigged_toon.fbx --export fbx \
+#   --outline --toon --surface_deform --limit_cloth_bones --try_faceit
+#
+# 기능 요약:
+# 1) GLB/GLTF/FBX/OBJ 불러오기
+# 2) Body/의복/헤어/소품 대략 분류
+# 3) 휴머노이드 Armature(T-포즈) 자동 생성 + Body 자동 가중치
+# 4) 의복: Surface Deform 또는 본 영향 축소
+# 5) Toon 머티리얼 + 인버티드 헐(Outline) 적용
+# 6) 표정: Faceit 감지 시 안내, 없으면 기본 Shape Key 플레이스홀더 생성
+# 7) FBX 또는 GLB 내보내기
+
+import bpy, sys, os, math, argparse
+from mathutils import Vector, Matrix
+
+# -----------------------
+# CLI args
+# -----------------------
+def parse_args():
+    argv = sys.argv
+    if "--" in argv:
+        argv = argv[argv.index("--") + 1:]
+    else:
+        argv = []
+    p = argparse.ArgumentParser()
+    p.add_argument("--in",  dest="inp", required=True,  help="입력 경로 (GLB/GLTF/FBX/OBJ)")
+    p.add_argument("--out", dest="out", required=True,  help="출력 파일 경로")
+    p.add_argument("--export", choices=["fbx", "glb"], default="fbx", help="내보내기 포맷")
+    p.add_argument("--outline", action="store_true", help="인버티드 헐 외곽선 생성")
+    p.add_argument("--toon", action="store_true", help="Toon 셰이딩 적용")
+    p.add_argument("--surface_deform", action="store_true", help="의복 Surface Deform 바인딩")
+    p.add_argument("--limit_cloth_bones", action="store_true", help="의복 Armature 본 영향 축소(간이)")
+    p.add_argument("--try_faceit", action="store_true", help="설치 시 Faceit 활용 안내")
+    p.add_argument("--scale", type=float, default=1.0, help="전체 스케일")
+    return p.parse_args()
+
+args = parse_args()
+inp_path  = bpy.path.abspath(args.inp)
+out_path  = bpy.path.abspath(args.out)
+export_fmt = args.export
+
+# -----------------------
+# 초기화
+# -----------------------
+for obj in list(bpy.data.objects):
+    obj.select_set(False)
+
+# -----------------------
+# Import model
+# -----------------------
+ext = os.path.splitext(inp_path)[1].lower()
+if ext in [".glb", ".gltf"]:
+    bpy.ops.import_scene.gltf(filepath=inp_path)
+elif ext in [".fbx"]:
+    bpy.ops.import_scene.fbx(filepath=inp_path)
+elif ext in [".obj"]:
+    bpy.ops.import_scene.obj(filepath=inp_path)
+else:
+    raise RuntimeError("지원하지 않는 포맷: " + ext)
+
+# 모든 Mesh 수집
+meshes = [o for o in bpy.context.scene.objects if o.type == "MESH"]
+if not meshes:
+    raise RuntimeError("MESH 오브젝트가 없습니다.")
+
+# 컬렉션 정리
+coll = bpy.data.collections.new("CHARACTER")
+bpy.context.scene.collection.children.link(coll)
+for o in meshes:
+    # 기존 컬렉션에서 제거 후 새 컬렉션으로 이동
+    if o.users_collection:
+        for c in o.users_collection:
+            try:
+                c.objects.unlink(o)
+            except Exception:
+                pass
+    coll.objects.link(o)
+
+# 스케일 정리
+for o in meshes:
+    o.select_set(True)
+bpy.ops.object.transform_apply(location=False, rotation=False, scale=True)
+for o in meshes:
+    o.select_set(False)
+
+# -----------------------
+# Body 추정: 바운딩박스 볼륨 기준
+# -----------------------
+def mesh_bbox_volume(obj):
+    m = obj.matrix_world
+    bb = [m @ Vector(corner) for corner in obj.bound_box]
+    minv = Vector((min(v.x for v in bb), min(v.y for v in bb), min(v.z for v in bb)))
+    maxv = Vector((max(v.x for v in bb), max(v.y for v in bb), max(v.z for v in bb)))
+    sz = maxv - minv
+    return abs(sz.x * sz.y * sz.z)
+
+volumes = sorted([(mesh_bbox_volume(o), o) for o in meshes], key=lambda x: x[0], reverse=True)
+body   = volumes[0][1]
+others = [o for _, o in volumes[1:]]
+
+body.name = "Body"
+
+# 의복/헤어/소품 키워드 분류(간이)
+CLOTH_KEYS = ["cloth","skirt","dress","coat","cape","jacket","shirt","pants","sleeve","kimono","robe"]
+HAIR_KEYS  = ["hair","bang","ponytail","fringe","bun","pigtail"]
+
+def classify(o):
+    name = (o.name + " " + " ".join([m.name for m in o.data.materials if m])).lower()
+    if any(k in name for k in CLOTH_KEYS): return "Cloth"
+    if any(k in name for k in HAIR_KEYS):  return "Hair"
+    return "Prop"
+
+for o in others:
+    try:
+        o["part_type"] = classify(o)
+    except Exception:
+        pass
+
+# -----------------------
+# Armature 생성 (간이 휴머노이드 T-포즈)
+# -----------------------
+bpy.ops.object.armature_add(enter_editmode=True)
+arm = bpy.context.object
+arm.name = "Armature"
+eb = arm.data.edit_bones
+
+# Body AABB 기반 중심/크기
+bb = [body.matrix_world @ Vector(c) for c in body.bound_box]
+minv = Vector((min(v.x for v in bb), min(v.y for v in bb), min(v.z for v in bb)))
+maxv = Vector((max(v.x for v in bb), max(v.y for v in bb), max(v.z for v in bb)))
+cent = (minv + maxv) / 2
+height = (maxv.z - minv.z)
+width  = (maxv.x - minv.x)
+
+def add_bone(name, head, tail, parent=None, roll=0.0):
+    b = eb.new(name)
+    b.head = head; b.tail = tail; b.roll = roll
+    if parent: b.parent = parent
+    return b
+
+# 코어 스파인
+hips  = add_bone("Hips",  Vector((cent.x, cent.y, minv.z + height*0.20)), Vector((cent.x, cent.y, minv.z + height*0.30)))
+spine = add_bone("Spine", hips.tail, Vector((cent.x, cent.y, minv.z + height*0.45)), parent=hips)
+chest = add_bone("Chest", spine.tail, Vector((cent.x, cent.y, minv.z + height*0.60)), parent=spine)
+neck  = add_bone("Neck",  Vector((cent.x, cent.y, minv.z + height*0.68)), Vector((cent.x, cent.y, minv.z + height*0.74)), parent=chest)
+headb = add_bone("Head",  neck.tail, Vector((cent.x, cent.y, minv.z + height*0.86)), parent=neck)
+
+# 팔(T-포즈)
+arm_len = max(width*0.35, 0.05)
+ua_L = add_bone("UpperArm.L", Vector((cent.x+0.05*width, cent.y, chest.tail.z-0.02*height)),
+                Vector((cent.x+0.05*width+arm_len*0.5, cent.y, chest.tail.z-0.02*height)), parent=chest)
+fa_L = add_bone("LowerArm.L", ua_L.tail, ua_L.tail + Vector((arm_len*0.5, 0, 0)), parent=ua_L)
+handL= add_bone("Hand.L",     fa_L.tail, fa_L.tail + Vector((arm_len*0.2, 0, 0)), parent=fa_L)
+ua_R = add_bone("UpperArm.R", Vector((cent.x-0.05*width, cent.y, chest.tail.z-0.02*height)),
+                Vector((cent.x-0.05*width-arm_len*0.5, cent.y, chest.tail.z-0.02*height)), parent=chest)
+fa_R = add_bone("LowerArm.R", ua_R.tail, ua_R.tail - Vector((arm_len*0.5, 0, 0)), parent=ua_R)
+handR= add_bone("Hand.R",     fa_R.tail, fa_R.tail - Vector((arm_len*0.2, 0, 0)), parent=fa_R)
+
+# 다리
+leg_off = max(width*0.12, 0.02)
+thighL = add_bone("Thigh.L", Vector((cent.x+leg_off, cent.y, hips.head.z)), Vector((cent.x+leg_off, cent.y, minv.z + height*0.05)), parent=hips)
+shinL  = add_bone("Shin.L",  thighL.tail, Vector((cent.x+leg_off, cent.y, minv.z + 0.01*height)), parent=thighL)
+footL  = add_bone("Foot.L",  shinL.tail, shinL.tail + Vector((0.0, 0.05*height, -0.02*height)), parent=shinL)
+thighR = add_bone("Thigh.R", Vector((cent.x-leg_off, cent.y, hips.head.z)), Vector((cent.x-leg_off, cent.y, minv.z + height*0.05)), parent=hips)
+shinR  = add_bone("Shin.R",  thighR.tail, Vector((cent.x-leg_off, cent.y, minv.z + 0.01*height)), parent=thighR)
+footR  = add_bone("Foot.R",  shinR.tail, shinR.tail + Vector((0.0, 0.05*height, -0.02*height)), parent=shinR)
+
+bpy.ops.object.mode_set(mode='OBJECT')
+
+# -----------------------
+# Body → Armature 자동 바인딩
+# -----------------------
+for o in meshes:
+    o.select_set(False)
+body.select_set(True)
+arm.select_set(True)
+bpy.context.view_layer.objects.active = arm
+bpy.ops.object.parent_set(type='ARMATURE_AUTO')
+
+# -----------------------
+# 의복 처리
+# -----------------------
+if args.surface_deform:
+    # Body 기준 Surface Deform (본가중치 최소화)
+    bpy.context.view_layer.objects.active = body
+    for o in others:
+        if o.type != "MESH":
+            continue
+        # 기존 Armature modifier 제거
+        for m in list(o.modifiers):
+            if m.type == "ARMATURE":
+                try:
+                    o.modifiers.remove(m)
+                except Exception:
+                    pass
+        sdef = o.modifiers.new("SurfaceDeform", "SURFACE_DEFORM")
+        sdef.target = body
+        try:
+            bpy.ops.object.surfacedeform_bind(modifier=sdef.name)
+        except Exception as e:
+            print("[WARN] SurfaceDeform bind 실패:", e)
+
+elif args.limit_cloth_bones:
+    # Armature 유지하되 본 영향 축소(간이 훅)
+    for o in others:
+        if o.type != "MESH":
+            continue
+        has_arm = any(m.type == "ARMATURE" for m in o.modifiers)
+        if not has_arm:
+            m = o.modifiers.new("Armature", "ARMATURE")
+            m.object = arm
+    # 세부 가중치 조정은 모델마다 달라 완전 자동화 난이도 높음 → 후편집 전제
+
+# -----------------------
+# Toon Shader & Outline
+# -----------------------
+def make_toon_material(name="ToonMat", base_color=(0.8, 0.8, 0.8, 1.0)):
+    mat = bpy.data.materials.new(name)
+    mat.use_nodes = True
+    nt = mat.node_tree
+    nodes = nt.nodes; links = nt.links
+    # 초기화
+    for n in list(nodes):
+        nodes.remove(n)
+    out  = nodes.new("ShaderNodeOutputMaterial"); out.location = (400, 0)
+    toon = nodes.new("ShaderNodeBsdfToon");       toon.location = (0, 0)
+    toon.inputs["Color"].default_value  = base_color
+    toon.inputs["Size"].default_value   = 0.5
+    toon.inputs["Smooth"].default_value = 0.0
+    links.new(toon.outputs["BSDF"], out.inputs["Surface"])
+    return mat
+
+def apply_toon(obj):
+    if obj.type != "MESH":
+        return
+    if not obj.data.materials:
+        obj.data.materials.append(make_toon_material())
+    else:
+        for i, _ in enumerate(obj.data.materials):
+            obj.data.materials[i] = make_toon_material(f"Toon_{obj.name}_{i}")
+
+def add_outline(obj, thickness=0.003):
+    if obj.type != "MESH":
+        return
+    outline = obj.copy()
+    outline.data = obj.data.copy()
+    outline.name = obj.name + "_Outline"
+    # 컬렉션 링크
+    for c in outline.users_collection:
+        try:
+            c.objects.unlink(outline)
+        except Exception:
+            pass
+    bpy.context.scene.collection.objects.link(outline)
+
+    # 검정 Emission 머티리얼
+    mat = bpy.data.materials.new("OutlineBlack")
+    mat.use_nodes = True
+    nodes = mat.node_tree.nodes; links = mat.node_tree.links
+    for n in list(nodes): nodes.remove(n)
+    out = nodes.new("ShaderNodeOutputMaterial"); out.location = (200, 0)
+    em  = nodes.new("ShaderNodeEmission");       em.location = (0, 0)
+    em.inputs["Color"].default_value = (0, 0, 0, 1)
+    em.inputs["Strength"].default_value = 1.0
+    links.new(em.outputs["Emission"], out.inputs["Surface"])
+
+    outline.data.materials.clear()
+    outline.data.materials.append(mat)
+
+    # Solidify로 외곽선(노멀 반전)
+    bpy.context.view_layer.objects.active = outline
+    solid = outline.modifiers.new("OutlineSolidify", "SOLIDIFY")
+    solid.thickness = -abs(thickness)
+    solid.offset = 1.0
+    solid.use_flip_normals = True
+    solid.material_offset = 0
+    outline.show_in_front = True
+
+if args.toon:
+    apply_toon(body)
+    for o in others:
+        apply_toon(o)
+
+if args.outline:
+    add_outline(body)
+    for o in others:
+        add_outline(o, thickness=0.003)
+
+# -----------------------
+# 표정(Shape Keys)
+# -----------------------
+def ensure_basis_key(obj):
+    if obj.data.shape_keys is None:
+        obj.shape_key_add(name="Basis")
+    return obj.data.shape_keys.key_blocks["Basis"]
+
+def add_placeholder_face_keys(obj):
+    ensure_basis_key(obj)
+    keys = [
+        "EyeBlink_L","EyeBlink_R","BrowDown_L","BrowDown_R",
+        "BrowUp","JawOpen","MouthSmile_L","MouthSmile_R",
+        "MouthFrown","MouthPucker","MouthLeft","MouthRight"
+    ]
+    for k in keys:
+        try:
+            obj.shape_key_add(name=k)
+        except Exception:
+            pass
+
+def try_faceit_generate():
+    # 애드온 설치 감지(자동 실행은 버전 의존으로 생략)
+    if "faceit" in bpy.context.preferences.addons:
+        print("[INFO] Faceit addon detected. Use GUI to auto-generate blendshapes if needed.")
+        return True
+    for k in bpy.context.preferences.addons.keys():
+        if "face" in k and "it" in k:
+            print(f"[INFO] Possibly Faceit-like addon detected: {k}")
+            return True
+    return False
+
+if args.try_faceit and try_faceit_generate():
+    # 사용자 GUI에서 Faceit 워크플로 진행 권장
+    pass
+else:
+    add_placeholder_face_keys(body)
+
+# -----------------------
+# Export
+# -----------------------
+# 선택 정리
+for o in bpy.context.scene.objects:
+    o.select_set(False)
+arm.select_set(True)
+body.select_set(True)
+for o in others:
+    if o.type == "MESH":
+        o.select_set(True)
+bpy.context.view_layer.objects.active = arm
+
+if export_fmt == "fbx":
+    bpy.ops.export_scene.fbx(
+        filepath=out_path,
+        use_selection=True,
+        apply_unit_scale=True,
+        bake_space_transform=True,
+        add_leaf_bones=False,
+        mesh_smooth_type='FACE'
+    )
+else:
+    bpy.ops.export_scene.gltf(
+        filepath=out_path,
+        export_format='GLB',
+        use_selection=True,
+        export_apply=True
+    )
+
+print("[DONE] Exported:", out_path)

requirements.txt

@@ -0,0 +1,42 @@
+# UI
+gradio==4.44.0
+gradio_client>=1.3.0
+
+# Core
+torch==2.3.1+cpu
+torchvision==0.18.1+cpu
+--extra-index-url https://download.pytorch.org/whl/cpu
+numpy==1.26.4
+Pillow
+scipy
+tqdm
+requests
+huggingface_hub
+safetensors
+accelerate==0.31.0
+
+# Diffusers / ControlNet
+diffusers==0.29.2
+transformers==4.43.4
+opencv-python-headless==4.10.0.84
+imageio
+scikit-image
+
+# Background removal
+rembg==2.0.56
+onnxruntime==1.18.0
+
+# Weapon removal (inpaint)
+simple-lama-inpainting
+
+# Hands (21 keypoints)
+mediapipe==0.10.14
+protobuf<5
+
+# 3D & optional 6-view render (headless에서 실패하면 코드가 자동 스킵)
+trimesh
+networkx
+pyrender
+PyOpenGL
+PyOpenGL-accelerate
+pyglet