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| # app.py — BRA v7 (AIGaming repo) × InstantID × ZeroGPU | |
| # 2025-06-22 | |
| ############################################################################## | |
| # torchvision 0.17+ 互換パッチ（functional_tensor → functional） | |
| ############################################################################## | |
| import sys, types | |
| try: | |
| import torchvision.transforms.functional as F | |
| if "torchvision.transforms.functional_tensor" not in sys.modules: | |
| faux = types.ModuleType("torchvision.transforms.functional_tensor") | |
| # 必要最低限だけ持たせる | |
| faux.rgb_to_grayscale = getattr(F, "rgb_to_grayscale", None) | |
| sys.modules["torchvision.transforms.functional_tensor"] = faux | |
| except Exception as e: | |
| print("[WARN] torchvision compatibility patch failed:", e) | |
| ############################################################################## | |
| # 0. diffusers-0.27 互換: cached_download() パッチ | |
| ############################################################################## | |
| from huggingface_hub import hf_hub_download | |
| import huggingface_hub as _hf | |
| if not hasattr(_hf, "cached_download"): | |
| _hf.cached_download = hf_hub_download | |
| ############################################################################## | |
| # 1. ライブラリ | |
| ############################################################################## | |
| import os, io, base64, subprocess, traceback | |
| from pathlib import Path | |
| from typing import Optional | |
| import numpy as np | |
| import torch, gradio as gr, spaces | |
| from fastapi import FastAPI, UploadFile, File, Form, HTTPException | |
| from PIL import Image | |
| from diffusers import ( | |
| StableDiffusionControlNetPipeline, | |
| ControlNetModel, | |
| DPMSolverMultistepScheduler, | |
| ) | |
| from diffusers.loaders import AttnProcsLayers | |
| from insightface.app import FaceAnalysis | |
| from realesrgan import RealESRGANer | |
| ############################################################################## | |
| # 2. キャッシュパス | |
| ############################################################################## | |
| ROOT = Path("/data") if Path("/data").exists() else Path.home() / ".cache/instantid" | |
| MODELS = ROOT / "models"; LORA = ROOT / "lora"; UPSCALE = ROOT / "realesrgan" | |
| for p in (MODELS, LORA, UPSCALE): p.mkdir(parents=True, exist_ok=True) | |
| ############################################################################## | |
| # 3. モデル ID / ファイル | |
| ############################################################################## | |
| # --- BRA v7 (公開) --- | |
| BRA_REPO = "AIGaming/beautiful_realistic_asians" | |
| BRA_FILE = "beautifulRealistic_v7.safetensors" | |
| BRA_REV = "801a9b1999dd7018e58a1e2b432fdccd3d1d723d" # 固定 revision | |
| # --- IP-Adapter 本体 & LoRA --- | |
| IP_REPO, IP_BIN = "h94/IP-Adapter", "models/ip-adapter-plus-face_sd15.bin" | |
| LORA_REPO,IP_LORA = "h94/IP-Adapter-FaceID", "ip-adapter-faceid-plusv2_sd15_lora.safetensors" | |
| # --- ControlNet (MediaPipe Face) --- | |
| CN_REPO, CN_SUBF = "CrucibleAI/ControlNetMediaPipeFace", "diffusion_sd15" | |
| # --- Real-ESRGAN --- | |
| ESRGAN_REPO, ESRGAN_FILE = "aimagelab/realesrgan", "RealESRGAN_x4plus.pth" | |
| ############################################################################## | |
| # 4. HF Hub ダウンロード | |
| ############################################################################## | |
| def dl(repo: str, file: str, sub: str | None = None, rev: str | None = None) -> Path: | |
| return Path(hf_hub_download(repo, file, subfolder=sub, | |
| revision=rev, cache_dir=str(MODELS))) | |
| ############################################################################## | |
| # 5. グローバル | |
| ############################################################################## | |
| pipe: Optional[StableDiffusionControlNetPipeline] = None | |
| face_analyser: Optional[FaceAnalysis] = None | |
| upsampler: Optional[RealESRGANer] = None | |
| ############################################################################## | |
| # 6. 初期化 | |
| ############################################################################## | |
| def init(): | |
| global pipe, face_analyser, upsampler | |
| if pipe is not None: | |
| return | |
| print("[INIT] downloading models…") | |
| # 6-1 BRA v7 | |
| bra_ckpt = dl(BRA_REPO, BRA_FILE, rev=BRA_REV) | |
| # 6-2 ControlNet | |
| cn = ControlNetModel.from_pretrained( | |
| CN_REPO, subfolder=CN_SUBF, torch_dtype=torch.float16, | |
| cache_dir=str(MODELS) | |
| ) | |
| # 6-3 Pipeline from .safetensors + ControlNet | |
| pipe_ = StableDiffusionControlNetPipeline.from_single_file( | |
| bra_ckpt, controlnet=cn, torch_dtype=torch.float16, | |
| safety_checker=None | |
| ) | |
| pipe_.scheduler = DPMSolverMultistepScheduler.from_config(pipe_.scheduler.config) | |
| # 6-4 IP-Adapter | |
| ip_lora = dl(LORA_REPO, IP_LORA) | |
| ### 最終修正 ### subfolder引数に空文字列""を渡し、TypeErrorを回避する | |
| pipe_.load_ip_adapter(IP_REPO, "", weight_name=IP_BIN, cache_dir=str(MODELS)) | |
| AttnProcsLayers(pipe_.unet.attn_processors).load_lora_weights( | |
| ip_lora, adapter_name="ip_faceid", safe_load=True | |
| ) | |
| pipe_.set_adapters(["ip_faceid"], adapter_weights=[0.6]) | |
| pipe_.to("cuda"); pipe_ = pipe_ | |
| pipe = pipe_ | |
| face_analyser = FaceAnalysis( | |
| name="buffalo_l", root=str(MODELS), providers=["CUDAExecutionProvider"] | |
| ); face_analyser.prepare(ctx_id=0, det_size=(640,640)) | |
| esr = dl(ESRGAN_REPO, ESRGAN_FILE) | |
| upsampler = RealESRGANer(scale=4, model_path=str(esr), half=True, | |
| tile=512, tile_pad=10, pre_pad=0, gpu_id=0) | |
| print("[INIT] ready.") | |
| ############################################################################## | |
| # 7. プロンプト | |
| ############################################################################## | |
| BASE = "(masterpiece:1.2), best quality, ultra-realistic, RAW photo, 8k, cinematic lighting, textured skin, " | |
| NEG = "verybadimagenegative_v1.3, ng_deepnegative_v1_75t, (worst quality:2), (low quality:2), lowres, blurry, bad anatomy, bad hands, extra digits, watermark, signature" | |
| ############################################################################## | |
| # 8. 生成コア | |
| ############################################################################## | |
| def generate(face: Image.Image, subj: str, add: str, neg: str, | |
| cfg: float, ipw: float, steps: int, w: int, h: int, | |
| up: bool, upf: int, progress=gr.Progress(track_tqdm=True)): | |
| if pipe is None: | |
| init() | |
| if len(face_analyser.get(np.array(face))) == 0: | |
| raise ValueError("顔が検出できません。他の画像でお試しください。") | |
| pipe.set_adapters(["ip_faceid"], adapter_weights=[ipw]) | |
| img = pipe(prompt=BASE+subj+", "+add, | |
| negative_prompt=NEG+", "+neg, | |
| num_inference_steps=steps, guidance_scale=cfg, | |
| image=face, width=w, height=h).images[0] | |
| if up: | |
| upsampler.scale = int(upf) | |
| img, _ = upsampler.enhance(np.array(img)); img = Image.fromarray(img) | |
| return img | |
| ############################################################################## | |
| # 9. Gradio UI | |
| ############################################################################## | |
| with gr.Blocks(title="BRA v7 × InstantID (ZeroGPU)") as demo: | |
| gr.Markdown("## BRA v7 × InstantID") | |
| with gr.Row(): | |
| f = gr.Image(type="pil", label="Face ID"); s = gr.Textbox(label="被写体説明") | |
| ap = gr.Textbox(label="追加プロンプト"); ng = gr.Textbox(label="追加ネガ") | |
| with gr.Row(): | |
| cf = gr.Slider(1,20,7.5,0.5,"CFG"); ip = gr.Slider(0.1,1.0,0.6,0.05,"IP-Adapter Weight") | |
| with gr.Row(): | |
| st = gr.Slider(10,50,30,1,"Steps"); W = gr.Slider(512,1024,768,64,"W"); H = gr.Slider(512,1024,768,64,"H") | |
| with gr.Row(): | |
| up = gr.Checkbox(label="Real-ESRGAN"); upf = gr.Radio([4,8], value=4, label="アップスケール") | |
| btn = gr.Button("Generate"); out = gr.Image(type="pil", label="Result") | |
| btn.click(generate, [f,s,ap,ng,cf,ip,st,W,H,up,upf], out, show_progress=True) | |
| ############################################################################## | |
| # 10. FastAPI | |
| ############################################################################## | |
| app = FastAPI() | |
| async def api_gen(subj: str=Form(...), cfg: float=Form(7.5), stp: int=Form(30), | |
| ipw: float=Form(0.6), W: int=Form(768), H: int=Form(768), | |
| file: UploadFile=File(...)): | |
| img = Image.open(io.BytesIO(await file.read())).convert("RGB") | |
| res = generate(img, subj, "", "", cfg, ipw, stp, W, H, False, 4) | |
| buf = io.BytesIO(); res.save(buf,"PNG") | |
| return {"image":"data:image/png;base64,"+base64.b64encode(buf.getvalue()).decode()} | |
| ############################################################################## | |
| # 11. Launch | |
| ############################################################################## | |
| demo.queue(default_concurrency_limit=2).launch(share=False) |