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import os |
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import shutil |
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import subprocess |
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import sys |
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import time |
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import mimetypes |
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from pathlib import Path |
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from typing import List, Optional, Tuple |
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from huggingface_hub import hf_hub_download |
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class SeedVRServer: |
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def __init__(self, **kwargs): |
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self.SEEDVR_ROOT = Path(os.getenv("SEEDVR_ROOT", "/data/SeedVR")) |
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self.CKPTS_ROOT = Path("/data/seedvr_models_fp16") |
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self.OUTPUT_ROOT = Path(os.getenv("OUTPUT_ROOT", "/app/outputs")) |
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self.INPUT_ROOT = Path(os.getenv("INPUT_ROOT", "/app/inputs")) |
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self.HF_HOME_CACHE = Path(os.getenv("HF_HOME", "/data/.cache/huggingface")) |
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self.REPO_URL = os.getenv("SEEDVR_GIT_URL", "https://github.com/numz/ComfyUI-SeedVR2_VideoUpscaler") |
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self.NUM_GPUS_TOTAL = int(os.getenv("NUM_GPUS", "4")) |
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print("🚀 SeedVRServer (FP16) inicializando e preparando o ambiente...") |
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for p in [self.SEEDVR_ROOT.parent, self.CKPTS_ROOT, self.OUTPUT_ROOT, self.INPUT_ROOT, self.HF_HOME_CACHE]: |
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p.mkdir(parents=True, exist_ok=True) |
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self.setup_dependencies() |
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print("✅ SeedVRServer (FP16) pronto.") |
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def setup_dependencies(self): |
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self._ensure_repo() |
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self._ensure_model() |
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def _ensure_repo(self) -> None: |
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if not (self.SEEDVR_ROOT / ".git").exists(): |
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print(f"[SeedVRServer] Clonando repositório para {self.SEEDVR_ROOT}...") |
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subprocess.run(["git", "clone", "--depth", "1", self.REPO_URL, str(self.SEEDVR_ROOT)], check=True) |
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else: |
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print("[SeedVRServer] Repositório SeedVR já existe.") |
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def _ensure_model(self) -> None: |
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"""Baixa os arquivos de modelo FP16 otimizados e suas dependências.""" |
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print(f"[SeedVRServer] Verificando checkpoints (FP16) em {self.CKPTS_ROOT}...") |
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model_files = { |
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"seedvr2_ema_3b_fp16.safetensors": "MonsterMMORPG/SeedVR2_SECourses", "ema_vae_fp16.safetensors": "MonsterMMORPG/SeedVR2_SECourses", |
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"pos_emb.pt": "ByteDance-Seed/SeedVR2-3B", "neg_emb.pt": "ByteDance-Seed/SeedVR2-3B" |
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} |
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for filename, repo_id in model_files.items(): |
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if not (self.CKPTS_ROOT / filename).exists(): |
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print(f"Baixando {filename} de {repo_id}...") |
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hf_hub_download(repo_id=repo_id, filename=filename, local_dir=str(self.CKPTS_ROOT), cache_dir=str(self.HF_HOME_CACHE), token=os.getenv("HF_TOKEN")) |
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print("[SeedVRServer] Checkpoints (FP16) estão no local correto.") |
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def _prepare_job(self, input_file: str) -> Tuple[Path, Path]: |
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ts = f"{int(time.time())}_{os.urandom(4).hex()}" |
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job_input_dir = self.INPUT_ROOT / f"job_{ts}" |
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out_dir = self.OUTPUT_ROOT / f"run_{ts}" |
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job_input_dir.mkdir(parents=True, exist_ok=True) |
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out_dir.mkdir(parents=True, exist_ok=True) |
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shutil.copy2(input_file, job_input_dir / Path(input_file).name) |
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return job_input_dir, out_dir |
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def run_inference(self, filepath: str, *, seed: int, resh: int, resw: int, spsize: int, fps: Optional[float] = None): |
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script = self.SEEDVR_ROOT / "inference_cli.py" |
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job_input_dir, outdir = self._prepare_job(filepath) |
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mediatype, _ = mimetypes.guess_type(filepath) |
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is_image = mediatype and mediatype.startswith("image") |
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effective_nproc = 1 if is_image else self.NUM_GPUS_TOTAL |
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effective_spsize = 1 if is_image else spsize |
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output_filename = f"result_{Path(filepath).stem}.mp4" if not is_image else f"{Path(filepath).stem}_upscaled" |
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output_filepath = outdir / output_filename |
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cmd = [ |
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"torchrun", "--standalone", "--nnodes=1", |
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f"--nproc-per-node={effective_nproc}", |
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str(script), |
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"--video_path", str(filepath), |
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"--output", str(output_filepath), |
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"--model_dir", str(self.CKPTS_ROOT), |
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"--seed", str(seed), |
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"--cuda_device", "0", |
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"--resolution", str(resh), |
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"--batch_size", str(effective_spsize), |
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"--model", "seedvr2_ema_3b_fp16.safetensors", |
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"--preserve_vram", |
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"--debug", |
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"--output_format", "video" if not is_image else "png", |
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] |
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print("SeedVRServer Comando:", " ".join(cmd)) |
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try: |
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subprocess.run(cmd, cwd=str(self.SEEDVR_ROOT), check=True, env=os.environ.copy(), stdout=sys.stdout, stderr=sys.stderr) |
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if is_image: |
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image_dir = output_filepath if output_filepath.suffix == "" else output_filepath.with_suffix("") |
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return str(image_dir), None, outdir |
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else: |
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return None, str(output_filepath), outdir |
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except Exception as e: |
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print(f"[UI ERROR] A inferência falhou: {e}") |
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return None, None, None |
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