DR: ComfyUI RTX3090 バッチ生成最速ワークフロー NSFW最適設定

{ "3": { "class_type": "KSampler", "inputs": { "seed": 0, "steps": 20, "cfg": 7.0, "sampler_name": "dpm_2_ancestral", "scheduler": "karras", "denoise": 1.0, "model": ["4", 0], "positive": ["6", 0], "negative": ["7", 0], "latent_image": ["5", 0] } }, "4": { "class_type": "CheckpointLoaderSimple", "inputs": { "ckpt_name": "waiIllustriousSDXL_v160.safetensors" } }, "5": { "class_type": "EmptyLatentImage", "inputs": { "width": 832, "height": 1216, "batch_size": 4 } }, "6": { "class_type": "CLIPTextEncode", "inputs": { "text": "POSITIVE_PROMPT_HERE", "clip": ["4", 1] } }, "7": { "class_type": "CLIPTextEncode", "inputs": { "text": "NEGATIVE_PROMPT_HERE", "clip": ["4", 1] } }, "8": { "class_type": "VAEDecode", "inputs": { "samples": ["3", 0], "vae": ["4", 2] } }, "9": { "class_type": "SaveImage", "inputs": { "filename_prefix": "batch_output/img", "images": ["8", 0] } } }

#!/usr/bin/env python3 """ ComfyUI APIバッチ生成スクリプト RTX3090 最速設定で大量生成 """ import json import requests import random import time import os from pathlib import Path COMFY_URL = "http://localhost:8188" OUTPUT_DIR = Path("C:/ddrive/AI/ComfyUI_portable/ComfyUI/output/batch") OUTPUT_DIR.mkdir(exist_ok=True) # ========== プロンプトテンプレート ========== POSITIVE_BASE = """masterpiece, best quality, ultra detailed, 8k, 1girl, {character_desc}, {scene_desc}, perfect anatomy, beautiful eyes, detailed face, soft lighting, cinematic composition""" NEGATIVE_BASE = """worst quality, low quality, normal quality, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, bad feet, ugly, duplicate, morbid, mutilated, blurry, mutation, deformed, watermark, signature, username""" # NSFWジャンル向け強化ネガティブ（審査落ちリスク低減） NEGATIVE_NSFW_SAFE = """worst quality, low quality, child, minor, loli, shota, underage, childlike, young girl, small breasts flat chest developing""" def queue_prompt(prompt_dict: dict) -> str: """ComfyUIキューにプロンプトを投入""" payload = {"prompt": prompt_dict} resp = requests.post(f"{COMFY_URL}/prompt", json=payload) return resp.json().get("prompt_id") def get_queue_status() -> dict: """キュー状況を確認""" return requests.get(f"{COMFY_URL}/queue").json() def wait_for_completion(prompt_id: str, timeout: int = 300) -> bool: """生成完了まで待機""" start = time.time() while time.time() - start < timeout: history = requests.get(f"{COMFY_URL}/history/{prompt_id}").json() if prompt_id in history: return True time.sleep(2) return False def load_workflow(json_path: str) -> dict: """ワークフローJSONを読み込み""" with open(json_path, 'r') as f: return json.load(f) def batch_generate( workflow_path: str, prompts: list[dict], batch_size: int = 4, steps: int = 20, cfg: float = 7.0, width: int = 832, height: int = 1216 ) -> list[str]: """バッチ生成メイン処理""" workflow = load_workflow(workflow_path) generated_ids = [] for i, prompt_data in enumerate(prompts): # ワークフローにパラメータ注入 wf = json.loads(json.dumps(workflow)) # deepcopy # サンプラー設定 wf["3"]["inputs"]["steps"] = steps wf["3"]["inputs"]["cfg"] = cfg wf["3"]["inputs"]["seed"] = random.randint(0, 999999999) # 解像度・バッチサイズ wf["5"]["inputs"]["width"] = width wf["5"]["inputs"]["height"] = height wf["5"]["inputs"]["batch_size"] = batch_size # プロンプト設定 positive = POSITIVE_BASE.format( character_desc=prompt_data.get("character", ""), scene_desc=prompt_data.get("scene", "") ) if prompt_data.get("extra_positive"): positive += ", " + prompt_data["extra_positive"] negative = NEGATIVE_BASE if prompt_data.get("nsfw_safe"): negative += ", " + NEGATIVE_NSFW_SAFE wf["6"]["inputs"]["text"] = positive wf["7"]["inputs"]["text"] = negative # キュー投入 prompt_id = queue_prompt(wf) generated_ids.append(prompt_id) print(f" [{i+1}/{len(prompts)}] キュー投入: {prompt_id[:8]}...") # キューが溜まりすぎたら待機 while True: status = get_queue_status() pending = len(status.get("queue_pending", [])) if pending < 3: break print(f" キュー待機中... ({pending}件)") time.sleep(5) # 全完了待機 print("生成完了待機中...") for pid in generated_ids: wait_for_completion(pid) return generated_ids # ========== プロンプトセット例（DLsite/FANZA向け）========== SAMPLE_PROMPTS = [ { "character": "long silver hair, golden eyes, tall woman, mature female, elegant", "scene": "office, white blouse, pencil skirt, confident pose", "nsfw_safe": True }, { "character": "short black hair, blue eyes, athletic build, toned body", "scene": "gym, sports bra, workout shorts, dynamic pose", "nsfw_safe": True }, { "character": "wavy brown hair, green eyes, gentle smile, soft expression", "scene": "cafe, casual outfit, reading book, cozy atmosphere", "nsfw_safe": False } ] if __name__ == "__main__": print("=== ComfyUI バッチ生成開始 ===") print(f"生成プロンプト数: {len(SAMPLE_PROMPTS)}") print(f"バッチサイズ: 4 枚/プロンプト") print(f"予想生成枚数: {len(SAMPLE_PROMPTS) * 4} 枚") ids = batch_generate( workflow_path="batch_gen_fast.json", prompts=SAMPLE_PROMPTS, batch_size=4, steps=20, cfg=7.0 ) print(f"\n完了: {len(ids)} バッチ処理")

:: run_nvidia_gpu.bat 最適化版 :: C:\ddrive\AI\ComfyUI_portable に配置 .\python_embeded\python.exe -s ComfyUI\main.py ^ --windows-standalone-build ^ --gpu-only ^ --fp16-vae ^ --force-fp16 ^ --preview-method auto ^ --listen 0.0.0.0 ^ --port 8188

-- 品質タグ（先頭に固定）-- masterpiece, best quality, ultra-detailed, highres, 8k uhd, -- キャラクター描写 -- 1girl, [年齢描写=adult/mature female], [髪色+スタイル], [目の色], [体型: slim/athletic/curvy/busty], [表情: gentle smile/confident/alluring], -- 衣装・シーン -- [服装詳細], [場所・背景], -- カメラ・構図 -- [shot type: close-up/half body/full body/cowboy shot], [lighting: soft light/studio lighting/golden hour/backlight], perfect anatomy, perfect hands, detailed fingers, -- Illustrious特有タグ -- anime style, illustration, 2d, cel shading, flat color shading

-- 必須ネガティブ（常時使用）-- (worst quality:1.4), (low quality:1.4), (normal quality:1.3), lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, bad feet, signature, watermark, ugly, duplicate, morbid, mutilated, out of frame, extra limbs, body out of frame, poorly drawn face, cloned face, gross proportions, deformed, blurry, bad proportions, cloned face, disfigured, extra arms, extra legs, fused fingers, too many fingers, long neck, -- NSFW審査対策（DLsite/FANZA出品時）-- minor, child, loli, shota, underage, young, childish face, flat chest, small breasts, developing body, school uniform（年齢曖昧な場合）

#!/usr/bin/env python3 """生成画像を自動的にセット別フォルダに整理""" import shutil import os from pathlib import Path from datetime import datetime OUTPUT_BASE = Path("C:/ddrive/AI/ComfyUI_portable/ComfyUI/output") ARCHIVE_BASE = Path("D:/CG_Archive") def organize_outputs(batch_name: str = None): """生成画像を日付・バッチ名フォルダに整理""" today = datetime.now().strftime('%Y%m%d') batch = batch_name or f"batch_{today}" src = OUTPUT_BASE / "batch_output" dst = ARCHIVE_BASE / today / batch dst.mkdir(parents=True, exist_ok=True) moved = 0 for img in src.glob("*.png"): shutil.move(str(img), str(dst / img.name)) moved += 1 print(f"整理完了: {moved}枚 → {dst}") return str(dst) if __name__ == "__main__": organize_outputs()