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meeting-103 v2.1 clean R1 ✅5/5: PuLID + Redux = pastel 48.5% (R9 best 갱신) R0 환경 점검: - VRAM 11.7/12.4GB free (94%) — 해소 확인 - pytorch 2.12.0+cu130 + sageattention venv 검증 - 모델 인벤토리: Flux Dev Q5 GGUF, PuLID, Redux, byeolyi-ref-916 확보 - fp8 다운로드 .part 0 bytes (재개 대기) R1 clean 5조합 (5/5 success): - 1-1: PuLID w0.85 mean → pastel 25.7% / black 1.95% - 1-2: PuLID w0.85 mean delayed_start 0.05 → pastel 10.0% / black 14.0% (어두움) - 1-3: PuLID w1.0 mean → pastel 27.5% / black 0.79% - 1-4: PuLID w0.7 + Redux 0.5 → pastel 48.5% / black 0.27% ★ R1 best - 1-5: 한옥 baseline Flux Dev 768² → pastel 12.9% / black 11.7% CUDA error 회복: - 1-2 retry concat → CUDA invalid argument → 후속 1-2~1-5 모두 실패 - ComfyUI venv 재시작 (sage + pytorch 2.12) → 1-2 변형 (delayed_start)로 대체 - 재시도 4/4 모두 success 이전 R9 best (44.5%) → R1-4 (48.5%) = +4 pp 갱신 자산 라이브러리 누적: - models-performance.json: 7 모델 추적 (flux-dev, pulid-flux, flux-redux 등) - workflows: winner_auto 1 + partial 2 - prompts/proven: illustration_auto 패턴 3건 - prompts/failed: pastel-low + CUDA error 패턴 - prompts/negative: A_byeolyi 패턴 etc. 검수: - Vault: D:\Vault\8460s-image-rd\eval\meeting-103-v2.1-clean-grid.html - Gitea: results/meeting-103-v2.1-clean/round1/
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<!DOCTYPE html>
<html lang="ko"><head><meta charset="utf-8">
meeting-103 v2.1 clean R2 ✅5/5: PuLID 0.85+Redux 0.5 = pastel 49.99% (전체 best 갱신) R2 5조합 (5/5 success, retry 2회 포함): - 2-1: PuLID 0.7 + Redux 0.5 + Stage 3 Refiner (denoise 0.3) → 48.82% (Stage 3 효과 미미) - 2-2: PuLID 0.7 + Redux 0.7 → 48.93% - 2-3: PuLID 0.7 + Redux 0.3 → 38.52% (Redux 낮으면 파스텔 감소) - 2-4: PuLID 0.85 + Redux 0.5 → 49.99% ★ R2 best & 전체 best - 2-5: 한옥 spring (cherry blossom) → 44.45% / black 4.3% R1 best (R1-4 48.5%) → R2-4 (49.99%) = +1.5 pp 갱신 R9 legacy (44.5%) → R2-4 (49.99%) = +5.5 pp 누적 학습: - PuLID weight 0.85 + Redux 0.5 multiply 조합이 0.7/0.5 보다 우월 - Redux 0.3 너무 낮음, 0.7 비슷, 0.85+ 미검증 - Stage 3 Refiner 효과 미미 (48.5% → 48.82%, +0.3pp) CUDA error 회복: - 2-3, 2-4, 2-5 첫 시도 CUDA invalid argument - ComfyUI venv 재시작 후 retry → 3/3 모두 success - 매 ~5건 후 재시작 패턴 확인됨 자산 라이브러리: - models-performance: 8 모델 추적 - workflows: winner_auto 4 (R1-4, R2-1, R2-2, R2-4) + partial 5 - prompts/proven: 7 패턴 (R1, R2 합산) R3 계획: - 3-1: PuLID 0.7 + Redux 0.85 (push redux 더 강) - 3-2: PuLID 0.6 + Redux 0.7 (PuLID 약화) - 3-3: PuLID 0.7 + Redux 0.7 @ 1024x1792 (해상도 증가) - 3-4: Qwen-Image fp8 + Lightning LoRA 60갑자 (fp8 ~20G 완료, GGUF 회피) - 3-5: Pony V6 img2img from byeolyi-ref (대안 ID 방법) 검수: D:\Vault\8460s-image-rd\eval\meeting-103-v2.1-clean-grid.html
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<title>meeting-103 v2.1 clean — R1+R2 grid</title>
meeting-103 v2.1 clean R1 ✅5/5: PuLID + Redux = pastel 48.5% (R9 best 갱신) R0 환경 점검: - VRAM 11.7/12.4GB free (94%) — 해소 확인 - pytorch 2.12.0+cu130 + sageattention venv 검증 - 모델 인벤토리: Flux Dev Q5 GGUF, PuLID, Redux, byeolyi-ref-916 확보 - fp8 다운로드 .part 0 bytes (재개 대기) R1 clean 5조합 (5/5 success): - 1-1: PuLID w0.85 mean → pastel 25.7% / black 1.95% - 1-2: PuLID w0.85 mean delayed_start 0.05 → pastel 10.0% / black 14.0% (어두움) - 1-3: PuLID w1.0 mean → pastel 27.5% / black 0.79% - 1-4: PuLID w0.7 + Redux 0.5 → pastel 48.5% / black 0.27% ★ R1 best - 1-5: 한옥 baseline Flux Dev 768² → pastel 12.9% / black 11.7% CUDA error 회복: - 1-2 retry concat → CUDA invalid argument → 후속 1-2~1-5 모두 실패 - ComfyUI venv 재시작 (sage + pytorch 2.12) → 1-2 변형 (delayed_start)로 대체 - 재시도 4/4 모두 success 이전 R9 best (44.5%) → R1-4 (48.5%) = +4 pp 갱신 자산 라이브러리 누적: - models-performance.json: 7 모델 추적 (flux-dev, pulid-flux, flux-redux 등) - workflows: winner_auto 1 + partial 2 - prompts/proven: illustration_auto 패턴 3건 - prompts/failed: pastel-low + CUDA error 패턴 - prompts/negative: A_byeolyi 패턴 etc. 검수: - Vault: D:\Vault\8460s-image-rd\eval\meeting-103-v2.1-clean-grid.html - Gitea: results/meeting-103-v2.1-clean/round1/
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.summary { background: #1c1c28; border-left: 3px solid #6f7df2; padding: 12px 16px; margin-bottom: 24px; border-radius: 6px; }
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meeting-103 v2.1 clean R2 ✅5/5: PuLID 0.85+Redux 0.5 = pastel 49.99% (전체 best 갱신) R2 5조합 (5/5 success, retry 2회 포함): - 2-1: PuLID 0.7 + Redux 0.5 + Stage 3 Refiner (denoise 0.3) → 48.82% (Stage 3 효과 미미) - 2-2: PuLID 0.7 + Redux 0.7 → 48.93% - 2-3: PuLID 0.7 + Redux 0.3 → 38.52% (Redux 낮으면 파스텔 감소) - 2-4: PuLID 0.85 + Redux 0.5 → 49.99% ★ R2 best & 전체 best - 2-5: 한옥 spring (cherry blossom) → 44.45% / black 4.3% R1 best (R1-4 48.5%) → R2-4 (49.99%) = +1.5 pp 갱신 R9 legacy (44.5%) → R2-4 (49.99%) = +5.5 pp 누적 학습: - PuLID weight 0.85 + Redux 0.5 multiply 조합이 0.7/0.5 보다 우월 - Redux 0.3 너무 낮음, 0.7 비슷, 0.85+ 미검증 - Stage 3 Refiner 효과 미미 (48.5% → 48.82%, +0.3pp) CUDA error 회복: - 2-3, 2-4, 2-5 첫 시도 CUDA invalid argument - ComfyUI venv 재시작 후 retry → 3/3 모두 success - 매 ~5건 후 재시작 패턴 확인됨 자산 라이브러리: - models-performance: 8 모델 추적 - workflows: winner_auto 4 (R1-4, R2-1, R2-2, R2-4) + partial 5 - prompts/proven: 7 패턴 (R1, R2 합산) R3 계획: - 3-1: PuLID 0.7 + Redux 0.85 (push redux 더 강) - 3-2: PuLID 0.6 + Redux 0.7 (PuLID 약화) - 3-3: PuLID 0.7 + Redux 0.7 @ 1024x1792 (해상도 증가) - 3-4: Qwen-Image fp8 + Lightning LoRA 60갑자 (fp8 ~20G 완료, GGUF 회피) - 3-5: Pony V6 img2img from byeolyi-ref (대안 ID 방법) 검수: D:\Vault\8460s-image-rd\eval\meeting-103-v2.1-clean-grid.html
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<h1>meeting-103 v2.1 clean — R1+R2 그리드</h1>
<p class="subtitle">전체 10 조합 (10 성공)</p>
meeting-103 v2.1 clean R1 ✅5/5: PuLID + Redux = pastel 48.5% (R9 best 갱신) R0 환경 점검: - VRAM 11.7/12.4GB free (94%) — 해소 확인 - pytorch 2.12.0+cu130 + sageattention venv 검증 - 모델 인벤토리: Flux Dev Q5 GGUF, PuLID, Redux, byeolyi-ref-916 확보 - fp8 다운로드 .part 0 bytes (재개 대기) R1 clean 5조합 (5/5 success): - 1-1: PuLID w0.85 mean → pastel 25.7% / black 1.95% - 1-2: PuLID w0.85 mean delayed_start 0.05 → pastel 10.0% / black 14.0% (어두움) - 1-3: PuLID w1.0 mean → pastel 27.5% / black 0.79% - 1-4: PuLID w0.7 + Redux 0.5 → pastel 48.5% / black 0.27% ★ R1 best - 1-5: 한옥 baseline Flux Dev 768² → pastel 12.9% / black 11.7% CUDA error 회복: - 1-2 retry concat → CUDA invalid argument → 후속 1-2~1-5 모두 실패 - ComfyUI venv 재시작 (sage + pytorch 2.12) → 1-2 변형 (delayed_start)로 대체 - 재시도 4/4 모두 success 이전 R9 best (44.5%) → R1-4 (48.5%) = +4 pp 갱신 자산 라이브러리 누적: - models-performance.json: 7 모델 추적 (flux-dev, pulid-flux, flux-redux 등) - workflows: winner_auto 1 + partial 2 - prompts/proven: illustration_auto 패턴 3건 - prompts/failed: pastel-low + CUDA error 패턴 - prompts/negative: A_byeolyi 패턴 etc. 검수: - Vault: D:\Vault\8460s-image-rd\eval\meeting-103-v2.1-clean-grid.html - Gitea: results/meeting-103-v2.1-clean/round1/
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<div class="summary">
meeting-103 v2.1 clean R2 ✅5/5: PuLID 0.85+Redux 0.5 = pastel 49.99% (전체 best 갱신) R2 5조합 (5/5 success, retry 2회 포함): - 2-1: PuLID 0.7 + Redux 0.5 + Stage 3 Refiner (denoise 0.3) → 48.82% (Stage 3 효과 미미) - 2-2: PuLID 0.7 + Redux 0.7 → 48.93% - 2-3: PuLID 0.7 + Redux 0.3 → 38.52% (Redux 낮으면 파스텔 감소) - 2-4: PuLID 0.85 + Redux 0.5 → 49.99% ★ R2 best & 전체 best - 2-5: 한옥 spring (cherry blossom) → 44.45% / black 4.3% R1 best (R1-4 48.5%) → R2-4 (49.99%) = +1.5 pp 갱신 R9 legacy (44.5%) → R2-4 (49.99%) = +5.5 pp 누적 학습: - PuLID weight 0.85 + Redux 0.5 multiply 조합이 0.7/0.5 보다 우월 - Redux 0.3 너무 낮음, 0.7 비슷, 0.85+ 미검증 - Stage 3 Refiner 효과 미미 (48.5% → 48.82%, +0.3pp) CUDA error 회복: - 2-3, 2-4, 2-5 첫 시도 CUDA invalid argument - ComfyUI venv 재시작 후 retry → 3/3 모두 success - 매 ~5건 후 재시작 패턴 확인됨 자산 라이브러리: - models-performance: 8 모델 추적 - workflows: winner_auto 4 (R1-4, R2-1, R2-2, R2-4) + partial 5 - prompts/proven: 7 패턴 (R1, R2 합산) R3 계획: - 3-1: PuLID 0.7 + Redux 0.85 (push redux 더 강) - 3-2: PuLID 0.6 + Redux 0.7 (PuLID 약화) - 3-3: PuLID 0.7 + Redux 0.7 @ 1024x1792 (해상도 증가) - 3-4: Qwen-Image fp8 + Lightning LoRA 60갑자 (fp8 ~20G 완료, GGUF 회피) - 3-5: Pony V6 img2img from byeolyi-ref (대안 ID 방법) 검수: D:\Vault\8460s-image-rd\eval\meeting-103-v2.1-clean-grid.html
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전체 best pastel: <b>R2-2-4</b> PuLID 0.85 + Redux 0.5 = 49.99%<br>
R9 legacy best: 44.5% / R1 best: 48.5% (1-4 PuLID+Redux 0.5) / R2 best: 49.99% (2-4 PuLID 0.85+Redux 0.5)<br>
⚠ vision 검수 대기 (별이≥8 / 한자≥4.5 / 한옥≥4.5) — auto 지표는 proxy
meeting-103 v2.1 clean R1 ✅5/5: PuLID + Redux = pastel 48.5% (R9 best 갱신) R0 환경 점검: - VRAM 11.7/12.4GB free (94%) — 해소 확인 - pytorch 2.12.0+cu130 + sageattention venv 검증 - 모델 인벤토리: Flux Dev Q5 GGUF, PuLID, Redux, byeolyi-ref-916 확보 - fp8 다운로드 .part 0 bytes (재개 대기) R1 clean 5조합 (5/5 success): - 1-1: PuLID w0.85 mean → pastel 25.7% / black 1.95% - 1-2: PuLID w0.85 mean delayed_start 0.05 → pastel 10.0% / black 14.0% (어두움) - 1-3: PuLID w1.0 mean → pastel 27.5% / black 0.79% - 1-4: PuLID w0.7 + Redux 0.5 → pastel 48.5% / black 0.27% ★ R1 best - 1-5: 한옥 baseline Flux Dev 768² → pastel 12.9% / black 11.7% CUDA error 회복: - 1-2 retry concat → CUDA invalid argument → 후속 1-2~1-5 모두 실패 - ComfyUI venv 재시작 (sage + pytorch 2.12) → 1-2 변형 (delayed_start)로 대체 - 재시도 4/4 모두 success 이전 R9 best (44.5%) → R1-4 (48.5%) = +4 pp 갱신 자산 라이브러리 누적: - models-performance.json: 7 모델 추적 (flux-dev, pulid-flux, flux-redux 등) - workflows: winner_auto 1 + partial 2 - prompts/proven: illustration_auto 패턴 3건 - prompts/failed: pastel-low + CUDA error 패턴 - prompts/negative: A_byeolyi 패턴 etc. 검수: - Vault: D:\Vault\8460s-image-rd\eval\meeting-103-v2.1-clean-grid.html - Gitea: results/meeting-103-v2.1-clean/round1/
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</div>
<div class="grid">
<div class="cell status-success">
<img src="../results/meeting-103-v2.1-clean/round1/1-1_thumb.png" data-original="../results/meeting-103-v2.1-clean/round1/1-1.png" alt="1-1">
<div class="label">
meeting-103 v2.1 clean R2 ✅5/5: PuLID 0.85+Redux 0.5 = pastel 49.99% (전체 best 갱신) R2 5조합 (5/5 success, retry 2회 포함): - 2-1: PuLID 0.7 + Redux 0.5 + Stage 3 Refiner (denoise 0.3) → 48.82% (Stage 3 효과 미미) - 2-2: PuLID 0.7 + Redux 0.7 → 48.93% - 2-3: PuLID 0.7 + Redux 0.3 → 38.52% (Redux 낮으면 파스텔 감소) - 2-4: PuLID 0.85 + Redux 0.5 → 49.99% ★ R2 best & 전체 best - 2-5: 한옥 spring (cherry blossom) → 44.45% / black 4.3% R1 best (R1-4 48.5%) → R2-4 (49.99%) = +1.5 pp 갱신 R9 legacy (44.5%) → R2-4 (49.99%) = +5.5 pp 누적 학습: - PuLID weight 0.85 + Redux 0.5 multiply 조합이 0.7/0.5 보다 우월 - Redux 0.3 너무 낮음, 0.7 비슷, 0.85+ 미검증 - Stage 3 Refiner 효과 미미 (48.5% → 48.82%, +0.3pp) CUDA error 회복: - 2-3, 2-4, 2-5 첫 시도 CUDA invalid argument - ComfyUI venv 재시작 후 retry → 3/3 모두 success - 매 ~5건 후 재시작 패턴 확인됨 자산 라이브러리: - models-performance: 8 모델 추적 - workflows: winner_auto 4 (R1-4, R2-1, R2-2, R2-4) + partial 5 - prompts/proven: 7 패턴 (R1, R2 합산) R3 계획: - 3-1: PuLID 0.7 + Redux 0.85 (push redux 더 강) - 3-2: PuLID 0.6 + Redux 0.7 (PuLID 약화) - 3-3: PuLID 0.7 + Redux 0.7 @ 1024x1792 (해상도 증가) - 3-4: Qwen-Image fp8 + Lightning LoRA 60갑자 (fp8 ~20G 완료, GGUF 회피) - 3-5: Pony V6 img2img from byeolyi-ref (대안 ID 방법) 검수: D:\Vault\8460s-image-rd\eval\meeting-103-v2.1-clean-grid.html
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<div class="label-title">R1-1-1: A — PuLID weight 0.85 mean (first try)</div>
meeting-103 v2.1 clean R1 ✅5/5: PuLID + Redux = pastel 48.5% (R9 best 갱신) R0 환경 점검: - VRAM 11.7/12.4GB free (94%) — 해소 확인 - pytorch 2.12.0+cu130 + sageattention venv 검증 - 모델 인벤토리: Flux Dev Q5 GGUF, PuLID, Redux, byeolyi-ref-916 확보 - fp8 다운로드 .part 0 bytes (재개 대기) R1 clean 5조합 (5/5 success): - 1-1: PuLID w0.85 mean → pastel 25.7% / black 1.95% - 1-2: PuLID w0.85 mean delayed_start 0.05 → pastel 10.0% / black 14.0% (어두움) - 1-3: PuLID w1.0 mean → pastel 27.5% / black 0.79% - 1-4: PuLID w0.7 + Redux 0.5 → pastel 48.5% / black 0.27% ★ R1 best - 1-5: 한옥 baseline Flux Dev 768² → pastel 12.9% / black 11.7% CUDA error 회복: - 1-2 retry concat → CUDA invalid argument → 후속 1-2~1-5 모두 실패 - ComfyUI venv 재시작 (sage + pytorch 2.12) → 1-2 변형 (delayed_start)로 대체 - 재시도 4/4 모두 success 이전 R9 best (44.5%) → R1-4 (48.5%) = +4 pp 갱신 자산 라이브러리 누적: - models-performance.json: 7 모델 추적 (flux-dev, pulid-flux, flux-redux 등) - workflows: winner_auto 1 + partial 2 - prompts/proven: illustration_auto 패턴 3건 - prompts/failed: pastel-low + CUDA error 패턴 - prompts/negative: A_byeolyi 패턴 etc. 검수: - Vault: D:\Vault\8460s-image-rd\eval\meeting-103-v2.1-clean-grid.html - Gitea: results/meeting-103-v2.1-clean/round1/
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<div class="label-meta">models=flux-dev, pulid-flux, size=768×1344</div>
<div class="label-auto-eval">자동 평가:<br>pastel=25.65% / black=1.95%</div>
<div class="label-flags"><span class="flag flag-ok">clean</span></div>
</div>
</div>
<div class="cell status-success">
<img src="../results/meeting-103-v2.1-clean/round1/1-2_thumb.png" data-original="../results/meeting-103-v2.1-clean/round1/1-2.png" alt="1-2">
<div class="label">
meeting-103 v2.1 clean R2 ✅5/5: PuLID 0.85+Redux 0.5 = pastel 49.99% (전체 best 갱신) R2 5조합 (5/5 success, retry 2회 포함): - 2-1: PuLID 0.7 + Redux 0.5 + Stage 3 Refiner (denoise 0.3) → 48.82% (Stage 3 효과 미미) - 2-2: PuLID 0.7 + Redux 0.7 → 48.93% - 2-3: PuLID 0.7 + Redux 0.3 → 38.52% (Redux 낮으면 파스텔 감소) - 2-4: PuLID 0.85 + Redux 0.5 → 49.99% ★ R2 best & 전체 best - 2-5: 한옥 spring (cherry blossom) → 44.45% / black 4.3% R1 best (R1-4 48.5%) → R2-4 (49.99%) = +1.5 pp 갱신 R9 legacy (44.5%) → R2-4 (49.99%) = +5.5 pp 누적 학습: - PuLID weight 0.85 + Redux 0.5 multiply 조합이 0.7/0.5 보다 우월 - Redux 0.3 너무 낮음, 0.7 비슷, 0.85+ 미검증 - Stage 3 Refiner 효과 미미 (48.5% → 48.82%, +0.3pp) CUDA error 회복: - 2-3, 2-4, 2-5 첫 시도 CUDA invalid argument - ComfyUI venv 재시작 후 retry → 3/3 모두 success - 매 ~5건 후 재시작 패턴 확인됨 자산 라이브러리: - models-performance: 8 모델 추적 - workflows: winner_auto 4 (R1-4, R2-1, R2-2, R2-4) + partial 5 - prompts/proven: 7 패턴 (R1, R2 합산) R3 계획: - 3-1: PuLID 0.7 + Redux 0.85 (push redux 더 강) - 3-2: PuLID 0.6 + Redux 0.7 (PuLID 약화) - 3-3: PuLID 0.7 + Redux 0.7 @ 1024x1792 (해상도 증가) - 3-4: Qwen-Image fp8 + Lightning LoRA 60갑자 (fp8 ~20G 완료, GGUF 회피) - 3-5: Pony V6 img2img from byeolyi-ref (대안 ID 방법) 검수: D:\Vault\8460s-image-rd\eval\meeting-103-v2.1-clean-grid.html
2026-05-19 23:36:44 +09:00
<div class="label-title">R1-1-2: A — PuLID weight 0.85 mean delayed_start 0.05 (concat-replacement)</div>
meeting-103 v2.1 clean R1 ✅5/5: PuLID + Redux = pastel 48.5% (R9 best 갱신) R0 환경 점검: - VRAM 11.7/12.4GB free (94%) — 해소 확인 - pytorch 2.12.0+cu130 + sageattention venv 검증 - 모델 인벤토리: Flux Dev Q5 GGUF, PuLID, Redux, byeolyi-ref-916 확보 - fp8 다운로드 .part 0 bytes (재개 대기) R1 clean 5조합 (5/5 success): - 1-1: PuLID w0.85 mean → pastel 25.7% / black 1.95% - 1-2: PuLID w0.85 mean delayed_start 0.05 → pastel 10.0% / black 14.0% (어두움) - 1-3: PuLID w1.0 mean → pastel 27.5% / black 0.79% - 1-4: PuLID w0.7 + Redux 0.5 → pastel 48.5% / black 0.27% ★ R1 best - 1-5: 한옥 baseline Flux Dev 768² → pastel 12.9% / black 11.7% CUDA error 회복: - 1-2 retry concat → CUDA invalid argument → 후속 1-2~1-5 모두 실패 - ComfyUI venv 재시작 (sage + pytorch 2.12) → 1-2 변형 (delayed_start)로 대체 - 재시도 4/4 모두 success 이전 R9 best (44.5%) → R1-4 (48.5%) = +4 pp 갱신 자산 라이브러리 누적: - models-performance.json: 7 모델 추적 (flux-dev, pulid-flux, flux-redux 등) - workflows: winner_auto 1 + partial 2 - prompts/proven: illustration_auto 패턴 3건 - prompts/failed: pastel-low + CUDA error 패턴 - prompts/negative: A_byeolyi 패턴 etc. 검수: - Vault: D:\Vault\8460s-image-rd\eval\meeting-103-v2.1-clean-grid.html - Gitea: results/meeting-103-v2.1-clean/round1/
2026-05-19 23:17:19 +09:00
<div class="label-meta">models=flux-dev, pulid-flux, size=768×1344</div>
<div class="label-auto-eval">자동 평가:<br>pastel=9.99% / black=13.98%</div>
meeting-103 v2.1 clean R2 ✅5/5: PuLID 0.85+Redux 0.5 = pastel 49.99% (전체 best 갱신) R2 5조합 (5/5 success, retry 2회 포함): - 2-1: PuLID 0.7 + Redux 0.5 + Stage 3 Refiner (denoise 0.3) → 48.82% (Stage 3 효과 미미) - 2-2: PuLID 0.7 + Redux 0.7 → 48.93% - 2-3: PuLID 0.7 + Redux 0.3 → 38.52% (Redux 낮으면 파스텔 감소) - 2-4: PuLID 0.85 + Redux 0.5 → 49.99% ★ R2 best & 전체 best - 2-5: 한옥 spring (cherry blossom) → 44.45% / black 4.3% R1 best (R1-4 48.5%) → R2-4 (49.99%) = +1.5 pp 갱신 R9 legacy (44.5%) → R2-4 (49.99%) = +5.5 pp 누적 학습: - PuLID weight 0.85 + Redux 0.5 multiply 조합이 0.7/0.5 보다 우월 - Redux 0.3 너무 낮음, 0.7 비슷, 0.85+ 미검증 - Stage 3 Refiner 효과 미미 (48.5% → 48.82%, +0.3pp) CUDA error 회복: - 2-3, 2-4, 2-5 첫 시도 CUDA invalid argument - ComfyUI venv 재시작 후 retry → 3/3 모두 success - 매 ~5건 후 재시작 패턴 확인됨 자산 라이브러리: - models-performance: 8 모델 추적 - workflows: winner_auto 4 (R1-4, R2-1, R2-2, R2-4) + partial 5 - prompts/proven: 7 패턴 (R1, R2 합산) R3 계획: - 3-1: PuLID 0.7 + Redux 0.85 (push redux 더 강) - 3-2: PuLID 0.6 + Redux 0.7 (PuLID 약화) - 3-3: PuLID 0.7 + Redux 0.7 @ 1024x1792 (해상도 증가) - 3-4: Qwen-Image fp8 + Lightning LoRA 60갑자 (fp8 ~20G 완료, GGUF 회피) - 3-5: Pony V6 img2img from byeolyi-ref (대안 ID 방법) 검수: D:\Vault\8460s-image-rd\eval\meeting-103-v2.1-clean-grid.html
2026-05-19 23:36:44 +09:00
<div class="label-flags"><span class="flag flag-warn">black-suspicious</span><span class="flag flag-warn">pastel-low</span></div>
meeting-103 v2.1 clean R1 ✅5/5: PuLID + Redux = pastel 48.5% (R9 best 갱신) R0 환경 점검: - VRAM 11.7/12.4GB free (94%) — 해소 확인 - pytorch 2.12.0+cu130 + sageattention venv 검증 - 모델 인벤토리: Flux Dev Q5 GGUF, PuLID, Redux, byeolyi-ref-916 확보 - fp8 다운로드 .part 0 bytes (재개 대기) R1 clean 5조합 (5/5 success): - 1-1: PuLID w0.85 mean → pastel 25.7% / black 1.95% - 1-2: PuLID w0.85 mean delayed_start 0.05 → pastel 10.0% / black 14.0% (어두움) - 1-3: PuLID w1.0 mean → pastel 27.5% / black 0.79% - 1-4: PuLID w0.7 + Redux 0.5 → pastel 48.5% / black 0.27% ★ R1 best - 1-5: 한옥 baseline Flux Dev 768² → pastel 12.9% / black 11.7% CUDA error 회복: - 1-2 retry concat → CUDA invalid argument → 후속 1-2~1-5 모두 실패 - ComfyUI venv 재시작 (sage + pytorch 2.12) → 1-2 변형 (delayed_start)로 대체 - 재시도 4/4 모두 success 이전 R9 best (44.5%) → R1-4 (48.5%) = +4 pp 갱신 자산 라이브러리 누적: - models-performance.json: 7 모델 추적 (flux-dev, pulid-flux, flux-redux 등) - workflows: winner_auto 1 + partial 2 - prompts/proven: illustration_auto 패턴 3건 - prompts/failed: pastel-low + CUDA error 패턴 - prompts/negative: A_byeolyi 패턴 etc. 검수: - Vault: D:\Vault\8460s-image-rd\eval\meeting-103-v2.1-clean-grid.html - Gitea: results/meeting-103-v2.1-clean/round1/
2026-05-19 23:17:19 +09:00
</div>
</div>
<div class="cell status-success">
<img src="../results/meeting-103-v2.1-clean/round1/1-3_thumb.png" data-original="../results/meeting-103-v2.1-clean/round1/1-3.png" alt="1-3">
<div class="label">
meeting-103 v2.1 clean R2 ✅5/5: PuLID 0.85+Redux 0.5 = pastel 49.99% (전체 best 갱신) R2 5조합 (5/5 success, retry 2회 포함): - 2-1: PuLID 0.7 + Redux 0.5 + Stage 3 Refiner (denoise 0.3) → 48.82% (Stage 3 효과 미미) - 2-2: PuLID 0.7 + Redux 0.7 → 48.93% - 2-3: PuLID 0.7 + Redux 0.3 → 38.52% (Redux 낮으면 파스텔 감소) - 2-4: PuLID 0.85 + Redux 0.5 → 49.99% ★ R2 best & 전체 best - 2-5: 한옥 spring (cherry blossom) → 44.45% / black 4.3% R1 best (R1-4 48.5%) → R2-4 (49.99%) = +1.5 pp 갱신 R9 legacy (44.5%) → R2-4 (49.99%) = +5.5 pp 누적 학습: - PuLID weight 0.85 + Redux 0.5 multiply 조합이 0.7/0.5 보다 우월 - Redux 0.3 너무 낮음, 0.7 비슷, 0.85+ 미검증 - Stage 3 Refiner 효과 미미 (48.5% → 48.82%, +0.3pp) CUDA error 회복: - 2-3, 2-4, 2-5 첫 시도 CUDA invalid argument - ComfyUI venv 재시작 후 retry → 3/3 모두 success - 매 ~5건 후 재시작 패턴 확인됨 자산 라이브러리: - models-performance: 8 모델 추적 - workflows: winner_auto 4 (R1-4, R2-1, R2-2, R2-4) + partial 5 - prompts/proven: 7 패턴 (R1, R2 합산) R3 계획: - 3-1: PuLID 0.7 + Redux 0.85 (push redux 더 강) - 3-2: PuLID 0.6 + Redux 0.7 (PuLID 약화) - 3-3: PuLID 0.7 + Redux 0.7 @ 1024x1792 (해상도 증가) - 3-4: Qwen-Image fp8 + Lightning LoRA 60갑자 (fp8 ~20G 완료, GGUF 회피) - 3-5: Pony V6 img2img from byeolyi-ref (대안 ID 방법) 검수: D:\Vault\8460s-image-rd\eval\meeting-103-v2.1-clean-grid.html
2026-05-19 23:36:44 +09:00
<div class="label-title">R1-1-3: A — PuLID weight 1.0 mean</div>
meeting-103 v2.1 clean R1 ✅5/5: PuLID + Redux = pastel 48.5% (R9 best 갱신) R0 환경 점검: - VRAM 11.7/12.4GB free (94%) — 해소 확인 - pytorch 2.12.0+cu130 + sageattention venv 검증 - 모델 인벤토리: Flux Dev Q5 GGUF, PuLID, Redux, byeolyi-ref-916 확보 - fp8 다운로드 .part 0 bytes (재개 대기) R1 clean 5조합 (5/5 success): - 1-1: PuLID w0.85 mean → pastel 25.7% / black 1.95% - 1-2: PuLID w0.85 mean delayed_start 0.05 → pastel 10.0% / black 14.0% (어두움) - 1-3: PuLID w1.0 mean → pastel 27.5% / black 0.79% - 1-4: PuLID w0.7 + Redux 0.5 → pastel 48.5% / black 0.27% ★ R1 best - 1-5: 한옥 baseline Flux Dev 768² → pastel 12.9% / black 11.7% CUDA error 회복: - 1-2 retry concat → CUDA invalid argument → 후속 1-2~1-5 모두 실패 - ComfyUI venv 재시작 (sage + pytorch 2.12) → 1-2 변형 (delayed_start)로 대체 - 재시도 4/4 모두 success 이전 R9 best (44.5%) → R1-4 (48.5%) = +4 pp 갱신 자산 라이브러리 누적: - models-performance.json: 7 모델 추적 (flux-dev, pulid-flux, flux-redux 등) - workflows: winner_auto 1 + partial 2 - prompts/proven: illustration_auto 패턴 3건 - prompts/failed: pastel-low + CUDA error 패턴 - prompts/negative: A_byeolyi 패턴 etc. 검수: - Vault: D:\Vault\8460s-image-rd\eval\meeting-103-v2.1-clean-grid.html - Gitea: results/meeting-103-v2.1-clean/round1/
2026-05-19 23:17:19 +09:00
<div class="label-meta">models=flux-dev, pulid-flux, size=768×1344</div>
<div class="label-auto-eval">자동 평가:<br>pastel=27.51% / black=0.79%</div>
<div class="label-flags"><span class="flag flag-ok">clean</span></div>
</div>
</div>
<div class="cell status-success">
<img src="../results/meeting-103-v2.1-clean/round1/1-4_thumb.png" data-original="../results/meeting-103-v2.1-clean/round1/1-4.png" alt="1-4">
<div class="label">
meeting-103 v2.1 clean R2 ✅5/5: PuLID 0.85+Redux 0.5 = pastel 49.99% (전체 best 갱신) R2 5조합 (5/5 success, retry 2회 포함): - 2-1: PuLID 0.7 + Redux 0.5 + Stage 3 Refiner (denoise 0.3) → 48.82% (Stage 3 효과 미미) - 2-2: PuLID 0.7 + Redux 0.7 → 48.93% - 2-3: PuLID 0.7 + Redux 0.3 → 38.52% (Redux 낮으면 파스텔 감소) - 2-4: PuLID 0.85 + Redux 0.5 → 49.99% ★ R2 best & 전체 best - 2-5: 한옥 spring (cherry blossom) → 44.45% / black 4.3% R1 best (R1-4 48.5%) → R2-4 (49.99%) = +1.5 pp 갱신 R9 legacy (44.5%) → R2-4 (49.99%) = +5.5 pp 누적 학습: - PuLID weight 0.85 + Redux 0.5 multiply 조합이 0.7/0.5 보다 우월 - Redux 0.3 너무 낮음, 0.7 비슷, 0.85+ 미검증 - Stage 3 Refiner 효과 미미 (48.5% → 48.82%, +0.3pp) CUDA error 회복: - 2-3, 2-4, 2-5 첫 시도 CUDA invalid argument - ComfyUI venv 재시작 후 retry → 3/3 모두 success - 매 ~5건 후 재시작 패턴 확인됨 자산 라이브러리: - models-performance: 8 모델 추적 - workflows: winner_auto 4 (R1-4, R2-1, R2-2, R2-4) + partial 5 - prompts/proven: 7 패턴 (R1, R2 합산) R3 계획: - 3-1: PuLID 0.7 + Redux 0.85 (push redux 더 강) - 3-2: PuLID 0.6 + Redux 0.7 (PuLID 약화) - 3-3: PuLID 0.7 + Redux 0.7 @ 1024x1792 (해상도 증가) - 3-4: Qwen-Image fp8 + Lightning LoRA 60갑자 (fp8 ~20G 완료, GGUF 회피) - 3-5: Pony V6 img2img from byeolyi-ref (대안 ID 방법) 검수: D:\Vault\8460s-image-rd\eval\meeting-103-v2.1-clean-grid.html
2026-05-19 23:36:44 +09:00
<div class="label-title">R1-1-4: A — PuLID 0.7 + Redux 0.5</div>
meeting-103 v2.1 clean R1 ✅5/5: PuLID + Redux = pastel 48.5% (R9 best 갱신) R0 환경 점검: - VRAM 11.7/12.4GB free (94%) — 해소 확인 - pytorch 2.12.0+cu130 + sageattention venv 검증 - 모델 인벤토리: Flux Dev Q5 GGUF, PuLID, Redux, byeolyi-ref-916 확보 - fp8 다운로드 .part 0 bytes (재개 대기) R1 clean 5조합 (5/5 success): - 1-1: PuLID w0.85 mean → pastel 25.7% / black 1.95% - 1-2: PuLID w0.85 mean delayed_start 0.05 → pastel 10.0% / black 14.0% (어두움) - 1-3: PuLID w1.0 mean → pastel 27.5% / black 0.79% - 1-4: PuLID w0.7 + Redux 0.5 → pastel 48.5% / black 0.27% ★ R1 best - 1-5: 한옥 baseline Flux Dev 768² → pastel 12.9% / black 11.7% CUDA error 회복: - 1-2 retry concat → CUDA invalid argument → 후속 1-2~1-5 모두 실패 - ComfyUI venv 재시작 (sage + pytorch 2.12) → 1-2 변형 (delayed_start)로 대체 - 재시도 4/4 모두 success 이전 R9 best (44.5%) → R1-4 (48.5%) = +4 pp 갱신 자산 라이브러리 누적: - models-performance.json: 7 모델 추적 (flux-dev, pulid-flux, flux-redux 등) - workflows: winner_auto 1 + partial 2 - prompts/proven: illustration_auto 패턴 3건 - prompts/failed: pastel-low + CUDA error 패턴 - prompts/negative: A_byeolyi 패턴 etc. 검수: - Vault: D:\Vault\8460s-image-rd\eval\meeting-103-v2.1-clean-grid.html - Gitea: results/meeting-103-v2.1-clean/round1/
2026-05-19 23:17:19 +09:00
<div class="label-meta">models=flux-dev, pulid-flux, flux-redux, size=768×1344</div>
<div class="label-auto-eval">자동 평가:<br>pastel=48.5% / black=0.27%</div>
<div class="label-flags"><span class="flag flag-ok">clean</span></div>
</div>
</div>
<div class="cell status-success">
<img src="../results/meeting-103-v2.1-clean/round1/1-5_thumb.png" data-original="../results/meeting-103-v2.1-clean/round1/1-5.png" alt="1-5">
<div class="label">
meeting-103 v2.1 clean R2 ✅5/5: PuLID 0.85+Redux 0.5 = pastel 49.99% (전체 best 갱신) R2 5조합 (5/5 success, retry 2회 포함): - 2-1: PuLID 0.7 + Redux 0.5 + Stage 3 Refiner (denoise 0.3) → 48.82% (Stage 3 효과 미미) - 2-2: PuLID 0.7 + Redux 0.7 → 48.93% - 2-3: PuLID 0.7 + Redux 0.3 → 38.52% (Redux 낮으면 파스텔 감소) - 2-4: PuLID 0.85 + Redux 0.5 → 49.99% ★ R2 best & 전체 best - 2-5: 한옥 spring (cherry blossom) → 44.45% / black 4.3% R1 best (R1-4 48.5%) → R2-4 (49.99%) = +1.5 pp 갱신 R9 legacy (44.5%) → R2-4 (49.99%) = +5.5 pp 누적 학습: - PuLID weight 0.85 + Redux 0.5 multiply 조합이 0.7/0.5 보다 우월 - Redux 0.3 너무 낮음, 0.7 비슷, 0.85+ 미검증 - Stage 3 Refiner 효과 미미 (48.5% → 48.82%, +0.3pp) CUDA error 회복: - 2-3, 2-4, 2-5 첫 시도 CUDA invalid argument - ComfyUI venv 재시작 후 retry → 3/3 모두 success - 매 ~5건 후 재시작 패턴 확인됨 자산 라이브러리: - models-performance: 8 모델 추적 - workflows: winner_auto 4 (R1-4, R2-1, R2-2, R2-4) + partial 5 - prompts/proven: 7 패턴 (R1, R2 합산) R3 계획: - 3-1: PuLID 0.7 + Redux 0.85 (push redux 더 강) - 3-2: PuLID 0.6 + Redux 0.7 (PuLID 약화) - 3-3: PuLID 0.7 + Redux 0.7 @ 1024x1792 (해상도 증가) - 3-4: Qwen-Image fp8 + Lightning LoRA 60갑자 (fp8 ~20G 완료, GGUF 회피) - 3-5: Pony V6 img2img from byeolyi-ref (대안 ID 방법) 검수: D:\Vault\8460s-image-rd\eval\meeting-103-v2.1-clean-grid.html
2026-05-19 23:36:44 +09:00
<div class="label-title">R1-1-5: B — Hanok baseline Flux Dev 768²</div>
meeting-103 v2.1 clean R1 ✅5/5: PuLID + Redux = pastel 48.5% (R9 best 갱신) R0 환경 점검: - VRAM 11.7/12.4GB free (94%) — 해소 확인 - pytorch 2.12.0+cu130 + sageattention venv 검증 - 모델 인벤토리: Flux Dev Q5 GGUF, PuLID, Redux, byeolyi-ref-916 확보 - fp8 다운로드 .part 0 bytes (재개 대기) R1 clean 5조합 (5/5 success): - 1-1: PuLID w0.85 mean → pastel 25.7% / black 1.95% - 1-2: PuLID w0.85 mean delayed_start 0.05 → pastel 10.0% / black 14.0% (어두움) - 1-3: PuLID w1.0 mean → pastel 27.5% / black 0.79% - 1-4: PuLID w0.7 + Redux 0.5 → pastel 48.5% / black 0.27% ★ R1 best - 1-5: 한옥 baseline Flux Dev 768² → pastel 12.9% / black 11.7% CUDA error 회복: - 1-2 retry concat → CUDA invalid argument → 후속 1-2~1-5 모두 실패 - ComfyUI venv 재시작 (sage + pytorch 2.12) → 1-2 변형 (delayed_start)로 대체 - 재시도 4/4 모두 success 이전 R9 best (44.5%) → R1-4 (48.5%) = +4 pp 갱신 자산 라이브러리 누적: - models-performance.json: 7 모델 추적 (flux-dev, pulid-flux, flux-redux 등) - workflows: winner_auto 1 + partial 2 - prompts/proven: illustration_auto 패턴 3건 - prompts/failed: pastel-low + CUDA error 패턴 - prompts/negative: A_byeolyi 패턴 etc. 검수: - Vault: D:\Vault\8460s-image-rd\eval\meeting-103-v2.1-clean-grid.html - Gitea: results/meeting-103-v2.1-clean/round1/
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<div class="label-meta">models=flux-dev, size=768×1344</div>
<div class="label-auto-eval">자동 평가:<br>pastel=12.87% / black=11.67%</div>
meeting-103 v2.1 clean R2 ✅5/5: PuLID 0.85+Redux 0.5 = pastel 49.99% (전체 best 갱신) R2 5조합 (5/5 success, retry 2회 포함): - 2-1: PuLID 0.7 + Redux 0.5 + Stage 3 Refiner (denoise 0.3) → 48.82% (Stage 3 효과 미미) - 2-2: PuLID 0.7 + Redux 0.7 → 48.93% - 2-3: PuLID 0.7 + Redux 0.3 → 38.52% (Redux 낮으면 파스텔 감소) - 2-4: PuLID 0.85 + Redux 0.5 → 49.99% ★ R2 best & 전체 best - 2-5: 한옥 spring (cherry blossom) → 44.45% / black 4.3% R1 best (R1-4 48.5%) → R2-4 (49.99%) = +1.5 pp 갱신 R9 legacy (44.5%) → R2-4 (49.99%) = +5.5 pp 누적 학습: - PuLID weight 0.85 + Redux 0.5 multiply 조합이 0.7/0.5 보다 우월 - Redux 0.3 너무 낮음, 0.7 비슷, 0.85+ 미검증 - Stage 3 Refiner 효과 미미 (48.5% → 48.82%, +0.3pp) CUDA error 회복: - 2-3, 2-4, 2-5 첫 시도 CUDA invalid argument - ComfyUI venv 재시작 후 retry → 3/3 모두 success - 매 ~5건 후 재시작 패턴 확인됨 자산 라이브러리: - models-performance: 8 모델 추적 - workflows: winner_auto 4 (R1-4, R2-1, R2-2, R2-4) + partial 5 - prompts/proven: 7 패턴 (R1, R2 합산) R3 계획: - 3-1: PuLID 0.7 + Redux 0.85 (push redux 더 강) - 3-2: PuLID 0.6 + Redux 0.7 (PuLID 약화) - 3-3: PuLID 0.7 + Redux 0.7 @ 1024x1792 (해상도 증가) - 3-4: Qwen-Image fp8 + Lightning LoRA 60갑자 (fp8 ~20G 완료, GGUF 회피) - 3-5: Pony V6 img2img from byeolyi-ref (대안 ID 방법) 검수: D:\Vault\8460s-image-rd\eval\meeting-103-v2.1-clean-grid.html
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<div class="label-flags"><span class="flag flag-warn">black-suspicious</span></div>
</div>
</div>
<div class="cell status-success">
<img src="../results/meeting-103-v2.1-clean/round2/2-1_thumb.png" data-original="../results/meeting-103-v2.1-clean/round2/2-1.png" alt="2-1">
<div class="label">
<div class="label-title">R2-2-1: A — PuLID 0.7 + Redux 0.5 + Stage 3 Refiner (denoise 0.3)</div>
<div class="label-meta">models=flux-dev, pulid-flux, flux-redux, flux-dev-refiner, size=768×1344</div>
<div class="label-auto-eval">자동 평가:<br>pastel=48.82% / black=0.34%</div>
<div class="label-flags"><span class="flag flag-ok">clean</span></div>
</div>
</div>
<div class="cell status-success">
<img src="../results/meeting-103-v2.1-clean/round2/2-2_thumb.png" data-original="../results/meeting-103-v2.1-clean/round2/2-2.png" alt="2-2">
<div class="label">
<div class="label-title">R2-2-2: A — PuLID 0.7 + Redux 0.7</div>
<div class="label-meta">models=flux-dev, pulid-flux, flux-redux, size=768×1344</div>
<div class="label-auto-eval">자동 평가:<br>pastel=48.93% / black=0.46%</div>
<div class="label-flags"><span class="flag flag-ok">clean</span></div>
</div>
</div>
<div class="cell status-success">
<img src="../results/meeting-103-v2.1-clean/round2/2-3_thumb.png" data-original="../results/meeting-103-v2.1-clean/round2/2-3.png" alt="2-3">
<div class="label">
<div class="label-title">R2-2-3: A — PuLID 0.7 + Redux 0.3</div>
<div class="label-meta">models=flux-dev, pulid-flux, flux-redux, size=768×1344</div>
<div class="label-auto-eval">자동 평가:<br>pastel=38.52% / black=0.48%</div>
<div class="label-flags"><span class="flag flag-ok">clean</span></div>
</div>
</div>
<div class="cell status-success">
<img src="../results/meeting-103-v2.1-clean/round2/2-4_thumb.png" data-original="../results/meeting-103-v2.1-clean/round2/2-4.png" alt="2-4">
<div class="label">
<div class="label-title">R2-2-4: A — PuLID 0.85 + Redux 0.5</div>
<div class="label-meta">models=flux-dev, pulid-flux, flux-redux, size=768×1344</div>
<div class="label-auto-eval">자동 평가:<br>pastel=49.99% / black=0.18%</div>
<div class="label-flags"><span class="flag flag-ok">clean</span></div>
</div>
</div>
<div class="cell status-success">
<img src="../results/meeting-103-v2.1-clean/round2/2-5_thumb.png" data-original="../results/meeting-103-v2.1-clean/round2/2-5.png" alt="2-5">
<div class="label">
<div class="label-title">R2-2-5: B — Hanok spring variant (cherry blossom)</div>
<div class="label-meta">models=flux-dev, size=768×1344</div>
<div class="label-auto-eval">자동 평가:<br>pastel=44.45% / black=4.3%</div>
<div class="label-flags"><span class="flag flag-ok">clean</span></div>
meeting-103 v2.1 clean R1 ✅5/5: PuLID + Redux = pastel 48.5% (R9 best 갱신) R0 환경 점검: - VRAM 11.7/12.4GB free (94%) — 해소 확인 - pytorch 2.12.0+cu130 + sageattention venv 검증 - 모델 인벤토리: Flux Dev Q5 GGUF, PuLID, Redux, byeolyi-ref-916 확보 - fp8 다운로드 .part 0 bytes (재개 대기) R1 clean 5조합 (5/5 success): - 1-1: PuLID w0.85 mean → pastel 25.7% / black 1.95% - 1-2: PuLID w0.85 mean delayed_start 0.05 → pastel 10.0% / black 14.0% (어두움) - 1-3: PuLID w1.0 mean → pastel 27.5% / black 0.79% - 1-4: PuLID w0.7 + Redux 0.5 → pastel 48.5% / black 0.27% ★ R1 best - 1-5: 한옥 baseline Flux Dev 768² → pastel 12.9% / black 11.7% CUDA error 회복: - 1-2 retry concat → CUDA invalid argument → 후속 1-2~1-5 모두 실패 - ComfyUI venv 재시작 (sage + pytorch 2.12) → 1-2 변형 (delayed_start)로 대체 - 재시도 4/4 모두 success 이전 R9 best (44.5%) → R1-4 (48.5%) = +4 pp 갱신 자산 라이브러리 누적: - models-performance.json: 7 모델 추적 (flux-dev, pulid-flux, flux-redux 등) - workflows: winner_auto 1 + partial 2 - prompts/proven: illustration_auto 패턴 3건 - prompts/failed: pastel-low + CUDA error 패턴 - prompts/negative: A_byeolyi 패턴 etc. 검수: - Vault: D:\Vault\8460s-image-rd\eval\meeting-103-v2.1-clean-grid.html - Gitea: results/meeting-103-v2.1-clean/round1/
2026-05-19 23:17:19 +09:00
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