feat: enforce held-out benchmark workflow

feat: add model quality workflow gate

docs: complete 100% bug backlog audit and update handover.md

feat: add master system verification test suite test_all.py with 100% pass rate and exit code 0

feat: complete Phase 6 Stage II Transformer fine-tuning setup and verification with exit code 0

feat: verify Phase 7 A/B Model & Preset Pipeline with exit code 0

feat: verify Phase 4 Dataset Expansion & Game Character Mixing with exit code 0

feat: verify Phase 3 ArcFace Identity Loss integration with exit code 0

docs: update handover.md with Phase 5 empirical benchmark verification results

feat: add Rule 11 (Mandatory Git Push), DirectML/OpenVINO EP ONNX, 1-Click Presets, Organ-Based Toggles, AI Quality Score & Multi-Scale Adaptive Sharpening

docs: update handover log with Tasks 17, 18, 19 accomplishments

docs: update handover.md and add dynamic fallback verification to quantize_onnx_static.py

docs: update handover.md with Task 15 details

fix: resolve all 9 codebase bugs (B1-B9) & add Rule 9 to AGENTS.md

docs: update handover Task 13 — Phase 1 complete, Phase 2 training started

fix: prevent infinite thread spawn when image is uploaded (polling loop guard)

fix: patch B2, B6, B10, B12 (ONNX tiling upscaler, start_time guard, cache split screen comparison, list css style)

fix: patch B3 and B4 (ONNX mutex lock and async batch processing queue)

docs: update bug backlog status in handover.md to reflect fixed tasks (B1, B5, B7, B8, B9)

docs: add Task 11 full bug audit backlog with 12 bugs and fix guidance to handover.md

fix: disable CORS and XsrfProtection on streamlit run command to resolve Axios 403 error on hugging face upload

docs: mark Task 10 as completed in handover.md with final applied changes

fix: resolve streamlit thread safety issues and cache face helper to optimize cpu

Optimize CPU performance: add INT8 quantization, set default lightweight detector, disable heavy upscaling by default

fix: make CPU training run (disable mkldnn, cv2 filter2D, num_block=6, gt=256, LMDB) + handover

perf: maximize CPU/RAM/disk for CPU training (LMDB, avx512, larger batch/queue)

feat: optimize CPU performance and add agents rules

feat: add Google Colab GPU notebook, ONNX export script, and pipeline ONNX optimization

feat: implement custom training configurations and runner script for model improvement

feat: integrate Real-ESRGAN background upscaling and face detection threshold

chore: add Dockerfile for Hugging Face Spaces Docker SDK deployment

chore: configure repository for Hugging Face Spaces Streamlit deployment

feat: build premium Streamlit UI for local AI enhancement control

feat: implement custom enhancement pipeline with adjustable soft blending

feat: clone CodeFormer, download pretrained weights, and verify imports

feat: initialize project, setup virtual env, and resolve basicsr dependency