OpenImagingLab / OpenImagingLab/FlashVSR

ComfyUI-FlashVSR_Stable v.1.2

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Python
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Description

High-performance Video Super Resolution for ComfyUI with VRAM optimization.

Run FlashVSR on 8GB-24GB+ GPUs without artifacts. Features intelligent resource management, 5 VAE options, and auto-downloading models.

[1.2.0] - 2025-12-23

✨ New Features

5 New VAE Models: Added support for Wan2.2, LightVAE_W2.1, TAE_W2.2, LightTAE_HY1.5 (plus original Wan2.1).
Smart Resource Calculator: Added "Pre-flight" check to analyze VRAM/RAM usage and recommend optimal settings before processing.
Auto-Download: Added automatic downloading for missing VAE models from HuggingFace (lightx2v/Autoencoders repository).
Unified UI: Replaced complex vae_type and alt_vae inputs with a single vae_model dropdown.

🐛 Bug Fixes

Fixed Black Borders: Implemented correct "Padding → Process → Crop" logic to handle VAE dimension requirements without corrupting the output.
Fixed Video Glitches: Corrected Tensor Permutation logic (B,C,F,H,W vs B,H,W,C) to prevent visual artifacts.
Fixed Model Loading: Solved the issue where selecting "Wan2.2" incorrectly loaded "Wan2.1_VAE.pth".
Fixed OOM False Positive: OOM recovery no longer triggers prematurely (adjusted threshold to 95%).

⚡ Optimization

Unified Pipeline: Merged tiny, full, and tiny-long logic into a single optimized architecture.
OOM Protection: Improved memory management with 95% VRAM threshold using torch.cuda.mem_get_info().
Lossless Resize: Uses NEAREST interpolation for integer scaling (0.5, 0.25) to avoid blur.
Aggressive Garbage Collection: Added torch.cuda.empty_cache() before/after heavy VAE operations.

🛠 Refactoring

Explicit VAE Instantiation: No more state_dict inspection/guessing - strict class mapping based on user selection.
VAE_MODEL_MAP: Centralized configuration for all 5 VAE options (class, file, URL, dimensions).
Summary Logging: End-of-processing report with total time, peak VRAM, and resolutions.
Debug Logging: Shows selected_model vs loaded_model_path for verification.

[1.1.0] - 2025-12-22

🚀 New Features

Wan2.2 VAE Support: Integrated Wan2.2 VAE with optimized normalization statistics.
LightX2V VAE Integration: Added LightX2V VAE for ~50% VRAM reduction and 2-3x faster inference.
VAE Type Selection: Added vae_model dropdown in both Init Pipeline and Ultra-Fast nodes.
Factory Function: Added create_video_vae() for programmatic VAE selection.

⚡ Performance

VRAM Reduction: LightX2V reduces peak VRAM usage by approximately 50%.
Speed Improvement: LightX2V provides 2-3x faster VAE decode times.

🛠 Refactoring

Backward Compatibility: All new VAE types maintain full compatibility with existing Wan2.1 weights.
Architecture Constants: Added VAE_FULL_DIM, VAE_LIGHT_DIM, VAE_Z_DIM for clarity.

https://github.com/naxci1/ComfyUI-FlashVSR_Stable

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Review the linked ComfyUI-FlashVSR_Stable repository and compare its 1.2.0 changes with this project. The issue names no files, tests, or requested change, so confirm with maintainers whether it is intended as a feature proposal or release note before starting; no completion criterion is stated.

Written by the indexing model from the issue text.

Assessment

Tech stack
python, pytorch
Domain
computer-vision, machine-learning
Issue type
Documentation
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
15/100

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