OpenImagingLab / OpenImagingLab/FlashVSR
ComfyUI-FlashVSR Stable version
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- Dominant language
- Python
- Stars
- 1.9k
- Forks
- 152
- PR merge metrics
- No merged PRs in 30d
Description
### Running FlashVSR on lower VRAM without any artifacts.
### 08.12.2025
Optimization: Ported all VRAM optimizations and Tiled VAE support to tiny-long mode, ensuring feature parity across all modes.
Performance: Optimized for Windows environments (speed improvements).
Update: General codebase cleanup and synchronization.
### 07.12.2025
VRAM Optimization: Implemented auto-fallback for process_chunk. If OOM occurs, it automatically retries with tiled_vae=True and then tiled_dit=True, preventing crashes.
Critical Fix: Fixed a bug in the non-tiled processing path where output was undefined.
Optimization: Defer VAE loading in full mode until strictly necessary, significantly reducing peak VRAM usage.
Optimization: Added a proactive 90% VRAM usage warning.
Refactor: Rewrote progress bar to use single-line in-place updates (\r) for cleaner console output.
Defaults: Updated default settings for FlashVSR Ultra-Fast node to be safer for 16GB cards (unload_dit=True, tiled options enabled).
Bug Fix: Fixed AttributeError in full mode by adding a fallback mechanism to manually load the VAE model if the model manager fails.
Bug Fix: Fixed the progress bar to correctly display status in ComfyUI using the cqdm wrapper. Added text-based progress bar to logs.
Sync: Enabled VAE spatial tiling for tiny mode, bringing VRAM savings from tiny-long to the standard fast pipeline.
Documentation: Expanded tooltips for all node parameters and added detailed usage instructions to README.
New Feature: Added frame_chunk_size option to split large videos into chunks, enabling processing of large files on limited VRAM by offloading to CPU.
Enhancement: Improved logging to show detailed resource usage (RAM, Peak VRAM, per-step timing) and model configuration details.
Optimization: Added torch.cuda.ipc_collect() for better memory cleanup.
New Feature: Added attention_mode selection with support for flash_attention_2, sdpa, sparse_sage, and block_sparse backends.
Refactor: Cleaned up code and improved error handling for imports.
### 06.12.2025
Bug Fix: Fixed a shape mismatch error for small input frames by implementing correct padding logic.
Optimization: VRAM is now immediately freed at the start of processing to prevent OOM errors.
New Feature: Added enable_debug option for extensive logging.
New Feature: Added keep_models_on_cpu option to keep models in RAM (CPU) instead of VRAM.
Enhancement: Added accurate FPS calculation and peak VRAM reporting.
Optimization: Replaced einops operations with native PyTorch ops.
Optimization: Added "Conv3d memory workaround".
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue points to the external ComfyUI-FlashVSR repository and lists optimizations, bug fixes, and new options rather than naming files or tests in FlashVSR. Start by determining whether the referenced implementation is intended to be ported here; done is undefined until the target scope and acceptance checks for a stable version are specified.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-vision, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100