OpenShot-ComfyUI provides production-focused ComfyUI nodes built for OpenShot integration, with a strong focus on reliable SAM2 workflows for longer videos.

The goal is simple: make advanced segmentation and video analysis features feel native inside OpenShot's UI, while keeping the underlying Comfy graphs stable, predictable, and memory-safe.

Why this exists

OpenShot needs SAM2 pipelines that can handle real-world clips, not just short demos.

Many SAM2 custom-node workflows process or retain full-video state in ways that become fragile or memory-heavy as clip length grows. In practice, that can lead to slowdowns, failures, or OOM behavior on longer timelines.

This project addresses that gap with chunk-oriented processing designed specifically for OpenShot's planned UI integration path.

How this works

Keep node interfaces close to standard ComfyUI types and patterns.
Process video segmentation in bounded chunks instead of retaining full-video mask history.
Return outputs that are easier for OpenShot to consume and orchestrate in larger editing workflows.
Include practical companion nodes (GroundingDINO + TransNetV2) that support automated, timeline-aware tooling.

What this includes (V1)

OpenShotDownloadAndLoadSAM2Model
OpenShotSam2Segmentation (single-image)
OpenShotSam2VideoSegmentationAddPoints
OpenShotSam2VideoSegmentationChunked (meta-batch/chunk friendly)
OpenShotGroundingDinoDetect (text-prompted object detection -> mask + JSON)
OpenShotTransNetSceneDetect (direct TransNetV2 inference -> IN/OUT JSON ranges)
OpenShotDeepFilterNetDenoiseAudio (file-path based audio denoise -> FLAC path)
OpenShotAudioSRClarity (isolated AudioSR runner -> FLAC path)

Attribution

This project is inspired by and partially based on ideas and APIs from:

kijai/ComfyUI-segment-anything-2
Meta SAM2 research/code

Please see upstream projects for full original implementations and credits.

Requirements

ComfyUI
PyTorch (as used by your Comfy install)
ffmpeg and ffprobe available on your PATH

Install this node pack into ComfyUI/custom_nodes/OpenShot-ComfyUI and restart ComfyUI.

Quick install (copy/paste)

Install this node pack's Python dependencies:

python -m pip install -r requirements.txt

Install SAM2 separately:

python -m pip install --no-build-isolation git+https://github.com/facebookresearch/sam2.git

Validate the environment:

python validate.py

Restart ComfyUI after install.

validate.py supports two cases:

On a regular laptop/dev environment, it validates the Python packages plus ffmpeg/ffprobe
Inside the actual ComfyUI Python environment, it also validates Comfy imports and node registration

If you run it in the ComfyUI environment and it passes, restart ComfyUI and the nodes should load.

SAM2 is installed separately on purpose. Keeping it out of requirements.txt makes the normal dependency install much more reliable and avoids long hangs during pip's build-isolation step.

First-use model downloads

OpenShotDownloadAndLoadSAM2Model downloads supported SAM2 checkpoints into ComfyUI/models/sam2 on first use.
OpenShotGroundingDinoDetect downloads model weights from Hugging Face on first use and uses the normal HF cache.
OpenShotDeepFilterNetDenoiseAudio downloads the default DeepFilterNet3 model on first use using DeepFilterNet's cache directory.
OpenShotAudioSRClarity creates an isolated local venv on first use, installs AudioSR there, and then downloads the selected AudioSR checkpoint from Hugging Face on first run.
OpenShotTransNetSceneDetect does not require a separate manual weight download from this node pack.

Audio denoise node

OpenShotDeepFilterNetDenoiseAudio is intentionally minimal:

Input: source_audio_path, noise_reduction, keep_model_loaded
Output: a new FLAC file path
The node uses the upstream DeepFilterNet package and blends the enhanced result with the original signal using noise_reduction from 0.0 to 1.0
0.0 means "keep the original audio" and still emits a FLAC copy
1.0 means "full denoise"

The node accepts typical audio formats that ffmpeg can decode and always writes a new .flac file into ComfyUI's output folder under openshot_audio/.

Audio clarity node

OpenShotAudioSRClarity is intended for low-fidelity or bandwidth-limited audio:

Input: source_audio_path or audio, model_name, keep_model_loaded
Output: a new FLAC file path
model_name=speech is intended for spoken voice
model_name=basic is intended for music and sound effects

AudioSR is intentionally not installed into the main Comfy environment because its package pins older numpy, librosa, and transformers versions. Instead, the node creates and uses an isolated runner environment on first use so the main Comfy environment stays stable. That means there is no extra install command for AudioSR, but the first Clarity run will take longer while the isolated environment and model checkpoint are prepared.

Validation script

Run:

python validate.py

It checks:

required Python imports
DeepFilterNet compatibility through the bundled runner shim
ffmpeg and ffprobe
ComfyUI-side imports needed for node registration, when ComfyUI is available
that the expected node classes are present, when ComfyUI is available

Notes

OpenShotSam2VideoSegmentationChunked returns only the requested chunk range (bounded memory) instead of collecting whole-video masks.
For very long videos, pair chunked outputs with batch-safe downstream nodes (VHS meta-batch, staged processing, or on-disk intermediates).
torchaudio is listed explicitly because DeepFilterNet imports it internally and some environments do not pull it in automatically.
AudioSR uses a separate on-demand runner environment to avoid downgrading shared Comfy dependencies.

Licensed under the GNU General Public License v3.0 (GPLv3). See LICENSE.md for the full license text.