Clips Studio Copyright (C) 2026 ColinGPT9 This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details. You should have received a copy of the GNU Affero General Public License along with this program. If not, see . The full text is in LICENSE. ------------------------------------------------------------------------------- What this means if you are just using the app ------------------------------------------------------------------------------- Nothing changes for you. Download it, install it, clip your streams, post the clips, make money from them. The AGPL places obligations on people who DISTRIBUTE the software or run a MODIFIED version as a network service — not on people who use it. Your videos and your clips are yours; the licence has nothing to say about them. If you modify Clips Studio and give that modified version to someone else, or run it as a service other people use over a network, you have to offer them the source of your modified version under this same licence. ------------------------------------------------------------------------------- Parts under other licences ------------------------------------------------------------------------------- The plugin SDK in sdk/python/ (clipskitty_sdk, which the installer also bundles so plugins can import it) is MIT-licensed; its notice is in sdk/python/LICENSE and travels with it. The example plugins in examples/pipelines/scene-cut-highlights/ and examples/pipelines/keyword-rater/ are MIT as well, and the copy of the Awesome Clips Kitty list in plugins/catalog_index.json is CC0-1.0, as is the list itself (github.com/ColinGPT9/awesome-clips-kitty). Plugins, pipelines and apps made by other people keep their own licences; installing one does not change it, and nothing here changes theirs. ------------------------------------------------------------------------------- Why a copyleft licence ------------------------------------------------------------------------------- It keeps improvements to the tool available to the creators it was written for, rather than allowing a closed fork of the same work to be sold back to them. ------------------------------------------------------------------------------- Third-party components ------------------------------------------------------------------------------- The Windows installer bundles the Python engine and its dependencies. The significant ones, with their licences: ultralytics (YOLOv8) AGPL-3.0 pose/face tracking + model weights TalkNet-ASD MIT active speaker detection; the model code is vendored unmodified under third_party/talknet/ (c) 2021 Tao Ruijie, and its pretrained weights are fetched by scripts/fetch_asd_model.py PANNs (Qiuqiang Kong) MIT game sounds; the MobileNetV1 network is adapted in analysis/panns.py (c) 2018-2020 Qiuqiang Kong, and its pretrained weights (Zenodo 3987831) are CC BY 4.0, fetched by scripts/fetch_panns.py. AudioSet's class names (config/ audioset_labels.txt) are CC BY 4.0, Google E-BARD detection models CC BY 4.0 the basketball, the hoop and the players, for basketball's 9:16 framing (sports/basketball/crop/sources.py); the YOLOv8n weights (huggingface.co/ GabrieleGiudici/E-BARD-detection- models, revision 3f4789c), unmodified, fetched by scripts/ fetch_basketball_model.py. Trained with ultralytics, so its AGPL-3.0 terms apply as to the YOLOv8 weights; full attribution below pyannote segmentation-3.0 MIT who is talking when, for the second speaker's caption colour (analysis/ voice_turns.py); (c) 2022 CNRS, the ONNX export is sherpa-onnx's (k2-fsa), fetched by scripts/fetch_voice_model.py WeSpeaker ResNet34-LM CC BY 4.0 whose voice a turn is, for the same; pretrained on VoxCeleb by the WeSpeaker team (huggingface.co/ Wespeaker/wespeaker-voxceleb- resnet34-LM), unmodified, fetched by scripts/fetch_voice_model.py RapidOCR Apache-2.0 on-screen text in a gaming stream; its bundled PaddleOCR models are Apache-2.0 (PaddlePaddle) faster-whisper MIT transcription; its model weights are fetched by scripts/fetch_whisper.py and are MIT (Systran/faster-whisper, converted from OpenAI Whisper) keyring MIT OS-protected Connected Accounts tokens on Linux and macOS only; Windows uses DPAPI, and keyring isn't installed there websockets BSD-3-Clause desktop Twitch EventSub connections Ollama MIT the local AI runtime, bundled unmodified and fetched at build time by scripts/fetch_ollama.py PyTorch BSD-3-Clause tensor runtime, CUDA libraries OpenCV (opencv-python) Apache-2.0 frame decoding and analysis yt-dlp Unlicense downloading source videos yt-dlp-ejs Unlicense, YouTube player solver scripts, for the MIT, ISC YouTube cookies fallback only QuickJS-ng MIT runs those scripts; bundled unmodified and fetched at build time by scripts/fetch_quickjs.py FFmpeg see below all encoding, decoding and muxing FastAPI / Uvicorn MIT the local API the desktop app talks to Electron MIT the desktop shell React MIT the interface Material Icons Apache-2.0 a few icon shapes in the layout editor's platform preview (Google) Lucide ISC a few icon shapes in the same preview; both notices are in third_party/icons/NOTICE.md The E-BARD detection model (https://github.com/GabrieleGiudic/E-BARD) is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0, https://creativecommons.org/licenses/by/4.0/). Clips Kitty uses its YOLOv8n weights unmodified: model https://huggingface.co/GabrieleGiudici/E-BARD-detection-models code https://github.com/GabrieleGiudic/E-BARD dataset https://huggingface.co/datasets/GabrieleGiudici/E-BARD-detection E-BARD extends BARD: G. Giudici, A. Maurino and P. Zuccolotto, "BARD: A Basketball Action Recognition Dataset for multi-label classification", Computer Vision and Image Understanding 267 (2026) 104713, https://doi.org/10.1016/j.cviu.2026.104713. FFmpeg is fetched at build time by scripts/fetch_ffmpeg.py rather than kept in this repository. The builds used are LGPL-2.1-or-later, or GPL-2.0-or-later where they include GPL-licensed components; the exact terms ship with the binary in the installer. Ollama is fetched at build time by scripts/fetch_ollama.py rather than kept in this repository, and ships unmodified. Its MIT licence travels with it in the installer as README-OLLAMA.txt. The language models Ollama runs are NOT bundled. The app downloads the one it needs on first launch, and each carries its own licence — Gemma, for example, is covered by the Gemma Terms of Use rather than by anything here. That is also why they are downloaded rather than shipped: redistributing them would mean accepting those terms on every user's behalf. ------------------------------------------------------------------------------- Commercial licensing ------------------------------------------------------------------------------- If the AGPL does not suit your use, ask. The copyright is held by one person, which means a different arrangement is possible without collecting agreements from a hundred contributors.