Proxy Labs: third-party notices (copy of NOTICES.md in the source repository) # Third-Party Notices and AI Model Licences Proxy Labs uses third-party open-source components and local machine-learning models. This document contains required copyright, attribution, and licence notices. --- ## 1. Machine Learning Models Proxy Labs executes machine learning models **strictly on the user's local hardware**. No models or user media are hosted or processed on remote cloud servers. ### YuNet Face Detection - **Purpose:** Fast face detection and 5-point facial landmark localisation. - **Source:** [OpenCV Zoo - YuNet](https://github.com/opencv/opencv_zoo/tree/main/models/face_detection_yunet) - **Licence:** MIT License ```text Copyright (C) 2021-2023, Shiqi Yu, all rights reserved. Copyright (C) 2022-2023, OpenCV, all rights reserved. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ``` --- ### SFace Face Recognition - **Purpose:** Extraction of 128-dimensional facial feature embeddings for clustering within a shoot. - **Source:** [OpenCV Zoo - SFace](https://github.com/opencv/opencv_zoo/tree/main/models/face_recognition_sface) / [Zhong et al., 2021] - **Licence:** Apache License, Version 2.0 ```text Copyright (c) 2021, OpenCV. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ``` --- ### YAMNet Audio Classifier - **Purpose:** Audio event classification (speech, applause, laughter, cheering, music). - **Source:** [Google TensorFlow AudioSet Models](https://github.com/tensorflow/models/tree/master/research/audioset/yamnet) - **Licence (Model Weights & Code):** Apache License, Version 2.0 ```text Copyright 2019 The TensorFlow Authors. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ``` - **Licence (AudioSet Ontology & Labels):** Creative Commons Attribution 4.0 International (CC BY 4.0) - J. F. Gemmeke, D. P. W. Ellis, et al., "Audio Set: An ontology and human-labeled dataset for audio events", Proc. IEEE ICASSP 2017. - Full licence text: https://creativecommons.org/licenses/by/4.0/ --- ### Whisper Speech-to-Text - **Purpose:** Multilingual background speech recognition for vows and toasts. - **Source:** [OpenAI Whisper](https://github.com/openai/whisper) and [whisper.cpp](https://github.com/ggerganov/whisper.cpp) by Georgi Gerganov. - **Licence:** MIT License ```text MIT License Copyright (c) 2022 OpenAI Copyright (c) 2023 Georgi Gerganov Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ``` --- ## 2. Key Runtimes & External Tools ### ONNX Runtime - **Copyright:** Microsoft Corporation - **Licence:** MIT License - **Purpose:** Execution engine for YuNet, SFace, and YAMNet neural network inference. ### FFmpeg (External Tool) - **Licence:** GNU Lesser General Public License (LGPL) v2.1+ / GNU General Public License (GPL) v2+. - **Compliance Notice:** Proxy Labs does not embed, statically link, or distribute FFmpeg binaries. FFmpeg is executed strictly as a standalone, independent external process via standard operating system process execution (`firstpass::util::command("ffmpeg")`). Users acquire FFmpeg independently through standard package managers (e.g., `winget` on Windows or `brew` on macOS) under its respective open-source licence. --- ## 3. Rust Open-Source Crates FirstPass builds upon crates from the Rust ecosystem, including: - `egui` (MIT / Apache-2.0) — GUI framework by Emil Ernerfeldt - `rayon` (MIT / Apache-2.0) — Data parallelism library - `serde`, `serde_json` (MIT / Apache-2.0) — Serialization framework - `image` (MIT / Apache-2.0) — Image decoding - `rubato`, `rustfft` (MIT) — Audio resampling and FFT operations - `ort` (MIT / Apache-2.0) — Safe ONNX Runtime bindings For a comprehensive list of crate dependencies and version trees, refer to `Cargo.lock`.