add readme, liscence and use public KPN

README.md

@@ -45,17 +45,23 @@ Optional flags:
 
 ## Models
 
-Download the required ONNX models:
+The ONNX model weights live in `models/` (tracked via Git LFS):
+- `arcface_w600k_r50.onnx` — primary ArcFace embedder
+- `arcface_w600k_mbf.onnx`, `arcface_r18.onnx` — lighter alternatives
+- `face_detection_yunet_2023mar.onnx` — YuNet face detector
+- `scrfd_500m_bnkps.onnx` — SCRFD face detector
+
+If they are missing (e.g. LFS not fetched), re-download them with:
 
 ```bash
 bash scripts/download_models.sh
 ```
 
-Models are placed in `external/`:
-- `arcface_w600k_r50.onnx` — primary ArcFace embedder
-- `arcface_w600k_mbf.onnx`, `arcface_r18.onnx` — lighter alternatives
-- `face_detection_yunet_2023mar.onnx` — YuNet face detector
-- `scrfd_500m_bnkps.onnx` — SCRFD face detector
+> **Model licensing:** the model weights carry their own licenses, separate
+> from this project's MIT license, and are redistributed here under those
+> upstream terms. Several — notably the InsightFace "buffalo" models (ArcFace /
+> SCRFD) — are licensed for **non-commercial research use only**. Review and
+> comply with each model's license before use.
 
 ## Binaries
 
@@ -154,8 +160,9 @@ Anything after `--` is passed through to `scene_analyze` unchanged. Pass
 `--no-filter` to use the gallery as-is (skip per-title cast filtering), or
 `--item-id` instead of `--title` to skip the search.
 
-After a successful run, the output JSON is pushed to the JRay Jellyfin
-plugin's Truth endpoint (`PUT /Plugins/JRay/Items/{itemId}/Truth`) so
+After a successful run, the output JSON is pushed to the [JRay Jellyfin
+plugin](https://gitea.tourolle.paris/dtourolle/jRay)'s Truth endpoint
+(`PUT /Plugins/JRay/Items/{itemId}/Truth`) so
 Jellyfin picks it up immediately, using `--api-key` (must be an
 **Administrator** key for the push to succeed). Pass `--no-push` to skip
 this and only write `--output` locally (e.g. for local debugging).
@@ -208,3 +215,13 @@ Debug/preview branches fan out automatically from `identity_matcher`.
 ## Evaluation
 
 Scripts in `eval/` and `scripts/movienet_*.py` support benchmarking against the MovieNet dataset.
+
+## License
+
+The source code in this repository is licensed under the [MIT License](LICENSE).
+
+The MIT license covers **only the code**. The model weights in `models/` (see
+[Models](#models)) are redistributed under their own licenses — several for
+non-commercial research use only. Third-party libraries this software links
+against (OpenCV, ONNX Runtime, FFmpeg, TensorRT/CUDA, nlohmann/json, nanobind,
+and others) likewise carry their own licenses.