Runrazor Detectors

--- license: apache-2.0 library_name: onnx tags: - object-detection - yolox - onnx - runrazor --- # runrazor detector models Downloadable subject-detector weights for [runrazor](https://pypi.org/project/runrazor/). These are stock **YOLOX** object detectors, exported to ONNX and used at runtime restricted to the COCO `person` class (skiers are detected as people; runrazor's tracking layer handles subject selection). runrazor fetches these on demand: `rrreframe clip.mp4 --detector nn --nn-model yolox_s` downloads the file once, verifies its SHA-256, and caches it. The smaller `yolox_nano` ships inside the `runrazor` package itself and needs no download. ## Files | file | base model | input | notes | |------|-----------|-------|-------| | `yolox_s-v1.onnx` | YOLOX-S | 640 | best accuracy/speed balance; recommended upgrade | | `yolox_m-v1.onnx` | YOLOX-M | 640 | highest recall; ~2.4x slower than S on CPU | Each file is pre-stamped with its runrazor runtime settings (`format=yolox_raw`, `conf`, `class_id=0`) in the ONNX metadata, so it is a drop-in -- no extra flags. ## Attribution and license These weights are derived from **YOLOX** (https://github.com/Megvii-BaseDetection/YOLOX), Copyright (c) 2021-2022 Megvii Inc., licensed under the **Apache License 2.0** (see `LICENSE`). The networks were not retrained; the upstream `.pth` weights were exported to ONNX. YOLOX is pretrained on the [COCO dataset](https://cocodataset.org).

Source context: 0 downloads · 0 likes · Pipeline object-detection · Library onnx · Repo kenjrwalker/runrazor-detectors