CamStack model mirror
This repository is a mirror of third-party models converted by
CamStack into the formats its inference
engines run (ONNX, OpenVINO IR, CoreML). Nothing here is relicensed.
Each folder stays under the licence of the model it was made from, stated in the
folder's README.md and in the table below, with the full text in
LICENSES/. The repository as a whole has no single licence; see
LICENSE.
Every model file here is a modified version of its upstream: at minimum converted to another format; where the folder card says so, re-exported at a smaller input size, quantised (OpenVINO NNCF INT8), fine-tuned, or with a graph edit.
THIRD_PARTY_MODELS.md is the notice CamStack ships
with its software. It covers every model CamStack can download, including those
fetched from other repositories, with the attributions each licence requires.
AGPL-3.0 models (Ultralytics)
objectDetection/yolo26, objectDetection/yolov9 and segmentation/yolo26-seg
hold Ultralytics weights under AGPL-3.0 (LICENSES/AGPL-3.0.txt).
Their Corresponding Source is set out in
Source offer for the AGPL-3.0 weights.
Non-commercial models
This may not be used commercially. See the folder's card.
vehicleClassification/vehicle-type-v1: trained on a CC BY-NC 4.0 dataset (LICENSES/CC-BY-NC-4.0.txt).
Required attributions
- Ultralytics YOLO26, YOLOv9: © Ultralytics, AGPL-3.0. YOLOv9 architecture: Chien-Yao Wang, I-Hau Yeh, Hong-Yuan Mark Liao, GPL-3.0.
- open-lpr models (plate detector): Copyright the open-lpr contributors,
Apache-2.0; YOLOX architecture and COCO pretraining by Megvii, Apache-2.0.
The upstream
NOTICEis in the folder and inLICENSES/NOTICE-open-lpr.txt. - fast-plate-ocr: Copyright (c) 2024 ankandrew, MIT.
- Open Images V7 (animal-classifier training data): annotations © Google LLC, CC BY 4.0.
- Vehicle classification dataset (vehicle-type-v1 training data): DrBimmer, https://huggingface.co/datasets/DrBimmer/vehicle-classification, CC BY-NC 4.0.
- AudioSet (YAMNet labels): © Google LLC, CC BY 4.0.
- COCO (YOLO pretraining): annotations CC BY 4.0.
- Apache-2.0 upstreams: RF-DETR (Roboflow), AuraFace v1 (fal.ai), U²-Net (Xuebin Qin et al.), YAMNet and AIY Vision Birds V1 (Google LLC), EfficientNet-Lite0 via timm (Ross Wightman).
Models
"Unknown" means no licence could be traced; it does not mean free to use. default marks the model a CamStack step runs when nobody chose one; hidden marks an entry kept resolvable for a saved selection but no longer offered.
| Folder | Catalog ids | Upstream | Weights licence | Licence text | CamStack modifications |
|---|---|---|---|---|---|
objectDetection/yolo26 | yolo26n (default), yolo26s, yolo26m, yolo26l, yolo26x (hidden), yolo26n-fp16 (hidden), yolo26n-int8, yolo26s-fp16 (hidden), yolo26s-int8, yolo26m-fp16 (hidden), yolo26m-int8, yolo26l-fp16 (hidden), yolo26l-int8, yolo26n-320, yolo26n-320-int8, yolo26n-256, yolo26n-256-int8, yolo26s-320, yolo26s-320-int8, yolo26s-256, yolo26s-256-int8, yolo26m-320, yolo26m-320-int8, yolo26m-256, yolo26m-256-int8, yolo26l-320, yolo26l-320-int8, yolo26l-256, yolo26l-256-int8, yolo26x-fp16 (hidden), yolo26x-int8 (hidden) | Ultralytics | AGPL-3.0 | AGPL-3.0.txt | exported to ONNX, OpenVINO IR and CoreML (scripts/build-camstack-models.py); OpenVINO FP16 export; exported to OpenVINO IR, then OpenVINO NNCF INT8 post-training quantisation; re-exported at 320×320 to ONNX, OpenVINO IR and CoreML; re-exported at 320×320 to OpenVINO IR; OpenVINO NNCF INT8 post-training quantisation; re-exported at 256×256 to ONNX, OpenVINO IR and CoreML; re-exported at 256×256 to OpenVINO IR; OpenVINO NNCF INT8 post-training quantisation |
objectDetection/yolov9 | yolov9t-320, yolov9t-320-int8, yolov9t-640, yolov9t-640-int8, yolov9s-320, yolov9s-320-int8, yolov9s-640, yolov9s-640-int8, yolov9m-320, yolov9m-320-int8, yolov9m-640, yolov9m-640-int8, yolov9c-320, yolov9c-320-int8, yolov9c-640, yolov9c-640-int8 | Ultralytics | AGPL-3.0 | AGPL-3.0.txt | exported at 320×320 to ONNX, OpenVINO IR FP16 and CoreML; exported at 320×320 to OpenVINO IR; OpenVINO NNCF INT8 post-training quantisation; exported at 640×640 to ONNX, OpenVINO IR FP16 and CoreML; exported at 640×640 to OpenVINO IR; OpenVINO NNCF INT8 post-training quantisation |
packageDetection/rfdetr-package | rfdetr-package (default) | Roboflow RF-DETR | Apache-2.0 | Apache-2.0.txt | RF-DETR-M fine-tuned to 2 classes at 576; exported to ONNX, OpenVINO IR and CoreML; training checkpoint .pth also published |
faceDetection/yunet | yunet-2023mar (default) | OpenCV Zoo YuNet | MIT | MIT-yunet-reference.txt, BSD-3-Clause.txt | input contract baked into the graph (the pool RGB /255 becomes the upstream BGR 0..255: Mul(255) plus a channel Gather); internal tensor names cleared in the OpenVINO IR; ONNX fp32, OpenVINO IR fp32, CoreML fp16 (scripts/build-yunet-model.py) |
faceRecognition/auraface | auraface-r100 (default) | fal.ai AuraFace v1 (glintr100.onnx only) | Apache-2.0 | Apache-2.0.txt | input scaling y = 2x - 1 baked ahead of the first Conv (scripts/build-auraface-model.py); converted to OpenVINO IR and CoreML FP16 |
plateDetection/yolox-tiny-plate | yolox-tiny-plate (default) | open-lpr models (faisalthaheem/open-lpr-models), YOLOX-tiny | Apache-2.0 | Apache-2.0.txt | input contract baked into the graph (static 1x3x640x640 RGB /255 becomes the upstream BGR 0..255: Mul(255) plus a channel Gather) and the output reshaped to the YOLOv8 layout (cx, cy, w, h, obj*cls); ONNX fp32, OpenVINO IR fp16, CoreML fp16 (scripts/build-yolox-plate-model.py) |
plateRecognition/cct-s-v2-global | cct-s-v2-global (default) | ankandrew/fast-plate-ocr | MIT | MIT-fast-plate-ocr.txt | input head removed (recorded in the ONNX doc_string); converted to OpenVINO IR and CoreML |
animalClassification/animal-classifier | animal-classifier (default) | timm EfficientNet-Lite0, fine-tuned by CamStack | Apache-2.0 | Apache-2.0.txt | fine-tuned by CamStack on the Open Images V7 animal subset (8 classes); exported to ONNX, OpenVINO IR and CoreML |
animalClassification/bird-classifier | bird-classifier (default) | Google AIY Vision birds_V1 | Apache-2.0 | Apache-2.0.txt | converted from TensorFlow with tf2onnx; OpenVINO IR and CoreML derived from it |
vehicleClassification/vehicle-type-v1 | vehicle-type-v1 (default) | torchvision MobileNetV3-Large, fine-tuned by CamStack | CC-BY-NC-4.0 | CC-BY-NC-4.0.txt, BSD-3-Clause.txt | fine-tuned by CamStack (8 classes); exported to ONNX, OpenVINO IR and CoreML |
clip/siglip2 | siglip2-b16-224 (default), siglip2-b16-224-text | Google SigLIP 2 (google/siglip2-base-patch16-224) | Apache-2.0 | Apache-2.0.txt | input scaling y = 2x - 1 baked ahead of the patch embedding; converted to OpenVINO IR and CoreML FP16, an FP32 ONNX hosted as the verification reference (scripts/build-siglip2-model.py); input sliced to the model's 64 positions in the graph; ONNX weights FP16, OpenVINO IR and CoreML FP16; a Lowercase normalizer prepended to the Gemma tokenizer (scripts/build-siglip2-model.py) |
segmentationRefiner/u2netp | u2netp (default) | xuebinqin/U-2-Net | Apache-2.0 | Apache-2.0.txt | converted to ONNX, OpenVINO IR and CoreML |
segmentation/yolo26-seg | yolo26n-seg, yolo26s-seg, yolo26m-seg | Ultralytics | AGPL-3.0 | AGPL-3.0.txt | exported to ONNX, OpenVINO IR and CoreML |
audioClassification/yamnet | yamnet-onnx (default) | tensorflow/models research/audioset/yamnet | Apache-2.0 | Apache-2.0.txt | converted from TensorFlow with tf2onnx; OpenVINO IR derived from it |
This mirror holds only the models CamStack offers. Models it no longer offers (SCRFD, ArcFace, Inception-ResNet, VGG-English, MobileCLIP S1/S2, YOLOv8n-package, SSDLite MobileDet, the YOLOv8n plate detector, and earlier a third-party face, PaddleOCR, animals-10, NABirds and EfficientNet folders) were removed, and the repository history was squashed on 2026-10-06.