You can deploy this model and start earning money today!

nxtr-kiranshivaraju/
hijab-person-rfdetr

Name: hijab-person-rfdetr
Availability: InStock

Views

No views yet

hijab-person-rfdetr

RF-DETR (DINOv2 backbone) person detector exported to ONNX, used by the people viscom in the vidiomatic CV platform. Private / internal (nextoar) — do not redistribute.

Contract — how to bind this model


file	`Hijab_model_2.onnx`
input	`input` float32 `[1, 3, 560, 560]`, RGB
preprocessing	ImageNet norm after /255 — `net-scale-factor=0.01735207357`, `offsets=123.675;116.28;103.53`, stretched to square (no letterbox)
outputs	`dets` `[1,300,4]` (DETR cx,cy,w,h, normalised) · `labels` `[1,300,2]` (per-query logits)
scoring	sigmoid, top-k, NMS-free (set predictor)
classes	index 0 = person (single trained class; index 1 unused). Detections fire on `class_id 0`.

Training & caveat

Trained with RF-DETR (Roboflow) on a single class hijab_person (people wearing a hijab), relabeled to person for the people viscom. Recall on people not wearing a hijab is not guaranteed — swap in a broader person detector for general use.

DeepStream / TensorRT usage

Requires the RF-DETR custom output parser NvDsInferParseCustomRfDetr (cluster-mode=4, NMS-free). On heavy downscale set scaling-filter=1 (bilinear) — nvinfer's default nearest-neighbour resize collapses RF-DETR recall (~33% vs raw PyTorch).

Pull

python

from huggingface_hub import hf_hub_download
onnx = hf_hub_download("nxtr-kiranshivaraju/hijab-person-rfdetr", "Hijab_model_2.onnx")