Face Occlusion
ONNX export of the ConvNeXt-Small face-occlusion classifier from LamKser/face-occlusion-classification (MIT). All credit for the model and training goes to the original author; this repo only re-packages a trained...
Modellquelle
- Art
- Checkpoint
- Dateigröße
- 192 MB
- Basismodell
- LamKser/face-occlusion-classification
- Version
- vRevision fa8df09
- Aktualisiert
- 3. Okt. 2026
- Verleger
- @Jacky622
- Downloads
- 0
- Quelle
- Hugging Face
Quellenbeschreibung
face-occlusion-classification (ONNX export)
ONNX export of the ConvNeXt-Small face-occlusion classifier from LamKser/face-occlusion-classification (MIT). All credit for the model and training goes to the original author; this repo only re-packages a trained checkpoint as ONNX for inference.
Files
face_occlusion.onnx— exported with theirconvert_2_onnx.py(opset 12).
I/O
- Input:
[1, 3, 224, 224]float32, RGB, scaled to[0,1]then ImageNet-normalized (mean[0.485,0.456,0.406], std[0.229,0.224,0.225]), NCHW. - Output:
[1, 2]logits — softmax index 1 = occluded.
License & attribution
Released under the MIT License, inherited from the upstream project. See the original repository for the full copyright notice and training details.
Quellen
1 Quelle
Quellen
1 QuelleVerifiziert 3. Okt.
Modellartefakte
1 Artefakt
Modellartefakte
1 ArtefaktQuellenauszüge
3 Auszüge
Quellenauszüge
3 Auszüge--- license: mit library_name: onnx tags: - image-classification - face-occlusion - onnx base_model: LamKser/face-occlusion-classification --- # face-occlusion-classification (ONNX export) ONNX export of the **ConvNeXt-Small** face-occlusion classifier from [LamKser/face-occlusion-classification](https://github.com/LamKser/face-occlusion-classification) (MIT). All credit for the model and training goes to the original author; this repo only re-packages a trained checkpoint as ONNX for inference. ## Files - `face_occlusion.onnx` — exported with their `convert_2_onnx.py` (opset 12). ## I/O - **Input:** `[1, 3, 224, 224]` float32, RGB, scaled to `[0,1]` then ImageNet-normalized (mean `[0.485,0.456,0.406]`, std `[0.229,0.224,0.225]`), NCHW. - **Output:** `[1, 2]` logits — softmax index **1 = occluded**. ## License & attribution Released under the MIT License, inherited from the upstream project. See the original repository for the full copyright notice and training details.
Source context: 0 downloads · 0 likes · Pipeline image-classification · Library onnx · Repo Jacky622/face_occlusion
Source context: 0 downloads · 0 likes · Pipeline image-classification · Library onnx · Repo Jacky622/face_occlusion
