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...
Fuente del modelo
- Tipo
- Checkpoint
- Tamaño del archivo
- 192 MB
- Modelo base
- LamKser/face-occlusion-classification
- Versión
- vRevision fa8df09
- Actualizado
- 3 oct 2026
- Publicador
- @Jacky622
- Descargas
- 0
- Fuente
- Hugging Face
Descripción de la fuente
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.
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 3 oct
Artefactos del modelo
1 artefacto
Artefactos del modelo
1 artefactoExtractos de fuentes
3 extractos
Extractos de fuentes
3 extractos--- 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
