NITEC ResNet-18 INT8 — Camera Contact
This model classifies an RGB face crop as camera contact or no camera contact. It is the NITEC ResNet-18 checkpoint converted to an A8W8, statically quantized ONNX graph for ONNX Runtime.
Artifact
| Item | Value |
|---|---|
| File | cam_contact_nitec_rs18-a8w8-ort-quantized.onnx |
| SHA-256 | eff8cfcce4ebdbdab68ad338c67c5608ffaf856808e5739b4289e5e7ddd7366d |
| Size | 11,352,950 bytes |
| Input | x, FLOAT [1, 3, 224, 224], RGB NCHW |
| Output | linear, FLOAT [1, 2] logits |
| Classes | 0: no contact; 1: contact |
| ONNX opset | 20 |
See config.yaml for the complete inference recipe.
Example
By default, the example runs every face crop under samples/ and writes its
predicted classification under assets/. The bundled examples include two
contact and two no contact results.
| Input | Inferred visualization |
|---|---|
python -m pip install numpy onnxruntime pillow pyyaml
python example.py
python example.py samples/face-crop-0.png assets/custom-classification.png
The script parses config.yaml, making its tensor names, shapes, resize and
center-crop behavior, normalization, class labels, and softmax postprocessing
an executable inference recipe. Image loading, preprocessing, ONNX inference,
output postprocessing, visualization, and saving remain separate steps for reuse.
Download
hf download Arm/nitec-resnet-18-int8-onnx \
cam_contact_nitec_rs18-a8w8-ort-quantized.onnx \
--local-dir .
Validation
The artifact completed an interface smoke test with ONNX Runtime 1.30.0 using
CPUExecutionProvider on x86-64. It produced finite classification logits with
the documented shape. This is not an accuracy or performance measurement.
Intended use and limitations
- Intended for camera-contact classification on already detected, tightly cropped faces.
- It is not a face detector and does not accept a full scene directly.
- Performance may vary with pose, occlusion, lighting, crop quality, and camera placement.
References
About this version
Original Model: NITEC ResNet-18 by Thorsten Hempel et al. - Repository
Optimization/conversion: Arm-Optimized version for execution on Arm-based platforms.
Converted/optimized by: Arm
License: The published artifacts in this repository are distributed under Apache-2.0.
This repository contains a converted or optimized version of the Original Model (the “Optimized Model”). The Original Model has been converted or optimized as described above for execution on Arm-based platforms.
No retraining or fine-tuning of the Original Model was performed as part of the conversion or optimization. The conversion or optimization was not intended to change the Original Model’s behavior or intended use.
Original Model and Documentation
For information about the Original Model, including its development, training data, intended uses, limitations and other relevant information, please refer to the Original Model repository. Information in that repository was provided by the original developer or other third parties and, unless expressly stated otherwise, has not been independently verified by Arm.
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Purpose of this Release
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