EclipseAidge/CustomResNet18
By EclipseAidge · ↓ 0 · ♥ 0 · Updated 2026-03-12
What's in this repo
This page lists the files in EclipseAidge/CustomResNet18, including CustomResNet18.onnx, CustomResNet18_cleaned.onnx.
- 2 ONNX models (.onnx files)
- 4 files, including 2 .onnx, 1 .md
- Last updated 2026-03-12
ONNX files
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
Custom ResNet-18 with integrated Dropout Layers
This is a custom ResNet-18 ONNX model implemented in PyTorch with integrated Dropout layers. It was trained on the CIFAR-10 dataset for image classification tasks. The model has been exported using opset version 15 and is fully compatible with the Aidge platform.
Details
- Architecture: Customized ResNet-18 with integrated Dropout layers
- Trained on: CIFAR-10 (60,000 32x32 color images, 10 classes)
- Image Preprocessing: Images were resized to
128×128 - Data Normalization:
mean = [0.4914, 0.4822, 0.4465];std = [0.2023, 0.1994, 0.2010] - Dropout Probability: 0.3
- ONNX opset version: 15
- Conversion tool: PyTorch → ONNX
Model info
Created: 2025-06-18
Updated: 2026-03-12
View on Hugging Face