| --- |
| framework: pytorch |
| model: EfficientNet-B1 |
| dataset: CIFAR10 (restructured to have random upright and upside-down samples, with labels {0:'up', 1:'down'} |
| imgSize: 224x224x3 |
| --- |
| |
|
|
| This repository contains model trained to predict orientation {0:'up', 1:'down'} of images. |
| The model '.pkl' file contains a dictionary with the following keys: |
|
|
| ```python: |
| 'optimizer': optimizer state dictionary |
| 'scheduler': scheduler state dictionary |
| 'model': model state dictionary |
| 'epoch': checkpoint epoch |
| ``` |
|
|
| The image size is 3x224x224. The model can be initialized as: |
|
|
| ```python: |
| model = torchvision.models.efficientnet_b1(pretrained=True) |
| |
| in_features = model.classifier[1].in_features |
| out_features = 2 |
| |
| model.classifier[1] = nn.Linear(in_features, out_features, bias=True) |
| ``` |
