https://github.com/rasbt/ord-torchhub
Ordinal Regression PyTorch Hub
https://github.com/rasbt/ord-torchhub
Last synced: about 1 year ago
JSON representation
Ordinal Regression PyTorch Hub
- Host: GitHub
- URL: https://github.com/rasbt/ord-torchhub
- Owner: rasbt
- License: bsd-3-clause
- Created: 2022-07-01T23:01:45.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2022-07-13T14:52:49.000Z (almost 4 years ago)
- Last Synced: 2025-03-31T20:06:46.210Z (about 1 year ago)
- Language: Python
- Size: 1.65 MB
- Stars: 6
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Ordinal Regression PyTorch Hub
This is a GitHub repository containing some deep learning models for ordinal regression (with pre-trained weights) in the PyTorch Hub / Torch Hub format. Note that this repository is not going to be a comprehensive Hub for ordinal regression models but more of a way to quickly access models from a specific manuscript:
- Xintong Shi, Wenzhi Cao, and Sebastian Raschka
*Deep Neural Networks for Rank-Consistent Ordinal Regression Based On Conditional Probabilities.* [https://arxiv.org/abs/2111.08851](https://arxiv.org/abs/2111.08851)
(More models may be added later, but I don't want to make any promises 😅.)
## PyTorch Hub / Torch Hub Resources
- For more information on (Py)Torch Hub, see the documentation at [https://pytorch.org/docs/stable/hub.html](https://pytorch.org/docs/stable/hub.html)
## Using the Models
You can load the model via the following syntax:
```python
import torch
model = torch.hub.load(
"rasbt/ord-torchhub",
model="resnet34_corn_afad",
source='github',
pretrained=True
)
```
Note that the pretrained versions may only perform well on images from the [AFAD](https://afad-dataset.github.io) dataset, which is the dataset that was used to train the models. For more usage examples and transfer learning instructions, please see the examples in [./examples](./examples).
## Which Models Are Currently Supported
- `"resnet34_corn_afad"` (an ordinal model trained via the [CORN](https://arxiv.org/abs/2111.08851) loss)
- `"resnet34_coral_afad"` (an ordinal model trained via the [CORAL](http://arxiv.org/abs/1901.07884) loss)
- `"resnet34_niu_afad"` (an ordinal model trained via [Niu et al.'s](https://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Niu_Ordinal_Regression_With_CVPR_2016_paper.pdf) loss)
- `"resnet34_crossentr_afad"` (a regular classifier trained via cross entropy loss)
## Training (Optional)
In case you want to reproduce the model training, you can find the respective instructions and files in the [`_train`](./_train) subfolder.
## App
Try an interactive App built with [Lightning AI](https://lightning.ai).
Link: https://bit.ly/3yHA5nk
(The source code for this App can be found under [./app](./app).)