add_notebook

This commit is contained in:
rmaphoh
2023-12-15 12:31:15 +00:00
parent a91abec5cd
commit de202be699
+6 -6
View File
@@ -8,21 +8,21 @@ Please contact **ykzhoua@gmail.com** or **yukun.zhou.19@ucl.ac.uk** if you have
Keras version implemented by Yuka Kihara can be found [here](https://github.com/uw-biomedical-ml/RETFound_MAE)
### Key features
### 📝Key features
- RETFound is pre-trained on 1.6 million retinal images with self-supervised learning
- RETFound has been validated in multiple disease detection tasks
- RETFound can be efficiently adapted to customised tasks
### News
### 🎉News
- 2023/12: [Colab notebook](https://colab.research.google.com/drive/1_X19zdMegmAlqPAEY0Ao659fzzzlx2IZ?usp=sharing) is now online - free GPU & simple operation!!!
- 🎄2023/12: [Colab notebook](https://colab.research.google.com/drive/1_X19zdMegmAlqPAEY0Ao659fzzzlx2IZ?usp=sharing) is now online - free GPU & simple operation!!!
- 2023/09: a [visualisation demo](https://github.com/rmaphoh/RETFound_MAE/blob/main/RETFound_visualize.ipynb) is added
- 2023/10: change the hyperparameter of [input_size](https://github.com/rmaphoh/RETFound_MAE#:~:text=finetune%20./RETFound_cfp_weights.pth%20%5C-,%2D%2Dinput_size%20224,-For%20evaluation%20only) for any image size
### Install environment
### 🔧Install environment
1. Create environment with conda:
@@ -40,7 +40,7 @@ pip install -r requirement.txt
```
### Fine-tuning with RETFound weights
### 🌱Fine-tuning with RETFound weights
To fine tune RETFound on your own data, follow these steps:
@@ -146,7 +146,7 @@ print("Model = %s" % str(model))
```
### Citation
### 📃Citation
If you find this repository useful, please consider citing this paper:
```