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@ -36,14 +36,51 @@ Multi-modality (MM) image fusion aims to render fused images that maintain the m
Our CDDFuse is implemented in ``net.py``. Our CDDFuse is implemented in ``net.py``.
### Training
**1. Virtual Environment**
```
# create virtual environment
conda create -n cddfuse python=3.8.10
conda activate cddfuse
# select pytorch version yourself
# install cddfuse requirements
pip install -r requirements.txt
```
**2. Data Preparation**
Download the MSRS dataset from [this link](https://github.com/Linfeng-Tang/MSRS) and place it in the folder ``'./MSRS_train/'``.
**3. Pre-Processing**
Run
```
python dataprocessing.py
```
and the processed training dataset is in ``'./data/MSRS_train_imgsize_128_stride_200.h5'``.
**4. CDDFuse Training**
Run
```
python train.py
```
and the trained model is available in ``'./models/'``.
### Testing ### Testing
**1. Pretrained models**
Pretrained models are available in ``'./models/CDDFuse_IVF.pth'`` and ``'./models/CDDFuse_MIF.pth'``, which are responsible for the Infrared-Visible Fusion (IVF) and Medical Image Fusion (MIF) tasks, respectively. Pretrained models are available in ``'./models/CDDFuse_IVF.pth'`` and ``'./models/CDDFuse_MIF.pth'``, which are responsible for the Infrared-Visible Fusion (IVF) and Medical Image Fusion (MIF) tasks, respectively.
**2. Test datasets**
The test datasets used in the paper have been stored in ``'./test_img/RoadScene'``, ``'./test_img/TNO'`` for IVF, ``'./test_img/MRI_CT'``, ``'./test_img/MRI_PET'`` and ``'./test_img/MRI_SPECT'`` for MIF. The test datasets used in the paper have been stored in ``'./test_img/RoadScene'``, ``'./test_img/TNO'`` for IVF, ``'./test_img/MRI_CT'``, ``'./test_img/MRI_PET'`` and ``'./test_img/MRI_SPECT'`` for MIF.
Unfortunately, since the size of **MSRS dataset** for IVF is 500+MB, we can not upload it for exhibition. It can be downloaded via [this link](https://github.com/Linfeng-Tang/MSRS). The other datasets contain all the test images. Unfortunately, since the size of **MSRS dataset** for IVF is 500+MB, we can not upload it for exhibition. It can be downloaded via [this link](https://github.com/Linfeng-Tang/MSRS). The other datasets contain all the test images.
**3. Results in Our Paper**
If you want to infer with our CDDFuse and obtain the fusion results in our paper, please run ``'test_IVF.py'`` for IVF and ``'test_MIF.py'`` for MIF. If you want to infer with our CDDFuse and obtain the fusion results in our paper, please run ``'test_IVF.py'`` for IVF and ``'test_MIF.py'`` for MIF.
The testing results will be printed in the terminal. The testing results will be printed in the terminal.
@ -91,38 +128,6 @@ CDDFuse_MIF 3.9 58.31 20.87 2.49 1.35 0.97 0.78 1.48
``` ```
which can match the results in Table 5 in our original paper. which can match the results in Table 5 in our original paper.
### Training
**1. Virtual Environment**
```
# create virtual environment
conda create -n cddfuse python=3.8.10
conda activate cddfuse
# select pytorch version yourself
# install cddfuse requirements
pip install -r requirements.txt
```
**2. Data Preparation**
Download the MSRS dataset from [this link](https://github.com/Linfeng-Tang/MSRS) and place it in the folder ``'./MSRS_train/'``.
**3. Pre-Processing**
Run
```
python dataprocessing.py
```
and the processed training dataset is in ``'./data/MSRS_train_imgsize_128_stride_200.h5'``.
**4. CDDFuse Training**
Run
```
python train.py
```
and the trained model is available in ``'./models/'``.
## CDDFuse ## CDDFuse
### Illustration of our CDDFuse model. ### Illustration of our CDDFuse model.