FCNet

Code release for FCNet: Extracting Undistorted Images for Fine-Grained Image Classification.

Requirement

python 3.8

PyTorch >= 1.3.1

torchvision >= 0.4.2

Training

1. Download datatsets for FGVC (e.g. CUB-200-2011, Standford Cars, FGVC-Aircraft, etc) and organize the structure as follows:

dataset
├── train
│   ├── class_001
|   |      ├── 1.jpg
|   |      ├── 2.jpg
|   |      └── ...
│   ├── class_002
|   |      ├── 1.jpg
|   |      ├── 2.jpg
|   |      └── ...
│   └── ...
└── test
    ├── class_001
    |      ├── 1.jpg
    |      ├── 2.jpg
    |      └── ...
    ├── class_002
    |      ├── 1.jpg
    |      ├── 2.jpg
    |      └── ...
    └── ...

2. Train the Stage-1 of FCNet with python Birds.py in FCNet_Training

3. Train the Stage-2 of FCNet with python Birds.py in FCNet_Training by setting --train_stage to default=2

4. Train ResNet-50 integrated with FCNet with python Birds.py in FT_ResNet_FCNet

Contact

Thanks for your attention! If you have any suggestion or question, you can leave a message here or contact us directly:

• [email protected]
• [email protected]