If you want to use CAR196 dataset, download CAR196/images
from here:
CAR196,
and put /images
in CAR196 folder.
While if you want CUB200 dataset, download CUB200/images
from here:
CUB200,
or use CUB200/split_train_test.py
to process your original
CUB_200_2011 and generate these images.
Note: If you want your own dataset, remember to edit your config.yaml
and change classnum: xxx.
Install the environment as the 'requirements.txt'.
pip install -i https://pypi.tuna.tsinghua.edu.cn/simple -r requirements.txt
Besides, you should install pytorch according your CUDA version https://pytorch.org/get-started/locally/.
Check the run.sh
script, and change hyperparameters accordingly.
(when the dataset choise occurs, just choose the number of you dataset )
- 1 $
bash run.sh setup
to runfilternet.py
9_selective_search
- 2 $
bash run.sh patch
to runpatch_filter.py
patchnet_bn_rerun.py
- 3 $
bash run.sh object
to runsaliencynet.py
CAM.py
objectnet_bn_rerun.py
- 4 $
bash run.sh part
to runfilterpart.py
align_part.py
partnet_bn_rerun.py
- 5 $
bash run.sh fusion
to runfusion_predict.py
or just run $ bash run.sh all
,
the final result is in /log/fusion_predict.log