Tensorflow implementation of CRPM-Net for PolSAR image classification by DongLing Xiao. Paper at https://arxiv.org/abs/1909.10783 .
- Clone this repository.
- Ensure tensorflow is installed using
//gpu-python2
sudo pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.2.0-cp27-none-linux_x86_64.whl
//cpu-python2
sudo pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0-cp27-none-linux_x86_64.whl
- Ensure scipy,numpy,PIL,matplotlib are installed.
- A jupyter note file is available.
- use
utils.pyto gain training pixels, the sampling number is required.
def get_train_data(data_path,label_path,label_path_local) # get random sampled pixels
get_sample_npy(label_path) # save as *.npy file
- Cs-CNN training step: in
CRPM_Net.py, change standard to 1; inmain.py, chage mode totrain
python main.py
****************epoch start****************
10 / 89 batch(s) processed in 1th epoch used 4 sec and loss is 0.3314
20 / 89 batch(s) processed in 1th epoch used 0 sec and loss is 0.5463
30 / 89 batch(s) processed in 1th epoch used 0 sec and loss is 0.6430
40 / 89 batch(s) processed in 1th epoch used 0 sec and loss is 0.5983
50 / 89 batch(s) processed in 1th epoch used 0 sec and loss is 3.5854
60 / 89 batch(s) processed in 1th epoch used 0 sec and loss is 0.5164
70 / 89 batch(s) processed in 1th epoch used 0 sec and loss is 0.4983
80 / 89 batch(s) processed in 1th epoch used 0 sec and loss is 0.5076
2019-01-21 12:19:46.082378 >> 1 epoch(s), 89 step(s)
grass: 0.736667
flax: 0.000000
potato: 0.323432
wheat: 0.000000
rapessed: 0.770833
beet: 0.000000
barley: 0.000000
peas: 0.000000
maize: 0.000000
bean: 0.000000
fruit: 0.477778
onion: 0.000000
oat: 0.000000
lucerne: 0.000000
building: 0.000000
road: 0.000000
**********validation evaluation**********
Validation >> 89th step in 1 epoch(s) / Accuracy: 0.2458 / Loss: 4.7863
global_step: 89
- CRPM-Net training step: in
CRPM_Net.py, change standard to 2; inmain.py, chage mode totrain
python main.py
-
test Cs-CNN: in
CRPM_Net.py, change standard to 1; inmain.py, chage mode totest1 -
test C-Dilated CNN: in
CRPM_Net.py, change standard to 1; inmain.py, chage mode todilate -
testCRPM-Net: in
CRPM_Net.py, change standard to 2; inmain.py, chage mode totest2
python main.py
- Test jupyter notebook CRPM_Net_flevoland.ipynb
