Get the directory structure neat

README.md

@@ -4,7 +4,7 @@ This is an unofficial implementation of the paper
 
 > Rodrigo Caye Daudt, Bertrand Le Saux, Alexandre Boulch. (2018, October). Fully convolutional siamese networks for change detection. In 2018 25th IEEE International Conference on Image Processing (ICIP) (pp. 4063-4067). IEEE.
  
-as the [official repo](https://github.com/rcdaudt/fully_convolutional_change_detection) does not provide the training code. 
+~~as the [official repo](https://github.com/rcdaudt/fully_convolutional_change_detection) does not provide the training code.~~
 
 [paper link](https://ieeexplore.ieee.org/abstract/document/8451652)
 
@@ -30,18 +30,18 @@ mkdir exp
 cd src
 ```
 
-In `src/constants.py`, change the dataset directories to your own. In `config_base.yaml`, feel free to change the configurations.
+In `src/constants.py`, change the dataset directories to your own. In `config_base.yaml`, feel free to change some configurations.
 
 For training, try
 
 ```bash
-python train.py train --exp-config ../config_base.yaml
+python train.py train --exp-config ../configs/config_base.yaml
 ```
 
 For evaluation, try
 
 ```bash
-python train.py val --exp-config ../config_base.yaml --resume path_to_checkpoint --save-on
+python train.py val --exp-config ../configs/config_base.yaml --resume path_to_checkpoint --save-on
 ```
 
 You can find the checkpoints in `exp/base/weights/`, the log files in `exp/base/logs`, and the output change maps in `exp/base/outs`.

train9.sh

@@ -15,6 +15,6 @@ for arch in ${ARCHS[@]}
 do
     for dataset in ${DATASETS[@]}
     do
-        python train.py train --exp-config ../config_${arch}_${dataset}.yaml
+        python train.py train --exp-config ../configs/config_${arch}_${dataset}.yaml
     done
 done
\ No newline at end of file