Extract building and road from aerial imagery
- OpenCV 2.4.10
- Boost 1.57.0
- Boost.NumPy
- Caffe (modified caffe: https://github.com/mitmul/caffe)
- NOTE: Build the
ssai
branch of the above repository
- NOTE: Build the
$ bash shells/donwload.sh
$ python scripts/create_dataset.py --dataset multi
$ python scripts/create_dataset.py --dataset single
$ python scripts/create_dataset.py --dataset roads_mini
$ python scripts/create_dataset.py --dataset roads
$ python scripts/create_dataset.py --dataset buildings
$ python scripts/create_dataset.py --dataset merged
- train: 1119872 patches
- epoch: 8749 mini-batches (mini-batch size: 128)
- valid: 36100 patches
- epoch: 282 mini-batches (mini-batch size: 128)
- test: 89968 patches
- epoch: 703 mini-batches (mini-batch size: 128)
$ python scripts/create_models.py --seed seeds/model_seeds.json
$ bash shells/train.sh models/Mnih_CNN
will create a directory named results/Mnih_CNN_{started date}
.
$ cd results/Mnih_CNN_{started date}
$ python ../../scripts/test_prediction.py --model predict.prototxt --weight snapshots/Mnih_CNN_iter_1000000.caffemodel --img_dir ../../data/mass_merged/test/sat --channel 3
$ cd lib
$ mkdir build
$ cd build
$ cmake ../
$ make
$ cd results/Mnih_CNN_{started date}
$ python ../../scripts/test_evaluation.py --map_dir ../../data/mass_merged/test/map --result_dir prediction_1000000 --channel 3