This is the implementation of "AnoGAN" corresponding to 2-dimensional shape.
Original paper: T. Schlegl, P. Seeböck, S. M. Waldstein, U. Schmidt-Erfurth, and G. Langs. Unsupervised anomaly detection with generative adversarial networks to guide marker discovery. In International Conference on Information Processing in Medical Imaging, 2017. link
Please build the source file according to the procedure.
$ mkdir build
$ cd build
$ cmake ..
$ make -j4
$ cd ..
- MVTec Anomaly Detection Dataset (MVTec AD)
This is a dataset for benchmarking anomaly detection methods with a focus on industrial inspection.
Link: official
Please create a link for the dataset.
The following hierarchical relationships are recommended.
datasets
|--Dataset1
| |--train
| | |--image1.png
| | |--image2.bmp
| | |--image3.jpg
| |
| |--valid
| |--test_anomaly
| |--test_normal
|
|--Dataset2
|--Dataset3
You should substitute the path of training normal data for "<training_path>", test anomaly data for "<test_anomaly_path>", test normal data for "<test_normal_path>", respectively.
The following is an example for "MVTecAD".
$ cd datasets
$ mkdir MVTecAD
$ cd MVTecAD
$ ln -s <training_path> ./train
$ ln -s <test_anomaly_path> ./test_anomaly
$ ln -s <test_normal_path> ./test_normal
$ cd ../..
Please set the shell for executable file.
$ vi scripts/train.sh
The following is an example of the training phase.
If you want to view specific examples of command line arguments, please view "src/main.cpp" or add "--help" to the argument.
#!/bin/bash
DATA='MVTecAD'
./AnoGAN2d \
--train true \
--epochs 300 \
--dataset ${DATA} \
--size 256 \
--batch_size 16 \
--gpu_id 0 \
--nc 3
Please execute the following to start the program.
$ sh scripts/train.sh
Please set the shell for executable file.
$ vi scripts/test.sh
The following is an example of the test phase.
If you want to view specific examples of command line arguments, please view "src/main.cpp" or add "--help" to the argument.
#!/bin/bash
DATA='MVTecAD'
HEATMAP_MAX=0.1
./AnoGAN2d \
--test true \
--dataset ${DATA} \
--test_dir "test_anomaly" \
--test_result_dir "test_result_anomaly" \
--heatmap_max ${HEATMAP_MAX} \
--size 256 \
--gpu_id 0 \
--nc 3
./AnoGAN2d \
--test true \
--dataset ${DATA} \
--test_dir "test_normal" \
--test_result_dir "test_result_normal" \
--heatmap_max ${HEATMAP_MAX} \
--size 256 \
--gpu_id 0 \
--nc 3
Please execute the following to start the program.
$ sh scripts/test.sh
Please set the shell for executable file.
$ vi scripts/anomaly_detection.sh
The following is an example of the anomaly detection phase.
If you want to view specific examples of command line arguments, please view "src/main.cpp" or add "--help" to the argument.
#!/bin/bash
DATA='MVTecAD'
./AnoGAN2d \
--AD true \
--dataset ${DATA} \
--anomaly_path "test_result_anomaly/anomaly_score.txt" \
--normal_path "test_result_normal/anomaly_score.txt" \
--n_thresh 256
Please execute the following to start the program.
$ sh scripts/anomaly_detection.sh
This code is inspired by pytorch_advanced.