MDvsFA

PyTorch implementation of ICCV2019 paper Miss Detection vs. False Alarm: Adversarial Learing for Small Object Segmentation in Infrared Images.

Guide

Creating the following folders:
- training_results: this folder is to contain all the images of evaluation phases, to visualize the performance of model.
- test_results: this folder is to contain the images during test phases.
- logs: this folder is to contain all logs during training.
- saved_models: to save the weight after each epoch.
The following command is to create fodler under the root of repository:
```
mkdir training_results test_results logs saved_models
```
Dataset: The official implementation offers the dataset, the structure has to be:
```
root
    data
        test_gt
        test_ort
        training
```
Using following command to train:
```
python train.py
```
all the training parameters have default values.
Using following command to test:
```
python test.py
```