# Output Diversified Sampling (ODS) with the Simple Black-box Attack (SimBA)

## Running experiments

The implemented method corresponds to SimBA-ODS in Section 5.1 of the paper.

The following experiments correspond results by SimBA-ODS in Table 3 of the paper (the experiments are held with 10 images which we used in the paper).

### Requirement

1. Install PyTorch>=1.2.0
1. Install pickle

### Evaluation SimBA with ODS (SimBA-ODS):
The following evaluation is held for 10 images on ImageNet (images are already resized and cropped).

#### Evaluate SimBA-ODS:
* untargeted settings:
```bash
  $ python simbaODS.py --data_folder ../data_NeurIPS --num_sample 10 --ODS 
```

* targeted settings:
```bash
  $ python simbaODS.py --data_folder ../data_NeurIPS --num_sample 10 --num_step 30000 --ODS --targeted
```
