## **Installation**

- Install PyTorch
- Install required Python packages:

```bash
pip install datasets
pip install huggingface_hub
pip install ultralytics
```

## Basic usage: Run the Filtering on WIT-base

Run the Filtering with Command-Line Arguments


```bash
python wit_filter.py --device cuda:0 --batch_size 32 --output_filtered_data_file_path /path/to/filtered_data_file.parquet
```

- `--device`: Set to "cpu" if GPU is unavailable (default: cuda:0)
- `--batch_size`: Adjust based on your available memory (default: 32)
- `--output_filtered_data_file_path`: Path to save the filtered results (default: filtered_data_file.parquet)

The filtered dataset will be saved at the path specified by `--output_filtered_data_file_path`.

## Evaluation Mode Usage: Evaluate Detection Performance on WIT-base Subset

A curated evaluation subset of 30 WIT-base images is included to evaluate the detection model performance.


To enable evaluation mode and save filtered images into category-specific folders, use the `--eval_mode` flag and specify the image directory:

```bash
python wit_filter.py --device cuda:0 --batch_size 32 --output_filtered_data_file_path /path/to/filtered_data_file.parquet --eval_mode --filtered_image_dir path/to/image_filter_result_dir
```

- `--eval_mode`: Enable evaluation mode to save filtered images into category-specific folders
- `--filtered_image_dir`: Directory where the filtered images will be saved (default: image_filter_result_dir)

Filtered images will be organized into subfolders under `filtered_image_dir`:

- `no_face/`: No valid face detected
- `valid_face_no_glasses/`: Valid face detected, no glasses
- `valid_face_with_eyeglasses/`: Valid face with eyeglasses
- `valid_face_with_sunglasses/`: Valid face with sunglasses

### Information about the Evaluation Data

📎 `wit_eval_30.csv`: Metadata for the evaluation set.

| Column | Description |
| --- | --- |
| `idx` | Index in the original WIT-base dataset |
| `has_face` | 0 = No face or too small, 1 = Valid face |
| `glasses_type` | 0 = No glasses, 1 = Eyeglasses, 2 = Sunglasses |

📎 `data/`: Directory containing all 30 images in the evaluation subset.