candle/candle-transformers/tests/nms_tests.rs

use candle::Result;
use candle_transformers::object_detection::{
    non_maximum_suppression, soft_non_maximum_suppression, Bbox,
};

#[test]
fn nms_basic() -> Result<()> {
    // Boxes based upon https://thepythoncode.com/article/non-maximum-suppression-using-opencv-in-python
    let mut bboxes = vec![vec![
        Bbox {
            xmin: 245.0,
            ymin: 305.0,
            xmax: 575.0,
            ymax: 490.0,
            confidence: 0.9,
            data: (),
        }, // Box 1
        Bbox {
            xmin: 235.0,
            ymin: 300.0,
            xmax: 485.0,
            ymax: 515.0,
            confidence: 0.8,
            data: (),
        }, // Box 2
        Bbox {
            xmin: 305.0,
            ymin: 270.0,
            xmax: 540.0,
            ymax: 500.0,
            confidence: 0.6,
            data: (),
        }, // Box 3
    ]];

    non_maximum_suppression(&mut bboxes, 0.5);
    let bboxes = bboxes.into_iter().next().unwrap();
    assert_eq!(bboxes.len(), 1);
    assert_eq!(bboxes[0].confidence, 0.9);

    Ok(())
}

#[test]
fn softnms_basic_functionality() -> Result<()> {
    let mut bboxes = vec![vec![
        Bbox {
            xmin: 0.0,
            ymin: 0.0,
            xmax: 1.0,
            ymax: 1.0,
            confidence: 0.5,
            data: (),
        },
        Bbox {
            xmin: 0.1,
            ymin: 0.1,
            xmax: 1.1,
            ymax: 1.1,
            confidence: 0.9,
            data: (),
        },
        Bbox {
            xmin: 0.2,
            ymin: 0.2,
            xmax: 1.2,
            ymax: 1.2,
            confidence: 0.6,
            data: (),
        },
    ]];

    soft_non_maximum_suppression(&mut bboxes, Some(0.5), Some(0.1), Some(0.5));

    // Should decay boxes following highest confidence box
    assert!(bboxes[0][0].confidence == 0.9);
    assert!(bboxes[0][1].confidence < 0.5);
    assert!(bboxes[0][2].confidence < 0.6);
    Ok(())
}

#[test]
fn softnms_confidence_decay() -> Result<()> {
    let mut bboxes = vec![vec![
        Bbox {
            xmin: 0.0,
            ymin: 0.0,
            xmax: 1.0,
            ymax: 1.0,
            confidence: 0.9,
            data: (),
        }, // Reference box
        Bbox {
            xmin: 0.1,
            ymin: 0.1,
            xmax: 1.1,
            ymax: 1.1,
            confidence: 0.8,
            data: (),
        }, // Overlapping box
    ]];

    soft_non_maximum_suppression(&mut bboxes, Some(0.5), Some(0.1), Some(0.5));

    // Check that confidence of the overlapping box is decayed
    assert!(bboxes[0][0].confidence == 0.9);
    assert!(bboxes[0][1].confidence < 0.8);
    Ok(())
}

#[test]
fn softnms_confidence_threshold() -> Result<()> {
    let mut bboxes = vec![vec![
        Bbox {
            xmin: 0.0,
            ymin: 0.0,
            xmax: 1.0,
            ymax: 1.0,
            confidence: 0.9,
            data: (),
        },
        Bbox {
            xmin: 0.1,
            ymin: 0.1,
            xmax: 1.1,
            ymax: 1.1,
            confidence: 0.05,
            data: (),
        },
    ]];

    soft_non_maximum_suppression(&mut bboxes, Some(0.5), Some(0.1), Some(0.5));

    // Box with confidence below the threshold should be removed
    assert_eq!(bboxes[0].len(), 2);
    assert_eq!(bboxes[0][0].confidence, 0.9);
    assert_eq!(bboxes[0][1].confidence, 0.00);
    Ok(())
}

#[test]
fn softnms_no_overlap() -> Result<()> {
    let mut bboxes = vec![vec![
        Bbox {
            xmin: 0.0,
            ymin: 0.0,
            xmax: 1.0,
            ymax: 1.0,
            confidence: 0.9,
            data: (),
        },
        Bbox {
            xmin: 2.0,
            ymin: 2.0,
            xmax: 3.0,
            ymax: 3.0,
            confidence: 0.8,
            data: (),
        },
    ]];

    soft_non_maximum_suppression(&mut bboxes, Some(0.5), Some(0.1), Some(0.5));

    // Both boxes should remain as they do not significantly overlap
    assert_eq!(bboxes[0].len(), 2);
    assert_eq!(bboxes[0][0].confidence, 0.9);
    assert_eq!(bboxes[0][1].confidence, 0.8);
    Ok(())
}
#[test]
fn softnms_no_bbox() -> Result<()> {
    let mut bboxes: Vec<Vec<Bbox<()>>> = vec![];
    soft_non_maximum_suppression(&mut bboxes, Some(0.5), Some(0.1), Some(0.5));
    assert!(bboxes.is_empty());
    Ok(())
}

#[test]
fn softnms_single_bbox() -> Result<()> {
    let mut bboxes = vec![vec![Bbox {
        xmin: 0.0,
        ymin: 0.0,
        xmax: 1.0,
        ymax: 1.0,
        confidence: 0.9,
        data: (),
    }]];
    soft_non_maximum_suppression(&mut bboxes, Some(0.5), Some(0.1), Some(0.5));
    assert_eq!(bboxes[0].len(), 1);
    Ok(())
}

#[test]
fn softnms_equal_confidence_overlap() -> Result<()> {
    let mut bboxes = vec![vec![
        Bbox {
            xmin: 0.0,
            ymin: 0.0,
            xmax: 1.0,
            ymax: 1.0,
            confidence: 0.5,
            data: (),
        },
        Bbox {
            xmin: 0.1,
            ymin: 0.1,
            xmax: 1.1,
            ymax: 1.1,
            confidence: 0.5,
            data: (),
        },
    ]];

    soft_non_maximum_suppression(&mut bboxes, Some(0.5), Some(0.1), Some(0.5));

    // First box will be reference box, second box should be decayed
    // Implementation must change to have both be decayed
    assert_eq!(bboxes[0].len(), 2);
    assert!(bboxes[0][0].confidence == 0.5);
    assert!(bboxes[0][1].confidence < 0.5);
    Ok(())
}