import numpy as np
import pytest

from hermes_vision.detect import Face, FaceDetector, merge, yunet_input_size


@pytest.mark.parametrize('size,expected', [
    ((1296, 972), (640, 480)),
    ((640, 480), (640, 480)),
    ((320, 240), (320, 256)),     # small frames are not upscaled; 240/32 = 7.5 rounds to 8
    ((1920, 1080), (640, 352)),
    ((10, 10), (32, 32)),
])
def test_yunet_input_size_is_a_multiple_of_32(size, expected):
    got = yunet_input_size(*size)
    assert got == expected and got[0] % 32 == 0 and got[1] % 32 == 0


def test_merge_drops_overlapping_boxes_and_keeps_distinct_ones():
    a, b, c = Face(100, 100, 80, 80), Face(105, 98, 78, 82), Face(400, 100, 80, 80)
    assert merge([a, b, c]) == [a, c]


def test_blank_image_has_no_faces():
    det = FaceDetector(model_path='/nonexistent.onnx')      # forces the Haar fallback
    assert det.backend == 'haar'
    assert det.detect(np.zeros((480, 640, 3), np.uint8)) == []