import numpy as np
from edge.adapters.movenet_pose import MoveNetPoseAdapter

class _FakeSession:
    """MoveNet 출력 형태 [1,1,17,3] (y,x,score) 정규화."""
    def get_inputs(self):
        class I: name = "input"
        return [I()]
    def run(self, _out, feed):
        kp = np.zeros((1, 1, 17, 3), dtype=np.float32)
        for j in range(17):
            kp[0, 0, j] = [0.5, 0.25, 0.9]  # y=0.5, x=0.25, score=0.9
        return [kp]

def test_infer_maps_movenet_to_coco17_persons():
    frame = np.zeros((400, 800, 3), dtype=np.uint8)
    a = MoveNetPoseAdapter("unused.onnx", session=_FakeSession())
    persons = a.infer(frame)
    assert len(persons) == 1
    p = persons[0]
    assert len(p.keypoints) == 17
    # x = 0.25 * 800 = 200, y = 0.5 * 400 = 200
    assert abs(p.keypoints[0].x - 200) < 1 and abs(p.keypoints[0].y - 200) < 1
    assert abs(p.keypoints[0].conf - 0.9) < 1e-6
    assert p.bbox.x1 <= 200 <= p.bbox.x2

def test_low_score_person_dropped():
    class Low(_FakeSession):
        def run(self, _o, feed):
            return [np.zeros((1, 1, 17, 3), dtype=np.float32)]  # all score 0
    a = MoveNetPoseAdapter("unused.onnx", session=Low())
    assert a.infer(np.zeros((10, 10, 3), np.uint8)) == []