import torch
from torchmetrics.detection.mean_ap import MeanAveragePrecision
preds = lambda: [dict(
    boxes=torch.tensor([[258.0, 41.0, 606.0, 285.0]]) + torch.randint(10, (1,4)),
    scores=torch.tensor([0.536]) + 0.1*torch.rand(1),
    labels=torch.tensor([0]),
)]
target = [dict(
    boxes=torch.tensor([[214.0, 41.0, 562.0, 285.0]]),
    labels=torch.tensor([0]),
)]
metric = MeanAveragePrecision()
vals = []
for _ in range(20):
    vals.append(metric(preds(), target))
fig_, ax_ = metric.plot(vals)