def test_track_basic(self):
tracker = PanopticTracker(MockDataset())
model = MockModel()
tracker.track(
model,
data=Data(pos=torch.tensor([[1, 2]]),
batch=torch.tensor([0, 0, 0])),
min_cluster_points=0,
iou_threshold=0.25,
)
metrics = tracker.get_metrics()
self.assertAlmostEqual(metrics["train_Iacc"], 1)
self.assertAlmostEqual(metrics["train_pos"], 1)
self.assertAlmostEqual(metrics["train_neg"], 0)
def get_tracker(self, wandb_log: bool, tensorboard_log: bool):
"""Factory method for the tracker
Arguments:
wandb_log - Log using weight and biases
Returns:
[BaseTracker] -- tracker
"""
return PanopticTracker(self,
wandb_log=wandb_log,
use_tensorboard=tensorboard_log)
def test_track_finalise(self):
tracker = PanopticTracker(MockDataset())
model = MockModel()
tracker.track(
model,
data=Data(pos=torch.tensor([[1, 2]]),
batch=torch.tensor([0, 0, 0])),
min_cluster_points=0,
iou_threshold=0.25,
track_instances=True,
)
tracker.finalise(
track_instances=True,
iou_threshold=0.25,
)
metrics = tracker.get_metrics()
self.assertAlmostEqual(metrics["train_map"], 1)