def test_fasterrcnn_bbone_train(tmpdir):
model = FasterRCNN(backbone="resnet18", fpn=True, pretrained_backbone=True)
train_dl = DataLoader(DummyDetectionDataset(), collate_fn=_collate_fn)
valid_dl = DataLoader(DummyDetectionDataset(), collate_fn=_collate_fn)
trainer = pl.Trainer(fast_dev_run=True, default_root_dir=tmpdir)
trainer.fit(model, train_dl, valid_dl)
def test_fasterrcnn_train(tmpdir):
model = FasterRCNN()
train_dl = DataLoader(DummyDetectionDataset(), collate_fn=_collate_fn)
valid_dl = DataLoader(DummyDetectionDataset(), collate_fn=_collate_fn)
trainer = pl.Trainer(fast_dev_run=True, default_root_dir=tmpdir)
trainer.fit(model, train_dataloader=train_dl, val_dataloaders=valid_dl)
def test_fasterrcnn_train(tmpdir):
model = FasterRCNN(pretrained=False, pretrained_backbone=False)
train_dl = DataLoader(DummyDetectionDataset(), collate_fn=_collate_fn)
valid_dl = DataLoader(DummyDetectionDataset(), collate_fn=_collate_fn)
trainer = Trainer(fast_dev_run=True,
logger=False,
checkpoint_callback=False,
default_root_dir=tmpdir)
trainer.fit(model, train_dataloader=train_dl, val_dataloaders=valid_dl)
def test_retinanet_backbone_train(tmpdir):
model = RetinaNet(backbone="resnet18", fpn=True, pretrained_backbone=False)
train_dl = DataLoader(DummyDetectionDataset(), collate_fn=_collate_fn)
valid_dl = DataLoader(DummyDetectionDataset(), collate_fn=_collate_fn)
trainer = Trainer(fast_dev_run=True,
logger=False,
checkpoint_callback=False,
default_root_dir=tmpdir)
model = FasterRCNN(backbone="resnet18",
fpn=True,
pretrained_backbone=False,
pretrained=False)
train_dl = DataLoader(DummyDetectionDataset(), collate_fn=_collate_fn)
valid_dl = DataLoader(DummyDetectionDataset(), collate_fn=_collate_fn)
trainer.fit(model, train_dl, valid_dl)
def test_fasterrcnn():
model = FasterRCNN()
image = torch.rand(1, 3, 400, 400)
model(image)
def test_fasterrcnn():
model = FasterRCNN(pretrained=False, pretrained_backbone=False)
image = torch.rand(1, 3, 224, 224)
model(image)
