def main(cfg_file):
print(cfg_file)
cfg = load_cfg(cfg_file)
data_loader = build_detection_train_loader(cfg)
device = torch.device("cuda")
model = build_model(cfg).to(device)
for data in data_loader:
ipdb.set_trace()
def test_model(cfg_file):
# get cfg
cfg = get_cfg()
cfg.merge_from_file(cfg_file)
cfg.SOLVER.IMS_PER_BATCH = 1
# get model
device = torch.device("cuda")
model = build_model(cfg).to(device)
ipdb.set_trace()
def build_model(cls, cfg):
"""
Returns:
torch.nn.Module:
It now calls :func:`slender_det.modeling.build_model`.
Overwrite it for using our own model.
"""
model = build_model(cfg)
logger = logging.getLogger(__name__)
logger.info("Model:\n{}".format(model))
return model
def test_training(cfg_file):
# get cfg
cfg = get_cfg()
cfg.merge_from_file(cfg_file)
cfg.SOLVER.IMS_PER_BATCH = 2
# get batch data
data_loader = build_detection_train_loader(cfg)
data_loader_iter = iter(data_loader)
data = next(data_loader_iter)
print(len(data))
# get model
device = torch.device("cuda")
model = build_model(cfg).to(device)
model.train()
outs = model(data[:2])
ipdb.set_trace()
from detectron2.data import MetadataCatalog, build_detection_train_loader
from detectron2.checkpoint import DetectionCheckpointer
import init_paths
from slender_det.config import get_cfg
from slender_det.modeling import build_model
# get cfg
cfg = get_cfg()
cfg.merge_from_file("configs/rep-points/rep_pointsv2_R_50_FPN_1x.yaml")
cfg.SOLVER.IMS_PER_BATCH = 2
# get model
device = torch.device("cuda")
model = build_model(cfg).to(device)
# get batch data
data_loader = build_detection_train_loader(cfg)
data_loader_iter = iter(data_loader)
data = next(data_loader_iter)
def test_training():
model.train()
outs = model(data[:2])
import pdb
pdb.set_trace()
def test_load_pt():
model = build_model(cfg)
ipdb.set_trace()
from detectron2.data import MetadataCatalog, build_detection_train_loader
from detectron2.checkpoint import DetectionCheckpointer
import init_paths
from slender_det.config import get_cfg
from slender_det.modeling.backbone import build_backbone
from slender_det.modeling import build_model
# get cfg
cfg = get_cfg()
cfg.merge_from_file("configs/corner/Base-CornerNet.yaml")
# get model
device = torch.device("cuda")
model = build_model(cfg)
# get batch data
data_loader = build_detection_train_loader(cfg)
data_loader_iter = iter(data_loader)
data = next(data_loader_iter)
def test_backbone():
backbone = build_backbone(cfg).to(device)
images = torch.empty((2, 3, 512, 512)).to(device)
assert isinstance(backbone, nn.Module)
num = 0
for module in backbone.modules():
if isinstance(module, nn.Conv2d):