def get(config_path, trained: bool = False):
"""
Get a model specified by relative path under FsDet's official ``configs/`` directory.
Args:
config_path (str): config file name relative to FsDet's "configs/"
directory, e.g., "COCO-detection/faster_rcnn_R_101_FPN_ft_all_1shot.yaml"
trained (bool): If True, will initialize the model with the trained model zoo weights.
If False, the checkpoint specified in the config file's ``MODEL.WEIGHTS`` is used
instead; this will typically (though not always) initialize a subset of weights using
an ImageNet pre-trained model, while randomly initializing the other weights.
Example:
.. code-block:: python
from fsdet import model_zoo
model = model_zoo.get("COCO-detection/faster_rcnn_R_101_FPN_ft_all_1shot.yaml", trained=True)
"""
cfg_file = get_config_file(config_path)
cfg = get_cfg()
cfg.merge_from_file(cfg_file)
if trained:
cfg.MODEL.WEIGHTS = get_checkpoint_url(config_path)
if not torch.cuda.is_available():
cfg.MODEL.DEVICE = "cpu"
model = build_model(cfg)
DetectionCheckpointer(model).load(cfg.MODEL.WEIGHTS)
return model
def setup(args):
cfg = get_cfg()
if args.config_file:
cfg.merge_from_file(args.config_file)
cfg.merge_from_list(args.opts)
cfg.freeze()
return cfg
def setup_cfg(args):
# load config from file and command-line arguments
cfg = get_cfg()
cfg.merge_from_file(args.config_file)
cfg.merge_from_list(args.opts)
# Set score_threshold for builtin models
cfg.MODEL.RETINANET.SCORE_THRESH_TEST = args.confidence_threshold
cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = args.confidence_threshold
cfg.freeze()
return cfg
def setup(args):
"""
Create configs and perform basic setups.
"""
cfg = get_cfg()
cfg.merge_from_file(args.config_file)
cfg.merge_from_list(args.opts)
cfg.freeze()
set_global_cfg(cfg)
default_setup(cfg, args)
return cfg
def setup(args):
"""
Create configs and perform basic setups.
"""
cfg = get_cfg()
#cfg.merge_from_file(model_zoo.get_config_file("COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml"))
#cfg.DATALOADER.NUM_WORKERS = 4
#cfg.MODEL.WEIGHTS = model_zoo.get_checkpoint_url("COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml") # Let training initialize from model zoo
cfg.merge_from_file(args.config_file)
#if args.opts:
# cfg.merge_from_list(args.opts)
cfg.freeze()
set_global_cfg(cfg)
default_setup(cfg, args)
return cfg