Glenn Jocher dce4efce48
ultralytics 8.0.100 add Mosaic9() augmentation (#2605)
Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
Co-authored-by: Tommy in Tongji <36354458+TommyZihao@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: BIGBOSS-FOX <47949596+BIGBOSS-FOX@users.noreply.github.com>
Co-authored-by: xbkaishui <xxkaishui@gmail.com>
2023-05-14 20:43:35 +02:00

36 lines
1.4 KiB
Python

# SAM model interface
from ultralytics.yolo.cfg import get_cfg
from .build import build_sam
from .predict import Predictor
class SAM:
def __init__(self, model='sam_b.pt') -> None:
if model and not model.endswith('.pt') and not model.endswith('.pth'):
# Should raise AssertionError instead?
raise NotImplementedError('Segment anything prediction requires pre-trained checkpoint')
self.model = build_sam(model)
self.predictor = None # reuse predictor
def predict(self, source, stream=False, **kwargs):
"""Predicts and returns segmentation masks for given image or video source."""
overrides = dict(conf=0.25, task='segment', mode='predict')
overrides.update(kwargs) # prefer kwargs
if not self.predictor:
self.predictor = Predictor(overrides=overrides)
self.predictor.setup_model(model=self.model)
else: # only update args if predictor is already setup
self.predictor.args = get_cfg(self.predictor.args, overrides)
return self.predictor(source, stream=stream)
def train(self, **kwargs):
"""Function trains models but raises an error as SAM models do not support training."""
raise NotImplementedError("SAM models don't support training")
def val(self, **kwargs):
"""Run validation given dataset."""
raise NotImplementedError("SAM models don't support validation")