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ultralytics 8.0.12 - Hydra removal (#506)

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Pronoy Mandal <lukex9442@gmail.com>
Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
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Glenn Jocher 2023-01-21 00:45:19 +01:00 • committed by GitHub
parent 6eec39162a
commit c5fccc3fc4
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37 changed files with 395 additions and 469 deletions
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12
ultralytics/yolo/engine/predictor.py
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@ -36,7 +36,7 @@ from ultralytics.nn.autobackend import AutoBackend
from ultralytics.yolo.configs import get_config
from ultralytics.yolo.data.dataloaders.stream_loaders import LoadImages, LoadPilAndNumpy, LoadScreenshots, LoadStreams
from ultralytics.yolo.data.utils import IMG_FORMATS, VID_FORMATS
from ultralytics.yolo.utils import DEFAULT_CONFIG, LOGGER, SETTINGS, callbacks, colorstr, ops
from ultralytics.yolo.utils import DEFAULT_CFG_PATH, LOGGER, SETTINGS, callbacks, colorstr, ops
from ultralytics.yolo.utils.checks import check_file, check_imgsz, check_imshow
from ultralytics.yolo.utils.files import increment_path
from ultralytics.yolo.utils.torch_utils import select_device, smart_inference_mode
@ -49,7 +49,7 @@ class BasePredictor:
A base class for creating predictors.
Attributes:
args (OmegaConf): Configuration for the predictor.
args (SimpleNamespace): Configuration for the predictor.
save_dir (Path): Directory to save results.
done_setup (bool): Whether the predictor has finished setup.
model (nn.Module): Model used for prediction.
@ -62,7 +62,7 @@ class BasePredictor:
data_path (str): Path to data.
"""
def __init__(self, config=DEFAULT_CONFIG, overrides=None):
def __init__(self, config=DEFAULT_CFG_PATH, overrides=None):
"""
Initializes the BasePredictor class.
@ -70,8 +70,6 @@ class BasePredictor:
config (str, optional): Path to a configuration file. Defaults to DEFAULT_CONFIG.
overrides (dict, optional): Configuration overrides. Defaults to None.
"""
if overrides is None:
overrides = {}
self.args = get_config(config, overrides)
project = self.args.project or Path(SETTINGS['runs_dir']) / self.args.task
name = self.args.name or f"{self.args.mode}"
@ -157,7 +155,7 @@ class BasePredictor:
if stream:
return self.stream_inference(source, model, verbose)
else:
return list(chain(*list(self.stream_inference(source, model, verbose)))) # merge list of Result into one
return list(self.stream_inference(source, model, verbose)) # merge list of Result into one
def predict_cli(self):
# Method used for CLI prediction. It uses always generator as outputs as not required by CLI mode
@ -211,7 +209,7 @@ class BasePredictor:
if self.args.save:
self.save_preds(vid_cap, i, str(self.save_dir / p.name))
yield results
yield from results
# Print time (inference-only)
if verbose: