def label_frames(config, multiple_individualsGUI=False, imtypes=["*.png"]):
"""
Manually label/annotate the extracted frames. Update the list of body parts you want to localize in the config.yaml file first.
Parameter
----------
config : string
String containing the full path of the config file in the project.
multiple_individualsGUI: bool, optional
If this is set to True, a user can label multiple individuals. Note for "multianimalproject=True" this is automatically used.
The default is ``False``; if provided it must be either ``True`` or ``False``.
imtypes: list of imagetypes to look for in folder to be labeled. By default only png images are considered.
Example
--------
Standard use case:
>>> deeplabcut.label_frames('/myawesomeproject/reaching4thestars/config.yaml')
To label multiple individuals (without having a multiple individuals project); otherwise this GUI is loaded automatically
>>> deeplabcut.label_frames('/analysis/project/reaching-task/config.yaml',multiple_individualsGUI=True)
To label other image types
>>> label_frames(config,multiple=False,imtypes=['*.jpg','*.jpeg'])
--------
"""
startpath = os.getcwd()
wd = Path(config).resolve().parents[0]
os.chdir(str(wd))
cfg = auxiliaryfunctions.read_config(config)
if cfg.get("multianimalproject", False) or multiple_individualsGUI:
from deeplabcut.generate_training_dataset import (
multiple_individuals_labeling_toolbox,
)
multiple_individuals_labeling_toolbox.show(config)
else:
from deeplabcut.generate_training_dataset import labeling_toolbox
labeling_toolbox.show(config, imtypes=imtypes)
os.chdir(startpath)
def label_frames(config, multiple=False, imtypes=['*.png']):
"""
Manually label/annotate the extracted frames. Update the list of body parts you want to localize in the config.yaml file first.
Parameter
----------
config : string
String containing the full path of the config file in the project.
multiple: bool, optional
If this is set to True, a user can label multiple individuals.
The default is ``False``; if provided it must be either ``True`` or ``False``.
imtypes: list of imagetypes to look for in folder to be labeled. By default only png images are considered.
Example
--------
Standard use case:
>>> deeplabcut.label_frames('/myawesomeproject/reaching4thestars/config.yaml')
To label multiple individuals
>>> deeplabcut.label_frames('/analysis/project/reaching-task/config.yaml',multiple=True)
To label other image types
>>> label_frames(config,multiple=False,imtypes=['*.jpg','*.jpeg'])
--------
"""
startpath = os.getcwd()
wd = Path(config).resolve().parents[0]
os.chdir(str(wd))
if multiple == False:
from deeplabcut.generate_training_dataset import labeling_toolbox
# labeling_toolbox.show(config,Screens,scale_w,scale_h, winHack, img_scale)
labeling_toolbox.show(config, imtypes=imtypes)
else:
from deeplabcut.generate_training_dataset import multiple_individuals_labeling_toolbox
multiple_individuals_labeling_toolbox.show(config)
os.chdir(startpath)