neuralib.deeplabcut.core.DeepLabCutMeta

class neuralib.deeplabcut.core.DeepLabCutMeta[source]

Bases: TypedDict

DeepLabCut model metadata

__init__(*args, **kwargs)

Methods

__init__(*args, **kwargs)

clear()

copy()

fromkeys(iterable[, value])

Create a new dictionary with keys from iterable and values set to value.

get(key[, default])

Return the value for key if key is in the dictionary, else default.

items()

keys()

pop(k[,d])

If the key is not found, return the default if given; otherwise, raise a KeyError.

popitem()

Remove and return a (key, value) pair as a 2-tuple.

setdefault(key[, default])

Insert key with a value of default if key is not in the dictionary.

update([E, ]**F)

If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]

values()

Attributes

start

stop

run_duration

Scorer

model_config

fps

batch_size

frame_dimensions

nframes

iteration

training_set_fraction

cropping

cropping_parameters

start: float
stop: float
run_duration: float
Scorer: str
model_config: DeepLabCutModelConfig
fps: float
batch_size: int
frame_dimensions: tuple[int, int]
nframes: int
iteration: int
training_set_fraction: float
cropping: bool
cropping_parameters: list[tuple[float, float, float, float]]