Data formats¶
sleap_io.load_file(filename, format=None, **kwargs)
¶
Load a file and return the appropriate object.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
filename |
str | Path
|
Path to a file. |
required |
format |
Optional[str]
|
Optional format to load as. If not provided, will be inferred from the file extension. Available formats are: "slp", "nwb", "labelstudio", "jabs" and "video". |
None
|
Returns:
Type | Description |
---|---|
Union[Labels, Video]
|
A |
Source code in sleap_io/io/main.py
def load_file(
filename: str | Path, format: Optional[str] = None, **kwargs
) -> Union[Labels, Video]:
"""Load a file and return the appropriate object.
Args:
filename: Path to a file.
format: Optional format to load as. If not provided, will be inferred from the
file extension. Available formats are: "slp", "nwb", "labelstudio", "jabs"
and "video".
Returns:
A `Labels` or `Video` object.
"""
if isinstance(filename, Path):
filename = filename.as_posix()
if format is None:
if filename.endswith(".slp"):
format = "slp"
elif filename.endswith(".nwb"):
format = "nwb"
elif filename.endswith(".json"):
format = "json"
elif filename.endswith(".h5"):
format = "jabs"
else:
for vid_ext in Video.EXTS:
if filename.endswith(vid_ext):
format = "video"
break
if format is None:
raise ValueError(f"Could not infer format from filename: '{filename}'.")
if filename.endswith(".slp"):
return load_slp(filename, **kwargs)
elif filename.endswith(".nwb"):
return load_nwb(filename, **kwargs)
elif filename.endswith(".json"):
return load_labelstudio(filename, **kwargs)
elif filename.endswith(".h5"):
return load_jabs(filename, **kwargs)
elif format == "video":
return load_video(filename, **kwargs)
sleap_io.save_file(labels, filename, format=None, **kwargs)
¶
Save a file based on the extension.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
labels |
Labels
|
A SLEAP |
required |
filename |
str | Path
|
Path to save labels to. |
required |
format |
Optional[str]
|
Optional format to save as. If not provided, will be inferred from the file extension. Available formats are: "slp", "nwb", "labelstudio" and "jabs". |
None
|
Source code in sleap_io/io/main.py
def save_file(
labels: Labels, filename: str | Path, format: Optional[str] = None, **kwargs
):
"""Save a file based on the extension.
Args:
labels: A SLEAP `Labels` object (see `load_slp`).
filename: Path to save labels to.
format: Optional format to save as. If not provided, will be inferred from the
file extension. Available formats are: "slp", "nwb", "labelstudio" and
"jabs".
"""
if isinstance(filename, Path):
filename = str(filename)
if format is None:
if filename.endswith(".slp"):
format = "slp"
elif filename.endswith(".nwb"):
format = "nwb"
elif filename.endswith(".json"):
format = "labelstudio"
elif "pose_version" in kwargs:
format = "jabs"
if format == "slp":
save_slp(labels, filename, **kwargs)
elif format == "nwb":
save_nwb(labels, filename, **kwargs)
elif format == "labelstudio":
save_labelstudio(labels, filename, **kwargs)
elif format == "jabs":
pose_version = kwargs.pop("pose_version", 5)
save_jabs(labels, pose_version, filename, **kwargs)
else:
raise ValueError(f"Unknown format '{format}' for filename: '{filename}'.")
sleap_io.load_video(filename, **kwargs)
¶
Load a video file.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
filename |
str
|
The filename(s) of the video. Supported extensions: "mp4", "avi", "mov", "mj2", "mkv", "h5", "hdf5", "slp", "png", "jpg", "jpeg", "tif", "tiff", "bmp". If the filename is a list, a list of image filenames are expected. If filename is a folder, it will be searched for images. |
required |
Returns:
Type | Description |
---|---|
Video
|
A |
Source code in sleap_io/io/main.py
def load_video(filename: str, **kwargs) -> Video:
"""Load a video file.
Args:
filename: The filename(s) of the video. Supported extensions: "mp4", "avi",
"mov", "mj2", "mkv", "h5", "hdf5", "slp", "png", "jpg", "jpeg", "tif",
"tiff", "bmp". If the filename is a list, a list of image filenames are
expected. If filename is a folder, it will be searched for images.
Returns:
A `Video` object.
"""
return Video.from_filename(filename, **kwargs)
sleap_io.load_slp(filename)
¶
Load a SLEAP dataset.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
filename |
str
|
Path to a SLEAP labels file ( |
required |
Returns:
Type | Description |
---|---|
Labels
|
The dataset as a |
sleap_io.save_slp(labels, filename, embed=None)
¶
Save a SLEAP dataset to a .slp
file.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
labels |
Labels
|
A SLEAP |
required |
filename |
str
|
Path to save labels to ending with |
required |
embed |
bool | str | list[tuple[Video, int]] | None
|
Frames to embed in the saved labels file. One of If If If This argument is only valid for the SLP backend. |
None
|
Source code in sleap_io/io/main.py
def save_slp(
labels: Labels,
filename: str,
embed: bool | str | list[tuple[Video, int]] | None = None,
):
"""Save a SLEAP dataset to a `.slp` file.
Args:
labels: A SLEAP `Labels` object (see `load_slp`).
filename: Path to save labels to ending with `.slp`.
embed: Frames to embed in the saved labels file. One of `None`, `True`,
`"all"`, `"user"`, `"suggestions"`, `"user+suggestions"`, `"source"` or list
of tuples of `(video, frame_idx)`.
If `None` is specified (the default) and the labels contains embedded
frames, those embedded frames will be re-saved to the new file.
If `True` or `"all"`, all labeled frames and suggested frames will be
embedded.
If `"source"` is specified, no images will be embedded and the source video
will be restored if available.
This argument is only valid for the SLP backend.
"""
return slp.write_labels(filename, labels, embed=embed)
sleap_io.load_nwb(filename)
¶
Load an NWB dataset as a SLEAP Labels
object.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
filename |
str
|
Path to a NWB file ( |
required |
Returns:
Type | Description |
---|---|
Labels
|
The dataset as a |
sleap_io.save_nwb(labels, filename, append=True)
¶
Save a SLEAP dataset to NWB format.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
labels |
Labels
|
A SLEAP |
required |
filename |
str
|
Path to NWB file to save to. Must end in |
required |
append |
bool
|
If |
True
|
See also: nwb.write_nwb, nwb.append_nwb
Source code in sleap_io/io/main.py
def save_nwb(labels: Labels, filename: str, append: bool = True):
"""Save a SLEAP dataset to NWB format.
Args:
labels: A SLEAP `Labels` object (see `load_slp`).
filename: Path to NWB file to save to. Must end in `.nwb`.
append: If `True` (the default), append to existing NWB file. File will be
created if it does not exist.
See also: nwb.write_nwb, nwb.append_nwb
"""
if append and Path(filename).exists():
nwb.append_nwb(labels, filename)
else:
nwb.write_nwb(labels, filename)
sleap_io.load_jabs(filename, skeleton=None)
¶
Read JABS-style predictions from a file and return a Labels
object.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
filename |
str
|
Path to the jabs h5 pose file. |
required |
skeleton |
Optional[Skeleton]
|
An optional |
None
|
Returns:
Type | Description |
---|---|
Labels
|
Parsed labels as a |
Source code in sleap_io/io/main.py
def load_jabs(filename: str, skeleton: Optional[Skeleton] = None) -> Labels:
"""Read JABS-style predictions from a file and return a `Labels` object.
Args:
filename: Path to the jabs h5 pose file.
skeleton: An optional `Skeleton` object.
Returns:
Parsed labels as a `Labels` instance.
"""
return jabs.read_labels(filename, skeleton=skeleton)
sleap_io.save_jabs(labels, pose_version, root_folder=None)
¶
Save a SLEAP dataset to JABS pose file format.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
labels |
Labels
|
SLEAP |
required |
pose_version |
int
|
The JABS pose version to write data out. |
required |
root_folder |
Optional[str]
|
Optional root folder where the files should be saved. |
None
|
Note
Filenames for JABS poses are based on video filenames.
Source code in sleap_io/io/main.py
def save_jabs(labels: Labels, pose_version: int, root_folder: Optional[str] = None):
"""Save a SLEAP dataset to JABS pose file format.
Args:
labels: SLEAP `Labels` object.
pose_version: The JABS pose version to write data out.
root_folder: Optional root folder where the files should be saved.
Note:
Filenames for JABS poses are based on video filenames.
"""
jabs.write_labels(labels, pose_version, root_folder)
sleap_io.load_labelstudio(filename, skeleton=None)
¶
Read Label Studio-style annotations from a file and return a Labels
object.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
filename |
str
|
Path to the label-studio annotation file in JSON format. |
required |
skeleton |
Optional[Union[Skeleton, list[str]]]
|
An optional |
None
|
Returns:
Type | Description |
---|---|
Labels
|
Parsed labels as a |
Source code in sleap_io/io/main.py
def load_labelstudio(
filename: str, skeleton: Optional[Union[Skeleton, list[str]]] = None
) -> Labels:
"""Read Label Studio-style annotations from a file and return a `Labels` object.
Args:
filename: Path to the label-studio annotation file in JSON format.
skeleton: An optional `Skeleton` object or list of node names. If not provided
(the default), skeleton will be inferred from the data. It may be useful to
provide this so the keypoint label types can be filtered to just the ones in
the skeleton.
Returns:
Parsed labels as a `Labels` instance.
"""
return labelstudio.read_labels(filename, skeleton=skeleton)