file

This module provides the FileWriter class, which writes predictions to files in various formats.

FileWriter

Bases: BaseWriter

Writer for saving predictions to files in various formats including tensors, images, videos, and ITK images. Custom writer functions can be provided to extend supported formats. Args: path: Directory path where output files will be saved. writer: Either a string specifying a built-in writer or a custom writer function. Built-in writers: - "tensor": Saves raw tensor data (.pt) - "image": Saves as image file (.png) - "video": Saves as video file - "itk_nrrd": Saves as ITK NRRD file (.nrrd) - "itk_seg_nrrd": Saves as ITK segmentation NRRD file (.seg.nrrd) - "itk_nifti": Saves as ITK NIfTI file (.nii.gz) Custom writers must: - Accept (path, tensor) arguments - Handle single tensor input (no batch dimension) - Save output to the specified path

Source code in lighter/callbacks/writer/file.py

class FileWriter(BaseWriter):
    """
    Writer for saving predictions to files in various formats including tensors, images, videos, and ITK images.
    Custom writer functions can be provided to extend supported formats.
    Args:
        path: Directory path where output files will be saved.
        writer: Either a string specifying a built-in writer or a custom writer function.
            Built-in writers:
                - "tensor": Saves raw tensor data (.pt)
                - "image": Saves as image file (.png)
                - "video": Saves as video file
                - "itk_nrrd": Saves as ITK NRRD file (.nrrd)
                - "itk_seg_nrrd": Saves as ITK segmentation NRRD file (.seg.nrrd)
                - "itk_nifti": Saves as ITK NIfTI file (.nii.gz)
            Custom writers must:
                - Accept (path, tensor) arguments
                - Handle single tensor input (no batch dimension)
                - Save output to the specified path
    """

    @property
    def writers(self) -> dict[str, Callable]:
        return {
            "tensor": write_tensor,
            "image": write_image,
            "video": write_video,
            "itk_nrrd": partial(write_itk_image, suffix=".nrrd"),
            "itk_seg_nrrd": partial(write_itk_image, suffix=".seg.nrrd"),
            "itk_nifti": partial(write_itk_image, suffix=".nii.gz"),
        }

    def write(self, tensor: Tensor, identifier: int | str) -> None:
        """
        Writes the tensor to a file using the specified writer.

        Args:
            tensor: The tensor to write.
            identifier: Identifier for naming the file.
        """
        if not self.path.is_dir():
            raise RuntimeError(f"FileWriter expects a directory path, got {self.path}")

        # Determine the path for the file based on prediction count. The suffix must be added by the writer function.
        path = self.path / str(identifier)
        # Write the tensor to the file.
        self.writer(path, tensor)

write(tensor, identifier)

Writes the tensor to a file using the specified writer.

Parameters:

Name	Type	Description	Default
tensor	Tensor	The tensor to write.	required
identifier	int | str	Identifier for naming the file.	required

Source code in lighter/callbacks/writer/file.py

def write(self, tensor: Tensor, identifier: int | str) -> None:
    """
    Writes the tensor to a file using the specified writer.

    Args:
        tensor: The tensor to write.
        identifier: Identifier for naming the file.
    """
    if not self.path.is_dir():
        raise RuntimeError(f"FileWriter expects a directory path, got {self.path}")

    # Determine the path for the file based on prediction count. The suffix must be added by the writer function.
    path = self.path / str(identifier)
    # Write the tensor to the file.
    self.writer(path, tensor)

write_image(path, tensor)

Writes a tensor as an image file in .png format.

Parameters:

Name	Type	Description	Default
path		The path to save the image.	required
tensor		The tensor representing the image.	required

Source code in lighter/callbacks/writer/file.py

def write_image(path, tensor):
    """
    Writes a tensor as an image file in .png format.

    Args:
        path: The path to save the image.
        tensor: The tensor representing the image.
    """
    path = path.with_suffix(".png")
    tensor = preprocess_image(tensor)
    torchvision.io.write_png(tensor, str(path))

write_itk_image(path, tensor, suffix)

Writes a tensor as an ITK image file.

Parameters:

Name	Type	Description	Default
path	str	The path to save the ITK image.	required
tensor	MetaTensor	The tensor representing the image. Must be in MONAI MetaTensor format.	required
suffix		The file suffix indicating the format.	required

Source code in lighter/callbacks/writer/file.py

def write_itk_image(path: str, tensor: MetaTensor, suffix) -> None:
    """
    Writes a tensor as an ITK image file.

    Args:
        path: The path to save the ITK image.
        tensor: The tensor representing the image. Must be in MONAI MetaTensor format.
        suffix: The file suffix indicating the format.
    """
    path = path.with_suffix(suffix)
    if not isinstance(tensor, MetaTensor):
        raise TypeError("Tensor must be in MONAI MetaTensor format.")
    itk_image = metatensor_to_itk_image(tensor, channel_dim=0, dtype=tensor.dtype)
    OPTIONAL_IMPORTS["itk"].imwrite(itk_image, str(path), True)

write_tensor(path, tensor)

Writes a tensor to a file in .pt format.

Parameters:

Name	Type	Description	Default
path		The path to save the tensor.	required
tensor		The tensor to save.	required

Source code in lighter/callbacks/writer/file.py

def write_tensor(path, tensor):
    """
    Writes a tensor to a file in .pt format.

    Args:
        path: The path to save the tensor.
        tensor: The tensor to save.
    """
    torch.save(tensor, path.with_suffix(".pt"))  # nosec B614

write_video(path, tensor)

Writes a tensor as a video file in .mp4 format.

Parameters:

Name	Type	Description	Default
path		The path to save the video.	required
tensor		The tensor representing the video.	required

Source code in lighter/callbacks/writer/file.py

def write_video(path, tensor):
    """
    Writes a tensor as a video file in .mp4 format.

    Args:
        path: The path to save the video.
        tensor: The tensor representing the video.
    """
    path = path.with_suffix(".mp4")
    # Video tensor must be divisible by 2. Pad the height and width.
    tensor = DivisiblePad(k=(0, 2, 2), mode="minimum")(tensor)
    # Video tensor must be THWC. Permute CTHW -> THWC.
    tensor = tensor.permute(1, 2, 3, 0)
    # Video tensor must have 3 channels (RGB). Repeat the channel dim to convert grayscale to RGB.
    if tensor.shape[-1] == 1:
        tensor = tensor.repeat(1, 1, 1, 3)
    # Video tensor must be in the range [0, 1]. Scale to [0, 255].
    tensor = (tensor * 255).to(torch.uint8)
    torchvision.io.write_video(str(path), tensor, fps=24)