Saving output in a task type¶

Primitive parameters¶

Primitive outputs (of type Int, Float, String or Bool; see Parameter Types) can be stored directly via the Python module xfworkerutil.

For example Lucid.CLIP.StatMinMax stores minimum and maximum output parameters:

import xfworkerutil

import clip_runtop

worker = xfworkerutil.XFWorkerJob()

inputs = worker.job['inputs']
calibration_name = inputs['calibration']

# Download input files
image = worker.get_omni_image(inputs['image'])

# CLIP
min, max = clip_runtop.runtop_min_max(image, worker.working_dir.path / "temp")

if calibration_name is not None:
    calibrations = image.pixel_calibrations_of_unit_type(calibration_name)
    if len(calibrations) == 0:
        worker.error(f"Image is missing calibration metadata of type {calibration_name}")
    calibration = calibrations[0]
    min = calibration.raw_to_calibrated(min)
    max = calibration.raw_to_calibrated(max)

# Save outputs
outputs = {
    "min": min,
    "max": max,
}
worker.finish(outputs)

Bulk data¶

Composite parameters like Image refer to bulk data that should be stored separately on FSS.

OMNI image data can be stored using the xfworkerutil.XFWorkerJob.upload_omni_output(). The returned value should be passed to xfworkerutil.XFWorkerJob.finish() for the respective output key. For example Lucid.CLIP.Threshold does this as follows:

import xfworkerutil

import clip_thres

worker = xfworkerutil.XFWorkerJob()

inputs = worker.job['inputs']
threshold_lower = inputs['threshold_lower0']
threshold_upper = inputs['threshold_upper0']

# Download input files
image = worker.get_omni_image(inputs['image'])

seg_image_omni_path = worker.create_related_path(image.metadata_path, '_seg.omni')
seg_image_pixels_path = worker.create_related_path(image.metadata_path, '_seg.raw')
thres_temp_dir_path = worker.working_dir.path / "thres"

# CLIP
seg_image = clip_thres.thres_image(
    image,
    threshold_lower,
    threshold_upper,
    seg_image_omni_path,
    seg_image_pixels_path,
    thres_temp_dir_path)

# Upload output files
seg_image_output = worker.upload_omni_output(seg_image)

# Save outputs
outputs = {
    "segments": seg_image_output,
}
worker.finish(outputs)