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76 lines
2.4 KiB
Python
76 lines
2.4 KiB
Python
__version__ = "1.0"
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from meshroom.core import desc
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from meshroom.core.utils import VERBOSE_LEVEL
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class CheckerboardDetection(desc.AVCommandLineNode):
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commandLine = 'aliceVision_checkerboardDetection {allParams}'
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size = desc.DynamicNodeSize('input')
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parallelization = desc.Parallelization(blockSize=5)
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commandLineRange = '--rangeStart {rangeStart} --rangeSize {rangeBlockSize}'
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category = 'Other'
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documentation = '''
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Detect checkerboard structures in a set of images.
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The detection method also supports nested calibration grids.
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'''
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inputs = [
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desc.File(
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name="input",
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label="Input",
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description="Input SfMData file. Viewpoints must correspond to lens calibration grids.",
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value="",
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),
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desc.BoolParam(
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name="useNestedGrids",
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label="Nested Calibration Grid",
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description="Enable if images contain nested calibration grids. These grids must be centered on the image center.",
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value=False,
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),
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desc.BoolParam(
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name="doubleSize",
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label="Double Size",
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description="Double the image size prior to processing.",
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value=False,
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),
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desc.BoolParam(
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name="ignorePixelAspectRatio",
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label="Ignore Pixel Aspect Ratio",
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description="Ignore pixel aspect ratio for detection.",
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value=False,
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),
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desc.BoolParam(
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name="exportDebugImages",
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label="Export Debug Images",
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description="Export debug images.",
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value=False,
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),
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desc.ChoiceParam(
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name="verboseLevel",
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label="Verbose Level",
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description="Verbosity level (fatal, error, warning, info, debug, trace).",
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values=VERBOSE_LEVEL,
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value="info",
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exclusive=True,
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),
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]
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outputs = [
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desc.File(
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name="output",
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label="Folder",
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description="Output folder.",
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value=desc.Node.internalFolder,
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),
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desc.File(
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name="checkerLines",
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enabled=lambda node: node.exportDebugImages.value,
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label="Checker Lines",
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description="Debug images.",
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semantic="image",
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value=desc.Node.internalFolder + "<VIEW_ID>.png",
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group="", # do not export on the command line
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),
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]
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