def buildIntrinsics(self, cameraInit, additionalViews):
"""
Build up-to-date intrinsics and views based on already loaded + additional images.
Does not modify the graph, can be called outside the main thread.
Emits intrinsicBuilt(views, intrinsics) when done.
"""
views = []
intrinsics = []
# Duplicate 'cameraInit' outside the graph.
# => allows to compute intrinsics without modifying the node or the graph
# If cameraInit is None (i.e: SfM augmentation):
# * create an uninitialized node
# * wait for the result before actually creating new nodes in the graph (see onIntrinsicsAvailable)
inputs = cameraInit.toDict()["inputs"] if cameraInit else {}
cameraInitCopy = Node("CameraInit", **inputs)
try:
self.setBuildingIntrinsics(True)
# Retrieve the list of updated viewpoints and intrinsics
views, intrinsics = cameraInitCopy.nodeDesc.buildIntrinsics(
cameraInitCopy, additionalViews)
except Exception:
import traceback
logging.error("Error while building intrinsics : {}".format(
traceback.format_exc()))
# Delete the duplicate
cameraInitCopy.deleteLater()
self.setBuildingIntrinsics(False)
# always emit intrinsicsBuilt signal to inform listeners
# in other threads that computation is over
self.intrinsicsBuilt.emit(cameraInit, views, intrinsics)
def setupTempCameraInit(self, node, attrName):
if not node or not attrName:
self.tempCameraInit = None
return
sfmFile = node.attribute(attrName).value
if not sfmFile or not os.path.isfile(sfmFile):
self.tempCameraInit = None
return
nodeDesc = meshroom.core.nodesDesc["CameraInit"]()
views, intrinsics = nodeDesc.readSfMData(sfmFile)
tmpCameraInit = Node("CameraInit",
viewpoints=views,
intrinsics=intrinsics)
self.tempCameraInit = tmpCameraInit
def buildIntrinsics(self, cameraInit, additionalViews, rebuild=False):
"""
Build up-to-date intrinsics and views based on already loaded + additional images.
Does not modify the graph, can be called outside the main thread.
Emits intrinsicBuilt(views, intrinsics) when done.
Args:
cameraInit (Node): CameraInit node to build the intrinsics for
additionalViews: list of additional views to add to the CameraInit viewpoints
rebuild (bool): whether to rebuild already created intrinsics
"""
views = []
intrinsics = []
# Duplicate 'cameraInit' outside the graph.
# => allows to compute intrinsics without modifying the node or the graph
# If cameraInit is None (i.e: SfM augmentation):
# * create an uninitialized node
# * wait for the result before actually creating new nodes in the graph (see onIntrinsicsAvailable)
inputs = cameraInit.toDict()["inputs"] if cameraInit else {}
cameraInitCopy = Node("CameraInit", **inputs)
if rebuild:
# if rebuilding all intrinsics, for each Viewpoint:
for vp in cameraInitCopy.viewpoints.value:
vp.intrinsicId.resetValue() # reset intrinsic assignation
vp.metadata.resetValue(
) # and metadata (to clear any previous 'SensorWidth' entries)
# reset existing intrinsics list
cameraInitCopy.intrinsics.resetValue()
try:
self.setBuildingIntrinsics(True)
# Retrieve the list of updated viewpoints and intrinsics
views, intrinsics = cameraInitCopy.nodeDesc.buildIntrinsics(
cameraInitCopy, additionalViews)
except Exception:
import traceback
logging.error("Error while building intrinsics : {}".format(
traceback.format_exc()))
# Delete the duplicate
cameraInitCopy.deleteLater()
self.setBuildingIntrinsics(False)
# always emit intrinsicsBuilt signal to inform listeners
# in other threads that computation is over
self.intrinsicsBuilt.emit(cameraInit, views, intrinsics, rebuild)
def addNewNode(self, nodeType, name=None, position=None, **kwargs):
"""
Create and add a new node to the graph.
Args:
nodeType (str): the node type name.
name (str): if specified, the desired name for this node. If not unique, will be prefixed (_N).
position (Position): (optional) the position of the node
**kwargs: keyword arguments to initialize node's attributes
Returns:
The newly created node.
"""
if name and name in self._nodes.keys():
name = self._createUniqueNodeName(name)
n = self.addNode(Node(nodeType, position=position, **kwargs), uniqueName=name)
n.updateInternals()
return n