def loadOldProject(data, labels_dict):
project = Project()
project.importLabelsFromConfiguration(labels_dict)
map_filename = data["Map File"]
#convert to relative paths in case:
dir = QDir(os.getcwd())
map_filename = dir.relativeFilePath(map_filename)
image_name = os.path.basename(map_filename)
image_name = image_name[:-4]
image = Image(id=image_name)
image.map_px_to_mm_factor = data["Map Scale"]
image.acquisition_date = "1955-11-05"
channel = Channel(filename=map_filename, type="RGB")
image.channels.append(channel)
for blob_data in data["Segmentation Data"]:
blob = Blob(None, 0, 0, 0)
blob.fromDict(blob_data)
blob.setId(int(
blob.id)) # id should be set again to update related info
image.annotations.addBlob(blob)
project.images.append(image)
return project
def __init__(self,
filename=None,
labels={},
images=[],
correspondences=None,
spatial_reference_system=None,
metadata={},
image_metadata_template={}):
self.filename = None #filename with path of the project json
self.labels = {key: Label(**value) for key, value in labels.items()}
if not 'Empty' in self.labels:
self.labels['Empty'] = Label(id='Empty',
name='Empty',
description=None,
fill=[127, 127, 127],
border=[200, 200, 200],
visible=True)
self.images = list(map(lambda img: Image(**img),
images)) #list of annotated images
# dict of tables (DataFrame) of correspondences betweeen a source and a target image
self.correspondences = {}
if correspondences is not None:
for key in correspondences.keys():
source = correspondences[key]['source']
target = correspondences[key]['target']
self.correspondences[key] = Correspondences(
self.getImageFromId(source), self.getImageFromId(target))
self.correspondences[key].fillTable(
correspondences[key]['correspondences'])
self.spatial_reference_system = spatial_reference_system #if None we assume coordinates in pixels (but Y is up or down?!)
self.metadata = metadata # project metadata => keyword -> value
self.image_metadata_template = image_metadata_template # description of metadata keywords expected in images