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ObjectModel

Properties

Name Type Description Notes
objid int The object Id.
acquisid int The parent acquisition Id.
classif_id int The classification Id. [optional]
objtime str [optional]
latitude float The latitude. [optional]
longitude float The longitude. [optional]
depth_min float The min depth. [optional]
depth_max float The min depth. [optional]
objdate date [optional]
classif_qual str The classification qualification. Could be P for predicted, V for validated or D for Dubious. [optional]
sunpos str Sun position, from date, time and coords. [optional]
classif_when datetime The classification date. [optional]
classif_who int The user who manualy classify this object. [optional]
classif_auto_id int Set if the object was ever predicted, remain forever with these value. Reflect the 'last state' only if classif_qual is 'P'. [optional]
classif_auto_when datetime Set if the object was ever predicted, remain forever with these value. Reflect the 'last state' only if classif_qual is 'P'. The classification date. [optional]
classif_auto_score float Set if the object was ever predicted, remain forever with these value. Reflect the 'last state' only if classif_qual is 'P'. The classification auto score is generally between 0 and 1. This is a confidence score, in the fact that, the taxon prediction for this object is correct. [optional]
orig_id str Original object ID from initial TSV load.
object_link str Object link. [optional]
complement_info str [optional]
sample_id int Sample (i.e. parent of parent acquisition) ID.
project_id int Project (i.e. parent of sample) ID.
images List[ImageModel] Images for this object. [optional] [default to []]
free_columns object Free columns from object mapping in project. [optional]
classif_crossvalidation_id int Always NULL, kept for compat. [optional]
similarity float Always NULL, kept for compat. [optional]
random_value int Random value associated to an image

Example

from ecotaxa_py_client.models.object_model import ObjectModel

# TODO update the JSON string below
json = "{}"
# create an instance of ObjectModel from a JSON string
object_model_instance = ObjectModel.from_json(json)
# print the JSON string representation of the object
print(ObjectModel.to_json())

# convert the object into a dict
object_model_dict = object_model_instance.to_dict()
# create an instance of ObjectModel from a dict
object_model_form_dict = object_model.from_dict(object_model_dict)

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