ObjectHeaderModel.md

ObjectHeaderModel

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]

Example

from ecotaxa_py_client.models.object_header_model import ObjectHeaderModel

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

# convert the object into a dict
object_header_model_dict = object_header_model_instance.to_dict()
# create an instance of ObjectHeaderModel from a dict
object_header_model_form_dict = object_header_model.from_dict(object_header_model_dict)

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