birdnet.geo.inference package

Submodules

birdnet.geo.inference.configs module

class birdnet.geo.inference.configs.InferenceConfig(model_conf, processing_conf)

Bases: object

model_conf: ModelConfig
processing_conf: ProcessingConfig
class birdnet.geo.inference.configs.ModelConfig(species_list, path, version, is_custom, backend_type, backend_kwargs)

Bases: object

Attributes:
n_species
backend_kwargs: dict[str, Any]
backend_type: type[VersionedBackendProtocol]
is_custom: bool
property n_species: int
path: Path
species_list: OrderedSet[str]
version: Literal['2.4', '3.0']
class birdnet.geo.inference.configs.PredictionConfig(min_confidence)

Bases: object

Methods

validate_min_confidence
min_confidence: float
classmethod validate_min_confidence(min_confidence)
Return type:

float

class birdnet.geo.inference.configs.ProcessingConfig(half_precision, device)

Bases: object

Methods

validate_device

validate_half_precision
device: str
half_precision: bool
classmethod validate_device(device)
Return type:

str

classmethod validate_half_precision(half_precision)
Return type:

bool

class birdnet.geo.inference.configs.RunConfig(latitude, longitude, week, year_round_aggregation)

Bases: object

Methods

validate_latitude

validate_longitude

validate_week

validate_year_round_aggregation
latitude: float
longitude: float
classmethod validate_latitude(latitude)
Return type:

float

classmethod validate_longitude(longitude)
Return type:

float

classmethod validate_week(week)
Return type:

int | None

classmethod validate_year_round_aggregation(year_round_aggregation)
Return type:

Literal['max', 'average']

week: int | None
year_round_aggregation: Literal['max', 'average']

birdnet.geo.inference.prediction_result module

class birdnet.geo.inference.prediction_result.GeoPredictionResult(model_path, model_version, model_precision, latitude, longitude, week, species_masked, species_ids, species_probs, species_list)

Bases: ResultBase

Attributes:
latitude
longitude
memory_size_MiB
model_path
model_precision
model_version
n_species
species_ids
species_list
species_masked
species_probs
week

Methods

load

save

to_arrow_table

to_csv

to_dataframe

to_set

to_structured_array

to_txt
property latitude: int
property longitude: int
property memory_size_MiB: float
property n_species: int
property species_ids: ndarray
property species_list: ndarray
property species_masked: ndarray
property species_probs: ndarray
to_arrow_table(sort_by='species')
Return type:

Table

to_csv(csv_out_path, sort_by='species', encoding='utf8')
Return type:

None

to_dataframe(sort_by='species')
Return type:

DataFrame

to_set()
Return type:

set[str]

to_structured_array(sort_by='species')
Return type:

ndarray

to_txt(txt_out_path, sort_by='species', encoding='utf8')
Return type:

None

property week: int

birdnet.geo.inference.session module

class birdnet.geo.inference.session.GeoPredictionSession(species_list, model_path, model_is_custom, model_version, model_backend_type, model_backend_custom_kwargs, *, min_confidence, half_precision, device)

Bases: GeoSessionBase

Methods

run
run(latitude, longitude, /, *, week=None, year_round_aggregation='max')
Return type:

GeoPredictionResult

class birdnet.geo.inference.session.GeoSessionBase(conf, specific_config)

Bases: SessionBase, ABC

Methods

run

Module contents