## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
eval = FALSE
)
## ----setup--------------------------------------------------------------------
# library(birdnetR)
## ----init_model---------------------------------------------------------------
# # The models are defined using the birdnet_model_* family of functions.
# # See ?birdnet_model_load for more details.
#
# # Initialize the TensorFlow Lite model
# birdnet_model_tflite("v2.4")
#
# # Initialize the Protobuf model
# birdnet_model_protobuf("v2.4")
#
#
## ----init_custom_model--------------------------------------------------------
# classifier_folder <- "/path/to/custom/model"
# classifier_name <- "Custom_Classifier"
#
# birdnet_model_custom("v2.4", classifier_folder = classifier_folder, classifier_name = classifier_name)
#
## ----species_in_audio---------------------------------------------------------
# library(birdnetR)
#
# # Initialize the TFLite BirdNET Model
# model <- birdnet_model_tflite("v2.4")
#
# # Path to an example audio file (replace with your own file path)
# audio_path <- system.file("extdata", "soundscape.mp3", package = "birdnetR")
#
# # Predict species in the audio file
# predictions <- predict_species_from_audio_file(model, audio_path, min_confidence = 0.3, keep_empty = FALSE)
#
# # Example output:
# # start end scientific_name common_name confidence
# # 0 3 Poecile atricapillus Black-capped Chickadee 0.8140557
# # 3 6 Poecile atricapillus Black-capped Chickadee 0.3082857
# # 9 12 Haemorhous mexicanus House Finch 0.6393781
# # 18 21 Cyanocitta cristata Blue Jay 0.4352708
# # 18 21 Clamator coromandus Chestnut-winged Cuckoo 0.3225890
# # 21 24 Cyanocitta cristata Blue Jay 0.3290859
# # ...
#
## ----top_predictions----------------------------------------------------------
# # Get the top prediction for each interval
# get_top_prediction(predictions)
#
# # Example output:
# # start end scientific_name common_name confidence
# # 0 3 Poecile atricapillus Black-capped Chickadee 0.8140557
# # 3 6 Poecile atricapillus Black-capped Chickadee 0.3082857
# # 9 12 Haemorhous mexicanus House Finch 0.6393781
# # 18 21 Cyanocitta cristata Blue Jay 0.4352708
# # 21 24 Cyanocitta cristata Blue Jay 0.3290859
#
# # Note: Fewer rows appear for the interval 18-21 as only the top prediction is retained.
#
## ----class_label_example------------------------------------------------------
# "Accipiter cooperii_Cooper's Hawk"
# "Agelaius phoeniceus_Red-winged Blackbird"
## ----label_file_paths---------------------------------------------------------
# # Retrieve the path to the full list of BirdNET classes.
# # Use this as a template for creating your custom species list, but don't modify this file directly.
# labels_path(model, language = "en_us")
# # /.../birdnet/models/v2.4/TFLite/labels/en_us.txt"
#
# # Path to the example custom species list with a reduced number of species
# custom_species_list <- system.file("extdata", "species_list.txt", package = "birdnetR")
# read_labels(custom_species_list)
#
# # [1] "Accipiter cooperii_Cooper's Hawk" "Agelaius phoeniceus_Red-winged Blackbird"
# # [3] "Anas platyrhynchos_Mallard" "Anas rubripes_American Black Duck"
# # [5] "Ardea herodias_Great Blue Heron" "Baeolophus bicolor_Tufted Titmouse"
# # [7] "Branta canadensis_Canada Goose" "Bucephala albeola_Bufflehead"
# # [9] "Bucephala clangula_Common Goldeneye" "Buteo jamaicensis_Red-tailed Hawk"
# # ...
#
## ----use_custom_species_list--------------------------------------------------
# predict_species_from_audio_file(model, audio_path, filter_species = c("Cyanocitta cristata_Blue Jay", "Junco hyemalis_Dark-eyed Junco"), min_confidence = 0.3, keep_empty = FALSE)
#
# # Example output:
# # start end scientific_name common_name confidence
# # 18 21 Cyanocitta cristata Blue Jay 0.4352708
# # 21 24 Cyanocitta cristata Blue Jay 0.3290859
# # 33 36 Junco hyemalis Dark-eyed Junco 0.4590625
# # 36 39 Junco hyemalis Dark-eyed Junco 0.3536855
# # 42 45 Junco hyemalis Dark-eyed Junco 0.7375432
#
## ----use_meta_model-----------------------------------------------------------
# # load the meta model
# meta_model <- birdnet_model_meta("v2.4")
#
# # predict species occurrence in Ithaca, NY in week 4 of the year
# predict_species_at_location_and_time(meta_model, latitude = 42.5, longitude = -76.45, week = 4)
#
# # Example output:
# # label confidence
# # Cyanocitta cristata_Blue Jay 0.92886776
# # Poecile atricapillus_Black-capped Chickadee 0.90332001
# # Sitta carolinensis_White-breasted Nuthatch 0.83232993
# # Cardinalis cardinalis_Northern Cardinal 0.82705086
# # Junco hyemalis_Dark-eyed Junco 0.82440305
# # Zenaida macroura_Mourning Dove 0.80619872
# # Corvus brachyrhynchos_American Crow 0.80580002
# # Dryobates pubescens_Downy Woodpecker 0.79495054
# # Spinus tristis_American Goldfinch 0.72782934
# # Baeolophus bicolor_Tufted Titmouse 0.63683629
#
## ----languages----------------------------------------------------------------
# # supply the version of the BirdNET model you are using
# available_languages("v2.4")
## -----------------------------------------------------------------------------
# birdnet_model_tflite("v2.4", language = "fr")
## ----labels_language----------------------------------------------------------
# labels_path_lang <- labels_path(model, language = "fr")
# read_labels(labels_path_lang)
#
# # Example output:
# # [1] "Abroscopus albogularis_Bouscarle à moustaches" "Abroscopus schisticeps_Bouscarle à face noire" "Abroscopus superciliaris_Bouscarle à sourcils blancs"
# # [4] "Aburria aburri_Pénélope aburri" "Acanthagenys rufogularis_Méliphage à bavette" "Acanthidops bairdi_Bec-en-cheville gris"
# # [7] "Acanthis cabaret_Sizerin cabaret" "Acanthis flammea_Sizerin flammé" "Acanthis hornemanni_Sizerin blanchâtre"
# # [10] "Acanthisitta chloris_Xénique grimpeur" "Acanthiza apicalis_Acanthize troglodyte" "Acanthiza chrysorrhoa_Acanthize à croupion jaune"
# # [13] "Acanthiza ewingii_Acanthize de Tasmanie" "Acanthiza inornata_Acanthize sobre" "Acanthiza lineata_Acanthize ridé"