## ----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"