SF_THRESH config
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ehpersonal38
@@ -11,6 +11,7 @@ SITE_NAME=""
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#______________________used for detecting bird audio.__________________________#
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MODEL=BirdNET_6K_GLOBAL_MODEL
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SF_THRESH=0.5
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#--------------------- Required: Latitude, and Longitude ----------------------#
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@@ -35,6 +35,7 @@ if(isset($_GET["latitude"])){
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$language = $_GET["language"];
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$timezone = $_GET["timezone"];
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$model = $_GET["model"];
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$sf_thresh = $_GET["sf_thresh"];
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if(isset($_GET['apprise_notify_each_detection'])) {
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$apprise_notify_each_detection = 1;
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@@ -135,6 +136,7 @@ if(isset($_GET["latitude"])){
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$contents = preg_replace("/FLICKR_FILTER_EMAIL=.*/", "FLICKR_FILTER_EMAIL=$flickr_filter_email", $contents);
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$contents = preg_replace("/APPRISE_MINIMUM_SECONDS_BETWEEN_NOTIFICATIONS_PER_SPECIES=.*/", "APPRISE_MINIMUM_SECONDS_BETWEEN_NOTIFICATIONS_PER_SPECIES=$minimum_time_limit", $contents);
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$contents = preg_replace("/MODEL=.*/", "MODEL=$model", $contents);
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$contents = preg_replace("/SF_THRESH=.*/", "SF_THRESH=$sf_thresh", $contents);
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$contents2 = file_get_contents("./scripts/thisrun.txt");
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$contents2 = preg_replace("/SITE_NAME=.*/", "SITE_NAME=\"$site_name\"", $contents2);
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@@ -152,6 +154,8 @@ if(isset($_GET["latitude"])){
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$contents2 = preg_replace("/FLICKR_FILTER_EMAIL=.*/", "FLICKR_FILTER_EMAIL=$flickr_filter_email", $contents2);
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$contents2 = preg_replace("/APPRISE_MINIMUM_SECONDS_BETWEEN_NOTIFICATIONS_PER_SPECIES=.*/", "APPRISE_MINIMUM_SECONDS_BETWEEN_NOTIFICATIONS_PER_SPECIES=$minimum_time_limit", $contents2);
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$contents2 = preg_replace("/MODEL=.*/", "MODEL=$model", $contents2);
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$contents2 = preg_replace("/SF_THRESH=.*/", "SF_THRESH=$sf_thresh", $contents2);
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if($site_name != $config["SITE_NAME"]) {
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@@ -342,6 +346,10 @@ function sendTestNotification(e) {
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?>
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</select>
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<label for="latitude">Species occurance frequency threshold: </label>
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<p>This value is used by the model to constrain the list of possible species that it will try to detect, given the minimum occurence frequency. A 0.05 threshold means that the species is seen on average at least 5% of the time, from historically collected data for your lat/lon.<br>If you'd like to tinker with this value and see the species list output, you can run the following command:<pre class="bash">~/BirdNET-Pi/birdnet/bin/python3 species.py --threshold 0.7</pre></p>
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<input name="latitude" type="number" max="90" min="-90" step="0.0001" value="<?php print($config['LATITUDE']);?>" required/><br>
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<dl>
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<dt>BirdNET_6K_GLOBAL_MODEL (2020)</dt><br>
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<dd id="ddnewline">This model comes from BirdNET-Lite, with bird sound recognition for more than 6,000 species worldwide. This is the default option and will generally work very well for most use cases.</dd>
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@@ -32,6 +32,7 @@ LONGITUDE=$(curl -s4 ifconfig.co/json | jq .longitude)
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#______________________used for detecting bird audio.__________________________#
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MODEL=BirdNET_6K_GLOBAL_MODEL
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SF_THRESH=0.5
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#--------------------- BirdWeather Station Information -----------------------#
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#_____________The variable below can be set to have your BirdNET-Pi____________#
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@@ -0,0 +1,139 @@
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from pathlib import Path
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from tzlocal import get_localzone
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import datetime
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import sqlite3
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import requests
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import json
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import time
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import math
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import numpy as np
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import librosa
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import operator
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import socket
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import threading
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import os
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import sys
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import argparse
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import datetime
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try:
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import tflite_runtime.interpreter as tflite
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except BaseException:
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from tensorflow import lite as tflite
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def loadMetaModel():
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global M_INTERPRETER
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global M_INPUT_LAYER_INDEX
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global M_OUTPUT_LAYER_INDEX
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global CLASSES
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# Load TFLite model and allocate tensors.
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M_INTERPRETER = tflite.Interpreter(model_path=userDir + '/BirdNET-Pi/model/BirdNET_GLOBAL_3K_V2.2_MData_Model_FP16.tflite')
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M_INTERPRETER.allocate_tensors()
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# Get input and output tensors.
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input_details = M_INTERPRETER.get_input_details()
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output_details = M_INTERPRETER.get_output_details()
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# Get input tensor index
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M_INPUT_LAYER_INDEX = input_details[0]['index']
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M_OUTPUT_LAYER_INDEX = output_details[0]['index']
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# Load labels
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CLASSES = []
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labelspath = userDir + '/BirdNET-Pi/model/labels.txt'
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with open(labelspath, 'r') as lfile:
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for line in lfile.readlines():
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CLASSES.append(line.replace('\n', ''))
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print("loaded META model")
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def predictFilter(lat, lon, week):
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global M_INTERPRETER
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# Does interpreter exist?
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try:
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if M_INTERPRETER == None:
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loadMetaModel()
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except Exception as e:
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loadMetaModel()
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# Prepare mdata as sample
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sample = np.expand_dims(np.array([lat, lon, week], dtype='float32'), 0)
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# Run inference
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M_INTERPRETER.set_tensor(M_INPUT_LAYER_INDEX, sample)
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M_INTERPRETER.invoke()
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return M_INTERPRETER.get_tensor(M_OUTPUT_LAYER_INDEX)[0]
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def explore(lat, lon, week):
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# Make filter prediction
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l_filter = predictFilter(lat, lon, week)
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# Apply threshold
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l_filter = np.where(l_filter >= 0.03, l_filter, 0)
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# Zip with labels
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l_filter = list(zip(l_filter, CLASSES))
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# Sort by filter value
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l_filter = sorted(l_filter, key=lambda x: x[0], reverse=True)
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return l_filter
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def getSpeciesList(lat, lon, week, threshold=0.05, sort=False):
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print('Getting species list for {}/{}, Week {}...'.format(lat, lon, week), end='', flush=True)
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# Extract species from model
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pred = explore(lat, lon, week)
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# Make species list
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slist = []
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for p in pred:
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if p[0] >= threshold:
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slist.append([p[1],p[0]])
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return slist
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userDir = os.path.expanduser('~')
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DB_PATH = userDir + '/BirdNET-Pi/scripts/birds.db'
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with open(userDir + '/BirdNET-Pi/scripts/thisrun.txt', 'r') as f:
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this_run = f.readlines()
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lat = str(str(str([i for i in this_run if i.startswith('LATITUDE')]).split('=')[1]).split('\\')[0])
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lon = str(str(str([i for i in this_run if i.startswith('LONGITUDE')]).split('=')[1]).split('\\')[0])
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weekofyear = datetime.datetime.today().isocalendar()[1]
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if __name__ == '__main__':
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# Parse arguments
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parser = argparse.ArgumentParser(description='Get list of species for a given location with BirdNET. Sorted by occurrence frequency.')
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#parser.add_argument('--o', default='/home/pi/BirdNET-Pi/include_species_list.txt', help='Path to output file or folder. If this is a folder, file will be named \'species_list.txt\'.')
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#parser.add_argument('--lat', type=float, default=##, help='Recording location latitude. Set -1 to ignore.')
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#parser.add_argument('--lon', type=float, default=##, help='Recording location longitude. Set -1 to ignore.')
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#parser.add_argument('--week', type=int, default=dayofweek, help='Week of the year when the recording was made. Values in [1, 48] (4 weeks per month). Set -1 for year-round species list.')
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parser.add_argument('--threshold', type=float, default=0.05, help='Occurrence frequency threshold. Defaults to 0.05.')
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#parser.add_argument('--sortby', default='freq', help='Sort species by occurrence frequency or alphabetically. Values in [\'freq\', \'alpha\']. Defaults to \'freq\'.')
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args = parser.parse_args()
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LOCATION_FILTER_THRESHOLD = args.threshold
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# Get species list
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species_list = getSpeciesList(lat, lon, weekofyear, LOCATION_FILTER_THRESHOLD, False)
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for x in range(len(species_list)):
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print(species_list[x][0] + " - "+ str(species_list[x][1]))
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print("\nThe above species list describes all of the species that have been historically observed at the specified lat/long ("+lat+", "+lon+") for this week of the year. The frequency threshold is the percentage of submitted eBird checklists that the species appeared on, meaning a higher threshold means that the species is more common.")
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print("\nNOTE: no actual changes to your BirdNET-Pi species list were made by running this command. To set your desired frequency threshold, do it through the BirdNET-Pi web interface (Tools -> Settings -> Model)")
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@@ -147,6 +147,9 @@ fi
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if ! grep MODEL /etc/birdnet/birdnet.conf &>/dev/null;then
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sudo -u$USER echo "MODEL=BirdNET_6K_GLOBAL_MODEL" >> /etc/birdnet/birdnet.conf
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fi
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if ! grep SF_THRESH /etc/birdnet/birdnet.conf &>/dev/null;then
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sudo -u$USER echo "SF_THRESH=0.5" >> /etc/birdnet/birdnet.conf
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fi
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sudo systemctl daemon-reload
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restart_services.sh
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