Merge pull request #754 from bdoner/feature/add-confidencepct-variable-to-apprise-notification
Add confidencepct variable to apprise notification
This commit is contained in:
+4
-2
@@ -519,6 +519,8 @@ https://discordapp.com/api/webhooks/{WebhookID}/{WebhookToken}
|
||||
<dd>Common Name</dd>
|
||||
<dt>$confidence</dt>
|
||||
<dd>Confidence Score</dd>
|
||||
<dt>$confidencepct</dt>
|
||||
<dd>Confidence Score as a percentage (eg. 0.91 => 91)</dd>
|
||||
<dt>$listenurl</dt>
|
||||
<dd>A link to the detection</dd>
|
||||
<dt>$date</dt>
|
||||
@@ -542,9 +544,9 @@ https://discordapp.com/api/webhooks/{WebhookID}/{WebhookToken}
|
||||
</dl>
|
||||
<p>Use the variables defined above to customize your notification title and body.</p>
|
||||
<label for="apprise_notification_title">Notification Title: </label>
|
||||
<input name="apprise_notification_title" type="text" value="<?php print($config['APPRISE_NOTIFICATION_TITLE']);?>" /><br>
|
||||
<input name="apprise_notification_title" style="width: 100%" type="text" value="<?php print($config['APPRISE_NOTIFICATION_TITLE']);?>" /><br>
|
||||
<label for="apprise_notification_body">Notification Body: </label>
|
||||
<input name="apprise_notification_body" type="text" value='<?php print($config['APPRISE_NOTIFICATION_BODY']);?>' /><br>
|
||||
<input name="apprise_notification_body" style="width: 100%" type="text" value='<?php print($config['APPRISE_NOTIFICATION_BODY']);?>' /><br>
|
||||
<input type="checkbox" name="apprise_notify_new_species" <?php if($config['APPRISE_NOTIFY_NEW_SPECIES'] == 1 && filesize($home."/BirdNET-Pi/apprise.txt") != 0) { echo "checked"; };?> >
|
||||
<label for="apprise_notify_new_species">Notify each new infrequent species detection (<5 visits per week)</label><br>
|
||||
<input type="checkbox" name="apprise_notify_new_species_each_day" <?php if($config['APPRISE_NOTIFY_NEW_SPECIES_EACH_DAY'] == 1 && filesize($home."/BirdNET-Pi/apprise.txt") != 0) { echo "checked"; };?> >
|
||||
|
||||
@@ -48,7 +48,8 @@ readings = 10
|
||||
plt_top10_today = (df_plt_today['Com_Name'].value_counts()[:readings])
|
||||
df_plt_top10_today = df_plt_today[df_plt_today.Com_Name.isin(plt_top10_today.index)]
|
||||
|
||||
if df_plt_top10_today.empty: exit(0)
|
||||
if df_plt_top10_today.empty:
|
||||
exit(0)
|
||||
|
||||
# Set Palette for graphics
|
||||
pal = "Greens"
|
||||
|
||||
@@ -95,7 +95,7 @@ else:
|
||||
def date_filter(df, start_date, end_date):
|
||||
filt = (df2.index >= pd.Timestamp(start_date)) & (df2.index <= pd.Timestamp(end_date + timedelta(days=1)))
|
||||
df = df[filt]
|
||||
return(df)
|
||||
return (df)
|
||||
|
||||
|
||||
df2 = date_filter(df2, start_date, end_date)
|
||||
@@ -142,7 +142,7 @@ def time_resample(df, resample_time):
|
||||
else:
|
||||
df_resample = df.resample(resample_time)['Com_Name'].aggregate('unique').explode()
|
||||
|
||||
return(df_resample)
|
||||
return (df_resample)
|
||||
|
||||
|
||||
top_bird = df2['Com_Name'].mode()[0]
|
||||
@@ -236,10 +236,10 @@ if daily is False:
|
||||
|
||||
if resample_time != '1D':
|
||||
specie = st.selectbox(
|
||||
'Which bird would you like to explore for the dates '
|
||||
+ str(start_date) + ' to ' + str(end_date) + '?',
|
||||
species,
|
||||
index=0)
|
||||
'Which bird would you like to explore for the dates '
|
||||
+ str(start_date) + ' to ' + str(end_date) + '?',
|
||||
species,
|
||||
index=0)
|
||||
|
||||
# filt = df2['Com_Name'] == specie
|
||||
if specie == 'All':
|
||||
@@ -256,7 +256,7 @@ if daily is False:
|
||||
# '{:.2f}%'.format(max(df2[df2['Com_Name'] == specie]['Confidence']) * 100)) +
|
||||
# ' ' + ' Median:' + str(
|
||||
# '{:.2f}%'.format(np.median(df2[df2['Com_Name'] == specie]['Confidence']) * 100))
|
||||
)
|
||||
)
|
||||
)
|
||||
fig.layout.annotations[1].update(x=0.7, y=0.25, font_size=15)
|
||||
|
||||
@@ -316,7 +316,7 @@ if daily is False:
|
||||
fig = make_subplots(
|
||||
rows=3, cols=1,
|
||||
specs=[[{"type": "polar", "rowspan": 2}], [{"rowspan": 1}], [{"type": "xy", "rowspan": 1}]]
|
||||
)
|
||||
)
|
||||
# Set 360 degrees, 24 hours for polar plot
|
||||
theta = np.linspace(0.0, 360, 24, endpoint=False)
|
||||
|
||||
|
||||
+18
-9
@@ -57,10 +57,11 @@ with open(userDir + '/BirdNET-Pi/scripts/thisrun.txt', 'r') as f:
|
||||
try:
|
||||
model = str(str(str([i for i in this_run if i.startswith('MODEL')]).split('=')[1]).split('\\')[0])
|
||||
sf_thresh = str(str(str([i for i in this_run if i.startswith('SF_THRESH')]).split('=')[1]).split('\\')[0])
|
||||
except Exception as e:
|
||||
except Exception:
|
||||
model = "BirdNET_6K_GLOBAL_MODEL"
|
||||
sf_thresh = 0.03
|
||||
|
||||
|
||||
def loadModel():
|
||||
|
||||
global INPUT_LAYER_INDEX
|
||||
@@ -97,6 +98,7 @@ def loadModel():
|
||||
|
||||
return myinterpreter
|
||||
|
||||
|
||||
def loadMetaModel():
|
||||
|
||||
global M_INTERPRETER
|
||||
@@ -117,15 +119,16 @@ def loadMetaModel():
|
||||
|
||||
print("loaded META model")
|
||||
|
||||
|
||||
def predictFilter(lat, lon, week):
|
||||
|
||||
global M_INTERPRETER
|
||||
|
||||
# Does interpreter exist?
|
||||
try:
|
||||
if M_INTERPRETER == None:
|
||||
if M_INTERPRETER is None:
|
||||
loadMetaModel()
|
||||
except Exception as e:
|
||||
except Exception:
|
||||
loadMetaModel()
|
||||
|
||||
# Prepare mdata as sample
|
||||
@@ -137,6 +140,7 @@ def predictFilter(lat, lon, week):
|
||||
|
||||
return M_INTERPRETER.get_tensor(M_OUTPUT_LAYER_INDEX)[0]
|
||||
|
||||
|
||||
def explore(lat, lon, week):
|
||||
|
||||
# Make filter prediction
|
||||
@@ -153,15 +157,17 @@ def explore(lat, lon, week):
|
||||
|
||||
return l_filter
|
||||
|
||||
|
||||
def predictSpeciesList(lat, lon, week):
|
||||
|
||||
l_filter = explore(lat, lon, week)
|
||||
for s in l_filter:
|
||||
if s[0] >= float(sf_thresh):
|
||||
#if there's a custom user-made include list, we only want to use the species in that
|
||||
if(len(INCLUDE_LIST) == 0):
|
||||
# if there's a custom user-made include list, we only want to use the species in that
|
||||
if (len(INCLUDE_LIST) == 0):
|
||||
PREDICTED_SPECIES_LIST.append(s[1])
|
||||
|
||||
|
||||
def loadCustomSpeciesList(path):
|
||||
|
||||
slist = []
|
||||
@@ -274,8 +280,7 @@ def analyzeAudioData(chunks, lat, lon, week, sensitivity, overlap,):
|
||||
|
||||
if model == "BirdNET_GLOBAL_3K_V2.3_Model_FP16":
|
||||
if len(PREDICTED_SPECIES_LIST) == 0 or len(INCLUDE_LIST) != 0:
|
||||
predictSpeciesList(lat,lon,week)
|
||||
|
||||
predictSpeciesList(lat, lon, week)
|
||||
|
||||
# Convert and prepare metadata
|
||||
mdata = convertMetadata(np.array([lat, lon, week]))
|
||||
@@ -322,7 +327,9 @@ def writeResultsToFile(detections, min_conf, path):
|
||||
rfile.write('Start (s);End (s);Scientific name;Common name;Confidence\n')
|
||||
for d in detections:
|
||||
for entry in detections[d]:
|
||||
if entry[1] >= min_conf and ((entry[0] in INCLUDE_LIST or len(INCLUDE_LIST) == 0) and (entry[0] not in EXCLUDE_LIST or len(EXCLUDE_LIST) == 0) and (entry[0] in PREDICTED_SPECIES_LIST or len(PREDICTED_SPECIES_LIST) == 0) ):
|
||||
if entry[1] >= min_conf and ((entry[0] in INCLUDE_LIST or len(INCLUDE_LIST) == 0)
|
||||
and (entry[0] not in EXCLUDE_LIST or len(EXCLUDE_LIST) == 0)
|
||||
and (entry[0] in PREDICTED_SPECIES_LIST or len(PREDICTED_SPECIES_LIST) == 0)):
|
||||
rfile.write(d + ';' + entry[0].replace('_', ';').split("/")[0] + ';' + str(entry[1]) + '\n')
|
||||
rcnt += 1
|
||||
print('DONE! WROTE', rcnt, 'RESULTS.')
|
||||
@@ -468,7 +475,8 @@ def handle_client(conn, addr):
|
||||
species_apprised_this_run = []
|
||||
for entry in detections[d]:
|
||||
if entry[1] >= min_conf and ((entry[0] in INCLUDE_LIST or len(INCLUDE_LIST) == 0)
|
||||
and (entry[0] not in EXCLUDE_LIST or len(EXCLUDE_LIST) == 0) and (entry[0] in PREDICTED_SPECIES_LIST or len(PREDICTED_SPECIES_LIST) == 0) ):
|
||||
and (entry[0] not in EXCLUDE_LIST or len(EXCLUDE_LIST) == 0)
|
||||
and (entry[0] in PREDICTED_SPECIES_LIST or len(PREDICTED_SPECIES_LIST) == 0)):
|
||||
# Write to text file.
|
||||
rfile.write(str(current_date) + ';' + str(current_time) + ';' + entry[0].replace('_', ';').split("/")[0] + ';'
|
||||
+ str(entry[1]) + ";" + str(args.lat) + ';' + str(args.lon) + ';' + str(min_conf) + ';' + str(week) + ';'
|
||||
@@ -511,6 +519,7 @@ def handle_client(conn, addr):
|
||||
settings_dict = config_to_settings(userDir + '/BirdNET-Pi/scripts/thisrun.txt')
|
||||
sendAppriseNotifications(species,
|
||||
str(score),
|
||||
str(round(score * 100)),
|
||||
File_Name,
|
||||
Date,
|
||||
Time,
|
||||
|
||||
+16
-31
@@ -1,18 +1,5 @@
|
||||
from pathlib import Path
|
||||
from tzlocal import get_localzone
|
||||
import datetime
|
||||
import sqlite3
|
||||
import requests
|
||||
import json
|
||||
import time
|
||||
import math
|
||||
import numpy as np
|
||||
import librosa
|
||||
import operator
|
||||
import socket
|
||||
import threading
|
||||
import os
|
||||
import sys
|
||||
import argparse
|
||||
import datetime
|
||||
|
||||
@@ -22,7 +9,6 @@ except BaseException:
|
||||
from tensorflow import lite as tflite
|
||||
|
||||
|
||||
|
||||
def loadMetaModel():
|
||||
|
||||
global M_INTERPRETER
|
||||
@@ -51,15 +37,16 @@ def loadMetaModel():
|
||||
|
||||
print("loaded META model")
|
||||
|
||||
|
||||
def predictFilter(lat, lon, week):
|
||||
|
||||
global M_INTERPRETER
|
||||
|
||||
# Does interpreter exist?
|
||||
try:
|
||||
if M_INTERPRETER == None:
|
||||
if M_INTERPRETER is None:
|
||||
loadMetaModel()
|
||||
except Exception as e:
|
||||
except Exception:
|
||||
loadMetaModel()
|
||||
|
||||
# Prepare mdata as sample
|
||||
@@ -71,6 +58,7 @@ def predictFilter(lat, lon, week):
|
||||
|
||||
return M_INTERPRETER.get_tensor(M_OUTPUT_LAYER_INDEX)[0]
|
||||
|
||||
|
||||
def explore(lat, lon, week, threshold):
|
||||
|
||||
# Make filter prediction
|
||||
@@ -87,6 +75,7 @@ def explore(lat, lon, week, threshold):
|
||||
|
||||
return l_filter
|
||||
|
||||
|
||||
def getSpeciesList(lat, lon, week, threshold=0.05, sort=False):
|
||||
|
||||
print('Getting species list for {}/{}, Week {}...'.format(lat, lon, week), end='', flush=True)
|
||||
@@ -98,7 +87,7 @@ def getSpeciesList(lat, lon, week, threshold=0.05, sort=False):
|
||||
slist = []
|
||||
for p in pred:
|
||||
if p[0] >= threshold:
|
||||
slist.append([p[1],p[0]])
|
||||
slist.append([p[1], p[0]])
|
||||
|
||||
return slist
|
||||
|
||||
@@ -112,17 +101,14 @@ with open(userDir + '/BirdNET-Pi/scripts/thisrun.txt', 'r') as f:
|
||||
lon = str(str(str([i for i in this_run if i.startswith('LONGITUDE')]).split('=')[1]).split('\\')[0])
|
||||
|
||||
weekofyear = datetime.datetime.today().isocalendar()[1]
|
||||
if __name__ == '__main__':
|
||||
if __name__ == '__main__':
|
||||
|
||||
# Parse arguments
|
||||
parser = argparse.ArgumentParser(description='Get list of species for a given location with BirdNET. Sorted by occurrence frequency.')
|
||||
#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\'.')
|
||||
#parser.add_argument('--lat', type=float, default=##, help='Recording location latitude. Set -1 to ignore.')
|
||||
#parser.add_argument('--lon', type=float, default=##, help='Recording location longitude. Set -1 to ignore.')
|
||||
#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.')
|
||||
parser = argparse.ArgumentParser(
|
||||
description='Get list of species for a given location with BirdNET. Sorted by occurrence frequency.'
|
||||
)
|
||||
parser.add_argument('--threshold', type=float, default=0.05, help='Occurrence frequency threshold. Defaults to 0.05.')
|
||||
#parser.add_argument('--sortby', default='freq', help='Sort species by occurrence frequency or alphabetically. Values in [\'freq\', \'alpha\']. Defaults to \'freq\'.')
|
||||
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
LOCATION_FILTER_THRESHOLD = args.threshold
|
||||
@@ -130,10 +116,9 @@ if __name__ == '__main__':
|
||||
# Get species list
|
||||
species_list = getSpeciesList(lat, lon, weekofyear, LOCATION_FILTER_THRESHOLD, False)
|
||||
for x in range(len(species_list)):
|
||||
print(species_list[x][0] + " - "+ str(species_list[x][1]))
|
||||
|
||||
print("\nThe above species list describes all the species that the model will attempt to detect. If you don't see a species you want detected on this list, decrease your threshold.")
|
||||
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)")
|
||||
|
||||
|
||||
print(species_list[x][0] + " - " + str(species_list[x][1]))
|
||||
|
||||
print("\nThe above species list describes all the species that the model will attempt to detect. \
|
||||
If you don't see a species you want detected on this list, decrease your threshold.")
|
||||
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)")
|
||||
|
||||
@@ -24,6 +24,7 @@ config = apprise.AppriseConfig()
|
||||
config.add(APPRISE_CONFIG)
|
||||
apobj.add(config)
|
||||
|
||||
|
||||
def notify(body, title, attached=""):
|
||||
if attached != "":
|
||||
apobj.notify(
|
||||
@@ -38,7 +39,9 @@ def notify(body, title, attached=""):
|
||||
)
|
||||
|
||||
|
||||
def sendAppriseNotifications(species, confidence, path, date, time, week, latitude, longitude, cutoff, sens, overlap, settings_dict, db_path=DB_PATH):
|
||||
def sendAppriseNotifications(species, confidence, confidencepct, path,
|
||||
date, time, week, latitude, longitude, cutoff,
|
||||
sens, overlap, settings_dict, db_path=DB_PATH):
|
||||
# print(sendAppriseNotifications)
|
||||
# print(settings_dict)
|
||||
if os.path.exists(APPRISE_CONFIG) and os.path.getsize(APPRISE_CONFIG) > 0:
|
||||
@@ -67,7 +70,7 @@ def sendAppriseNotifications(species, confidence, path, date, time, week, latitu
|
||||
print("APPRISE NOTIFICATION EXCEPTION: "+str(e))
|
||||
return
|
||||
|
||||
#TODO: this all needs to be changed, we changed the caddy default to allow direct IP access, so birdnetpi.local shouldn't be relied on anymore
|
||||
# TODO: this all needs to be changed, we changed the caddy default to allow direct IP access, so birdnetpi.local shouldn't be relied on anymore
|
||||
try:
|
||||
websiteurl = settings_dict.get('BIRDNETPI_URL')
|
||||
if len(websiteurl) == 0:
|
||||
@@ -79,27 +82,28 @@ def sendAppriseNotifications(species, confidence, path, date, time, week, latitu
|
||||
image_url = ""
|
||||
|
||||
if len(settings_dict.get('FLICKR_API_KEY')) > 0 and "$flickrimage" in body:
|
||||
if not comName in flickr_images:
|
||||
if comName not in flickr_images:
|
||||
try:
|
||||
# TODO: Make this work with non-english comnames. Implement the "// convert sci name to English name" logic from overview.php here
|
||||
headers = {'User-Agent': 'Python_Flickr/1.0'}
|
||||
url = 'https://www.flickr.com/services/rest/?method=flickr.photos.search&api_key='+str(settings_dict.get('FLICKR_API_KEY'))+'&text='+str(comName)+' bird&sort=relevance&per_page=5&media=photos&format=json&license=2%2C3%2C4%2C5%2C6%2C9&nojsoncallback=1'
|
||||
resp = requests.get(url=url, headers=headers)
|
||||
|
||||
resp.encoding = "utf-8"
|
||||
data = resp.json()["photos"]["photo"][0]
|
||||
|
||||
image_url = 'https://farm'+str(data["farm"])+'.static.flickr.com/'+str(data["server"])+'/'+str(data["id"])+'_'+str(data["secret"])+'_n.jpg'
|
||||
flickr_images[comName] = image_url
|
||||
except Exception as e:
|
||||
print("FLICKR API ERROR: "+str(e))
|
||||
print("FLICKR API ERROR: "+str(e))
|
||||
image_url = ""
|
||||
else:
|
||||
image_url = flickr_images[comName]
|
||||
|
||||
|
||||
if settings_dict.get('APPRISE_NOTIFY_EACH_DETECTION') == "1":
|
||||
notify_body = body.replace("$sciname", sciName)\
|
||||
.replace("$comname", comName)\
|
||||
.replace("$confidencepct", confidencepct)\
|
||||
.replace("$confidence", confidence)\
|
||||
.replace("$listenurl", listenurl)\
|
||||
.replace("$date", date)\
|
||||
@@ -113,6 +117,7 @@ def sendAppriseNotifications(species, confidence, path, date, time, week, latitu
|
||||
.replace("$overlap", overlap)
|
||||
notify_title = title.replace("$sciname", sciName)\
|
||||
.replace("$comname", comName)\
|
||||
.replace("$confidencepct", confidencepct)\
|
||||
.replace("$confidence", confidence)\
|
||||
.replace("$listenurl", listenurl)\
|
||||
.replace("$date", date)\
|
||||
@@ -143,6 +148,7 @@ def sendAppriseNotifications(species, confidence, path, date, time, week, latitu
|
||||
print("send the notification")
|
||||
notify_body = body.replace("$sciname", sciName)\
|
||||
.replace("$comname", comName)\
|
||||
.replace("$confidencepct", confidencepct)\
|
||||
.replace("$confidence", confidence)\
|
||||
.replace("$listenurl", listenurl)\
|
||||
.replace("$date", date)\
|
||||
@@ -157,6 +163,7 @@ def sendAppriseNotifications(species, confidence, path, date, time, week, latitu
|
||||
+ " (first time today)"
|
||||
notify_title = title.replace("$sciname", sciName)\
|
||||
.replace("$comname", comName)\
|
||||
.replace("$confidencepct", confidencepct)\
|
||||
.replace("$confidence", confidence)\
|
||||
.replace("$listenurl", listenurl)\
|
||||
.replace("$date", date)\
|
||||
@@ -191,6 +198,7 @@ def sendAppriseNotifications(species, confidence, path, date, time, week, latitu
|
||||
if numberDetections > 0 and numberDetections <= 5:
|
||||
notify_body = body.replace("$sciname", sciName)\
|
||||
.replace("$comname", comName)\
|
||||
.replace("$confidencepct", confidencepct)\
|
||||
.replace("$confidence", confidence)\
|
||||
.replace("$listenurl", listenurl)\
|
||||
.replace("$date", date)\
|
||||
@@ -205,6 +213,7 @@ def sendAppriseNotifications(species, confidence, path, date, time, week, latitu
|
||||
+ " (only seen " + str(int(numberDetections)) + " times in last 7d)"
|
||||
notify_title = title.replace("$sciname", sciName)\
|
||||
.replace("$comname", comName)\
|
||||
.replace("$confidencepct", confidencepct)\
|
||||
.replace("$confidence", confidence)\
|
||||
.replace("$listenurl", listenurl)\
|
||||
.replace("$date", date)\
|
||||
|
||||
@@ -6,7 +6,7 @@ def config_to_settings(path):
|
||||
this_run = f.readlines()
|
||||
for i in this_run:
|
||||
key = i.split("=")[0]
|
||||
value = i.split("=")[1][:-1]
|
||||
value = "=".join(i.split("=")[1:])[:-1]
|
||||
# Trim for strings, not ideal
|
||||
if value.startswith('"') and value.endswith('"'):
|
||||
value = value[1:-1]
|
||||
|
||||
@@ -50,6 +50,7 @@ def test_notifications(mocker):
|
||||
"APPRISE_NOTIFY_NEW_SPECIES_EACH_DAY": "0"
|
||||
}
|
||||
sendAppriseNotifications("Myiarchus crinitus_Great Crested Flycatcher",
|
||||
"0.91",
|
||||
"91",
|
||||
"filename",
|
||||
"1666-06-06",
|
||||
@@ -64,12 +65,13 @@ def test_notifications(mocker):
|
||||
"test.db")
|
||||
|
||||
# No active apprise notifcations configured. Confirm no notifications.
|
||||
assert(notify_call.call_count == 0) # No notification should be sent.
|
||||
assert (notify_call.call_count == 0) # No notification should be sent.
|
||||
|
||||
# Add daily notification.
|
||||
notify_call.reset_mock()
|
||||
settings_dict["APPRISE_NOTIFY_NEW_SPECIES_EACH_DAY"] = "1"
|
||||
sendAppriseNotifications("Myiarchus crinitus_Great Crested Flycatcher",
|
||||
"0.91",
|
||||
"91",
|
||||
"filename",
|
||||
"1666-06-06",
|
||||
@@ -83,8 +85,8 @@ def test_notifications(mocker):
|
||||
settings_dict,
|
||||
"test.db")
|
||||
|
||||
assert(notify_call.call_count == 1)
|
||||
assert(
|
||||
assert (notify_call.call_count == 1)
|
||||
assert (
|
||||
notify_call.call_args_list[0][0][0] == "A Great Crested Flycatcher (Myiarchus crinitus) was just detected with a confidence of 91 (first time today)"
|
||||
)
|
||||
|
||||
@@ -92,6 +94,7 @@ def test_notifications(mocker):
|
||||
notify_call.reset_mock()
|
||||
settings_dict["APPRISE_NOTIFY_NEW_SPECIES"] = "1"
|
||||
sendAppriseNotifications("Myiarchus crinitus_Great Crested Flycatcher",
|
||||
"0.91",
|
||||
"91",
|
||||
"filename",
|
||||
"1666-06-06",
|
||||
@@ -105,18 +108,20 @@ def test_notifications(mocker):
|
||||
settings_dict,
|
||||
"test.db")
|
||||
|
||||
assert(notify_call.call_count == 2)
|
||||
assert(
|
||||
assert (notify_call.call_count == 2)
|
||||
assert (
|
||||
notify_call.call_args_list[0][0][0] == "A Great Crested Flycatcher (Myiarchus crinitus) was just detected with a confidence of 91 (first time today)"
|
||||
)
|
||||
assert(
|
||||
notify_call.call_args_list[1][0][0] == "A Great Crested Flycatcher (Myiarchus crinitus) was just detected with a confidence of 91 (only seen 1 times in last 7d)"
|
||||
assert (
|
||||
notify_call.call_args_list[1][0][0] == "A Great Crested Flycatcher (Myiarchus crinitus) was just detected with a confidence \
|
||||
of 91 (only seen 1 times in last 7d)"
|
||||
)
|
||||
|
||||
# Add each species notification.
|
||||
notify_call.reset_mock()
|
||||
settings_dict["APPRISE_NOTIFY_EACH_DETECTION"] = "1"
|
||||
sendAppriseNotifications("Myiarchus crinitus_Great Crested Flycatcher",
|
||||
"0.91",
|
||||
"91",
|
||||
"filename",
|
||||
"1666-06-06",
|
||||
@@ -130,4 +135,4 @@ def test_notifications(mocker):
|
||||
settings_dict,
|
||||
"test.db")
|
||||
|
||||
assert(notify_call.call_count == 3)
|
||||
assert (notify_call.call_count == 3)
|
||||
|
||||
@@ -39,6 +39,6 @@ IDFILE=/home/pi/BirdNET-Pi/IdentifiedSoFar.txt"""
|
||||
f.write(text)
|
||||
|
||||
settings = config_to_settings(filename.name)
|
||||
assert(settings["APPRISE_NOTIFICATION_TITLE"] == "Bird!")
|
||||
assert(settings["FULL_DISK"] == "purge")
|
||||
assert(settings["OVERLAP"] == "0.0") # Yes, it's a string at this point.
|
||||
assert (settings["APPRISE_NOTIFICATION_TITLE"] == "Bird!")
|
||||
assert (settings["FULL_DISK"] == "purge")
|
||||
assert (settings["OVERLAP"] == "0.0") # Yes, it's a string at this point.
|
||||
|
||||
Reference in New Issue
Block a user