Revert "Adding Flake8 Github Action for Python Linting "

.flake8

@@ -1,3 +0,0 @@
-[flake8]
-max-line-length = 128
-

.github/workflows/ci.yml

@@ -1,23 +0,0 @@
-name: CI Jobs
-
-on: pull_request
-
-jobs:
-  python-lint:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout
-        uses: actions/checkout@v3
-
-      - name: Setup Python
-        uses: actions/setup-python@v3
-        with:
-          python-version: '3.9.x'
-          cache: 'pip'
-          architecture: 'x64'
-
-      - name: Install flake8
-        run: pip install flake8
-
-      - name: Run Flake8 Lint
-        uses: py-actions/flake8@v2

scripts/analyze.py

@@ -1,16 +1,3 @@
-#!/usr/bin/env python3
-
-"""
-# Example calls
-python3 analyze.py --i 'example/XC558716 - Soundscape.mp3' \
-    --lat 35.4244 --lon -120.7463 --week 18
-
-python3 analyze.py --i 'example/XC563936 - Soundscape.mp3' \
-    --lat 47.6766 --lon -122.294 --week 11 \
-    --overlap 1.5 --min_conf 0.25 --sensitivity 1.25 \
-    --custom_list 'example/custom_species_list.txt'
-"""
-
 import argparse
 import socket
 
@@ -24,7 +11,6 @@ ADDR = (SERVER, PORT)
 client = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
 client.connect(ADDR)
 
-
 def send(msg):
     message = msg.encode(FORMAT)
     msg_length = len(message)
@@ -34,7 +20,6 @@ def send(msg):
     client.send(message)
     print(client.recv(2048).decode(FORMAT))
 
-
 def main():
 
     global INCLUDE_LIST
@@ -42,62 +27,17 @@ def main():
 
     # Parse passed arguments
     parser = argparse.ArgumentParser()
-    parser.add_argument(
+    parser.add_argument('--i', help='Path to input file.')
-        '--i',
+    parser.add_argument('--o', default='result.csv', help='Path to output file. Defaults to result.csv.')
-        help='Path to input file.')
+    parser.add_argument('--lat', type=float, default=-1, help='Recording location latitude. Set -1 to ignore.')
-    parser.add_argument(
+    parser.add_argument('--lon', type=float, default=-1, help='Recording location longitude. Set -1 to ignore.')
-        '--o',
+    parser.add_argument('--week', type=int, default=-1, help='Week of the year when the recording was made. Values in [1, 48] (4 weeks per month). Set -1 to ignore.')
-        default='result.csv',
+    parser.add_argument('--overlap', type=float, default=0.0, help='Overlap in seconds between extracted spectrograms. Values in [0.0, 2.9]. Defaults tp 0.0.')
-        help='Path to output file. Defaults to result.csv.')
+    parser.add_argument('--sensitivity', type=float, default=1.0, help='Detection sensitivity; Higher values result in higher sensitivity. Values in [0.5, 1.5]. Defaults to 1.0.')
-    parser.add_argument(
+    parser.add_argument('--min_conf', type=float, default=0.1, help='Minimum confidence threshold. Values in [0.01, 0.99]. Defaults to 0.1.')   
-        '--lat',
+    parser.add_argument('--include_list', default='null', help='Path to text file containing a list of included species. Not used if not provided.')
-        type=float,
+    parser.add_argument('--exclude_list', default='null', help='Path to text file containing a list of excluded species. Not used if not provided.')
-        default=-1,
+    parser.add_argument('--birdweather_id', default='99999', help='Private Station ID for BirdWeather.')    
-        help='Recording location latitude. Set -1 to ignore.')
-    parser.add_argument(
-        '--lon',
-        type=float,
-        default=-1,
-        help='Recording location longitude. Set -1 to ignore.')
-    parser.add_argument(
-        '--week',
-        type=int,
-        default=-1,
-        help='''Week of the year when the recording was made.
-                Values in [1, 48] (4 weeks per month). Set -1 to ignore.''')
-    parser.add_argument(
-        '--overlap',
-        type=float,
-        default=0.0,
-        help='''Overlap in seconds between extracted spectrograms.
-                Values in [0.0, 2.9]. Defaults tp 0.0.''')
-    parser.add_argument(
-        '--sensitivity',
-        type=float,
-        default=1.0,
-        help='''Detection sensitivity;
-                Higher values result in higher sensitivity.
-                Values in [0.5, 1.5]. Defaults to 1.0.''')
-    parser.add_argument(
-        '--min_conf',
-        type=float,
-        default=0.1,
-        help='''Minimum confidence threshold.
-                Values in [0.01, 0.99]. Defaults to 0.1.''')
-    parser.add_argument(
-        '--include_list',
-        default='null',
-        help='''Path to text file containing a list of included species.
-                Not used if not provided.''')
-    parser.add_argument(
-        '--exclude_list',
-        default='null',
-        help='''Path to text file containing a list of excluded species.
-                Not used if not provided.''')
-    parser.add_argument(
-        '--birdweather_id',
-        default='99999',
-        help='Private Station ID for BirdWeather.')
 
     args = parser.parse_args()
 
@@ -133,6 +73,10 @@ def main():
 ###############################################################################    
 ###############################################################################    
 
-
 if __name__ == '__main__':
+
     main()
+
+    # Example calls
+    # python3 analyze.py --i 'example/XC558716 - Soundscape.mp3' --lat 35.4244 --lon -120.7463 --week 18
+    # python3 analyze.py --i 'example/XC563936 - Soundscape.mp3' --lat 47.6766 --lon -122.294 --week 11 --overlap 1.5 --min_conf 0.25 --sensitivity 1.25 --custom_list 'example/custom_species_list.txt'

scripts/daily_plot.py

@@ -1,5 +1,6 @@
 import sqlite3
 import os
+import configparser
 import pandas as pd
 import seaborn as sns
 import matplotlib.pyplot as plt
@@ -11,8 +12,7 @@ userDir = os.path.expanduser('~')
 conn = sqlite3.connect(userDir + '/BirdNET-Pi/scripts/birds.db')
 df = pd.read_sql_query("SELECT * from detections", conn)
 cursor = conn.cursor()
-cursor.execute(
+cursor.execute('SELECT * FROM detections WHERE Date = DATE(\'now\', \'localtime\')')
-    'SELECT * FROM detections WHERE Date = DATE(\'now\', \'localtime\')')
 
 table_rows = cursor.fetchall()
 
@@ -37,29 +37,17 @@ df_plt_today = df_plt[df_plt['Date'] == now.strftime("%Y-%m-%d")]
 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(
+df_plt_top10_today = df_plt_today[df_plt_today.Com_Name.isin(plt_top10_today.index)]
-    plt_top10_today.index)]
 
 #Set Palette for graphics
 pal = "Greens"
 
 #Set up plot axes and titles
-f, axs = plt.subplots(
+f, axs = plt.subplots(1, 2, figsize = (10, 4), gridspec_kw=dict(width_ratios=[3, 6]), facecolor='#77C487')
-    1, 2, figsize=(
+plt.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=0, hspace=0)
-        10, 4), gridspec_kw=dict(
-            width_ratios=[
-                3, 6]), facecolor='#77C487')
-plt.subplots_adjust(
-    left=None,
-    bottom=None,
-    right=None,
-    top=None,
-    wspace=0,
-    hspace=0)
 
 #generate y-axis order for all figures based on frequency
-freq_order = pd.value_counts(
+freq_order = pd.value_counts(df_plt_top10_today['Com_Name']).iloc[:readings].index
-    df_plt_top10_today['Com_Name']).iloc[:readings].index
 
 #make color for max confidence --> this groups by name and calculates max conf
 confmax = df_plt_top10_today.groupby('Com_Name')['Confidence'].max()
@@ -71,28 +59,21 @@ norm = plt.Normalize(confmax.values.min(), confmax.values.max())
 colors = plt.cm.Greens(norm(confmax))
 
 #Generate frequency plot
-plot = sns.countplot(
+plot=sns.countplot(y='Com_Name', data = df_plt_top10_today, palette = colors,  order=freq_order, ax=axs[0])
-    y='Com_Name',
-    data=df_plt_top10_today,
-    palette=colors,
-    order=freq_order,
-    ax=axs[0])
 
 
-# Try plot grid lines between bars - problem at the moment plots grid
+
-# lines on bars - want between bars
+
+#Try plot grid lines between bars - problem at the moment plots grid lines on bars - want between bars
 z=plot.get_ymajorticklabels()
-plot.set_yticklabels(['\n'.join(textwrap.wrap(ticklabel.get_text(), 15))
+plot.set_yticklabels(['\n'.join(textwrap.wrap(ticklabel.get_text(),15)) for ticklabel in plot.get_yticklabels()], fontsize = 10)
-                     for ticklabel in plot.get_yticklabels()], fontsize=10)
 plot.set(ylabel=None)
 plot.set(xlabel="Detections")
 
 
 #Generate crosstab matrix for heatmap plot
 
-heat = pd.crosstab(
+heat = pd.crosstab(df_plt_top10_today['Com_Name'],df_plt_top10_today['Hour of Day'])
-    df_plt_top10_today['Com_Name'],
-    df_plt_top10_today['Hour of Day'])
 #Order heatmap Birds by frequency of occurrance
 heat.index = pd.CategoricalIndex(heat.index, categories = freq_order)
 heat.sort_index(level=0, inplace=True)
@@ -103,20 +84,7 @@ heat_frame = pd.DataFrame(data=0, index=heat.index, columns=hours_in_day)
 heat=(heat+heat_frame).fillna(0)
 
 #Generatie heatmap plot
-plot = sns.heatmap(
+plot = sns.heatmap(heat, norm=LogNorm(),  annot=True,  annot_kws={"fontsize":7}, fmt="g", cmap = pal , square = False, cbar=False, linewidths = 0.5, linecolor = "Grey", ax=axs[1], yticklabels = False)
-    heat,
-    norm=LogNorm(),
-    annot=True,
-    annot_kws={
-        "fontsize": 7},
-    fmt="g",
-    cmap=pal,
-    square=False,
-    cbar=False,
-    linewidths=0.5,
-    linecolor="Grey",
-    ax=axs[1],
-    yticklabels=False)
 plot.set_xticklabels(plot.get_xticklabels(), rotation = 0, size = 7)
 
 # Set heatmap border
@@ -131,8 +99,7 @@ plt.suptitle("Top 10 Last Updated: " + str(now.strftime("%Y-%m-%d %H:%M")))
 
 #Save combined plot
 userDir = os.path.expanduser('~')
-savename = userDir + '/BirdSongs/Extracted/Charts/Combo-' + \
+savename=userDir + '/BirdSongs/Extracted/Charts/Combo-'+str(now.strftime("%Y-%m-%d"))+'.png'
-    str(now.strftime("%Y-%m-%d")) + '.png'
 plt.savefig(savename)
 plt.show()
 plt.close()
@@ -140,30 +107,18 @@ plt.close()
 
 # Get Bottom detection frequency
 plt_Bot10_today = (df_plt_today['Com_Name'].value_counts()[-readings:])
-df_plt_Bot10_today = df_plt_today[df_plt_today.Com_Name.isin(
+df_plt_Bot10_today = df_plt_today[df_plt_today.Com_Name.isin(plt_Bot10_today.index)]
-    plt_Bot10_today.index)]
 
 #Set Palette for graphics
 pal = "Reds"
 
 #Set up plot axes and titles
 
-f, axs = plt.subplots(
+f, axs = plt.subplots(1, 2, figsize = (10, 4), gridspec_kw=dict(width_ratios=[3, 6]), facecolor='#77C487')
-    1, 2, figsize=(
+plt.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=0, hspace=0)
-        10, 4), gridspec_kw=dict(
-            width_ratios=[
-                3, 6]), facecolor='#77C487')
-plt.subplots_adjust(
-    left=None,
-    bottom=None,
-    right=None,
-    top=None,
-    wspace=0,
-    hspace=0)
 
 #generate y-axis order for all figures based on frequency
-freq_order = pd.value_counts(
+freq_order = pd.value_counts(df_plt_Bot10_today['Com_Name']).iloc[-readings:].index
-    df_plt_Bot10_today['Com_Name']).iloc[-readings:].index
 
 #make color for max confidence --> this groups by name and calculates max conf
 confmax = df_plt_Bot10_today.groupby('Com_Name')['Confidence'].max()
@@ -174,27 +129,20 @@ norm = plt.Normalize(confmax.values.min(), confmax.values.max())
 colors = plt.cm.Reds(norm(confmax))
 
 #Generate frequency plot
-plot = sns.countplot(
+plot=sns.countplot(y='Com_Name', data = df_plt_Bot10_today, palette = colors,  order=freq_order, ax=axs[0])
-    y='Com_Name',
-    data=df_plt_Bot10_today,
-    palette=colors,
-    order=freq_order,
-    ax=axs[0])
 
 
-# Try plot grid lines between bars - problem at the moment plots grid
+
-# lines on bars - want between bars
+
+#Try plot grid lines between bars - problem at the moment plots grid lines on bars - want between bars
 z=plot.get_ymajorticklabels()
-plot.set_yticklabels(['\n'.join(textwrap.wrap(ticklabel.get_text(), 15))
+plot.set_yticklabels(['\n'.join(textwrap.wrap(ticklabel.get_text(),15)) for ticklabel in plot.get_yticklabels()], fontsize = 10)
-                     for ticklabel in plot.get_yticklabels()], fontsize=10)
 plot.set(ylabel=None)
 plot.set(xlabel="Detections")
 
 #Generate crosstab matrix for heatmap plot
 
-heat = pd.crosstab(
+heat = pd.crosstab(df_plt_Bot10_today['Com_Name'],df_plt_Bot10_today['Hour of Day'])
-    df_plt_Bot10_today['Com_Name'],
-    df_plt_Bot10_today['Hour of Day'])
 #Order heatmap Birds by frequency of occurrance
 heat.index = pd.CategoricalIndex(heat.index, categories = freq_order)
 heat.sort_index(level=0, inplace=True)
@@ -205,20 +153,7 @@ heat_frame = pd.DataFrame(data=0, index=heat.index, columns=hours_in_day)
 heat=(heat+heat_frame).fillna(0)
 
 #Generatie heatmap plot
-plot = sns.heatmap(
+plot = sns.heatmap(heat, norm=LogNorm(),  annot=True, fmt="g",  annot_kws={"fontsize":7}, cmap = pal , square = False, cbar=False, linewidths = 0.5, linecolor = "Grey", ax=axs[1], yticklabels = False)
-    heat,
-    norm=LogNorm(),
-    annot=True,
-    fmt="g",
-    annot_kws={
-        "fontsize": 7},
-    cmap=pal,
-    square=False,
-    cbar=False,
-    linewidths=0.5,
-    linecolor="Grey",
-    ax=axs[1],
-    yticklabels=False)
 plot.set_xticklabels(plot.get_xticklabels(), rotation = 0, size = 7)
 
 # Set heatmap border
@@ -232,8 +167,7 @@ f.subplots_adjust(top=0.9)
 plt.suptitle("Bottom 10 Last Updated: "+ str(now.strftime("%Y-%m-%d %H:%M")))
 
 #Save combined plot
-savename = userDir + '/BirdSongs/Extracted/Charts/Combo2-' + \
+savename=userDir + '/BirdSongs/Extracted/Charts/Combo2-'+str(now.strftime("%Y-%m-%d"))+'.png'
-    str(now.strftime("%Y-%m-%d")) + '.png'
 plt.savefig(savename)
 plt.show()
 plt.close()

scripts/plotly_streamlit.py

@@ -4,7 +4,8 @@ import pandas as pd
 import numpy as np
 import plotly.graph_objects as go
 from plotly.subplots import make_subplots
-from datetime import timedelta
+from datetime import timedelta, datetime
+from pathlib import Path
 import sqlite3
 from sqlite3 import Connection
 
@@ -41,7 +42,6 @@ def get_data(conn: Connection):
     df1=pd.read_sql("SELECT * FROM detections", con=conn)
     return df1
 
-
 conn = get_connection(URI_SQLITE_DB)
 # Read in the cereal data
 # df = load_data()
@@ -51,6 +51,7 @@ df2['DateTime'] = pd.to_datetime(df2['Date'] + " " + df2['Time'])
 df2=df2.set_index('DateTime')
 
 
+
 # Filter on date range
 # Date as calendars
 # Start_Date = pd.to_datetime(st.sidebar.date_input('Which date do you want to start?', value = df2.index.min()))
@@ -67,6 +68,7 @@ Date_Slider = st.slider('Date Range',
                                 )
 
 
+
 filt = (df2.index >= pd.Timestamp(Date_Slider[0])) &  (df2.index <= pd.Timestamp(Date_Slider[1]+timedelta(days=1)))
 df2 = df2[filt]
 
@@ -92,10 +94,7 @@ top_N = cols1.slider(
 top_N_species = (df2['Com_Name'].value_counts()[:top_N])
 
 
-specie = cols2.selectbox(
+specie = cols2.selectbox('Which bird would you like to explore for the dates '+str(Date_Slider[0])+' to '+str(Date_Slider[1])+'?', species,
-    'Which bird would you like to explore for the dates ' +
-    str(Date_Slider[0]) + ' to ' + str(Date_Slider[1]) + '?',
-    species,
                               index=species.index(list(top_N_species.index)[0]))
 
 
@@ -109,17 +108,11 @@ df_counts = df2[filt].resample('D').count()
 
 fig = make_subplots(
                     rows=3, cols =2,
-    specs=[[{"type": "xy", "rowspan": 3}, {"type": "polar", "rowspan": 2}], [
+                    specs= [[{"type":"xy","rowspan":3}, {"type":"polar","rowspan":2}], [{"rowspan":1}, {"rowspan":1} ], [None, {"type":"xy","rowspan":1}]],
-        {"rowspan": 1}, {"rowspan": 1}], [None, {"type": "xy", "rowspan": 1}]],
+                    subplot_titles=('<b>Top '+ str(top_N) + ' Species in Date Range '+str(Date_Slider[0])+' to '+str(Date_Slider[1])+'</b>',
-    subplot_titles=(
-        '<b>Top ' + str(top_N) +
-        ' Species in Date Range ' + str(Date_Slider[0]) +
-        ' to ' + str(Date_Slider[1]) +
-        '</b>',
                                     'Total Detect:'+str('{:,}'.format(sum(df_counts.Time)))+
                                     '   Confidence Max:'+str('{:.2f}%'.format(max(df2[df2['Com_Name']==specie]['Confidence'])*100))+
-        '   ' + '   Median:' +
+                                    '   '+'   Median:'+str('{:.2f}%'.format(np.median(df2[df2['Com_Name']==specie]['Confidence'])*100))
-        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)
@@ -154,16 +147,15 @@ fig.update_layout(
             rotation = -90,
             direction = 'clockwise',
             tickmode='array',
-            tickvals=[0, 15, 35, 45, 60, 75, 90, 105, 120, 135, 150, 165,
+            tickvals=[0,15,35,45,60,75,90,105,120,135,150,165,180,195,210,225,240,255,270,285,300,315,330,345],
-                      180, 195, 210, 225, 240, 255, 270, 285, 300, 315, 330, 345],
+            ticktext=['12am','1am','2am','3am','4am','5am', '6am','7am','8am','9am','10am','11am','12pm','1pm','2pm','3pm','4pm','5pm', '6pm','7pm','8pm','9pm','10pm','11pm'],
-            ticktext=['12am', '1am', '2am', '3am', '4am', '5am', '6am', '7am', '8am', '9am', '10am', '11am',
-                      '12pm', '1pm', '2pm', '3pm', '4pm', '5pm', '6pm', '7pm', '8pm', '9pm', '10pm', '11pm'],
             hoverformat = "#%{theta}: <br>Popularity: %{percent} </br> %{r}"
         ),
         ),
     )
 
 
+
 daily=pd.crosstab(df2['Com_Name'],df2.index.date, dropna=False)
 
 fig.add_trace(go.Bar(x=daily.columns, y=daily.loc[specie]), row=3, col=2)
@@ -176,6 +168,6 @@ st.plotly_chart(fig, use_container_width=True)  # , config=config)
 # 
 # extract_date=Date_Slider
 # 
-# audio_file = open('/home/*/BirdSongs/Extracted/By_Date/2022-03-22/Yellow-streaked_Greenbul/Yellow-streaked_Greenbul-77-2022-03-22-birdnet-15:04:28.mp3', 'rb') # noqa: E501
+# audio_file = open('/home/*/BirdSongs/Extracted/By_Date/2022-03-22/Yellow-streaked_Greenbul/Yellow-streaked_Greenbul-77-2022-03-22-birdnet-15:04:28.mp3', 'rb')
 # audio_bytes = audio_file.read()
 # cols4.audio(audio_bytes, format='audio/mp3')

scripts/server.py

@@ -1,27 +1,32 @@
-import os
 import socket 
 import threading
-import operator
+import os
-import librosa
-import numpy as np
-import math
-import time
-import json
-import requests
-import sqlite3
-import datetime
-from tzlocal import get_localzone
-from pathlib import Path
-import apprise
-
 os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
 os.environ['CUDA_VISIBLE_DEVICES'] = ''
 
 try:
     import tflite_runtime.interpreter as tflite
-except BaseException:
+except:
     from tensorflow import lite as tflite
 
+import argparse
+import operator
+import librosa
+import numpy as np
+import math
+import time
+from decimal import Decimal
+import json
+import requests
+import sqlite3
+import datetime
+from time import sleep
+import pytz
+from tzlocal import get_localzone
+from pathlib import Path
+import apprise
+
+
 HEADER = 64
 PORT = 5050
 SERVER = socket.gethostbyname(socket.gethostname())
@@ -32,18 +37,18 @@ DISCONNECT_MESSAGE = "!DISCONNECT"
 server = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
 try:
     server.bind(ADDR)
-except BaseException:
+except:
     print("Waiting on socket")
     time.sleep(5)
     
 
+
 # Open most recent Configuration and grab DB_PWD as a python variable
 userDir = os.path.expanduser('~')
 with open(userDir + '/BirdNET-Pi/scripts/thisrun.txt', 'r') as f:
     this_run = f.readlines()
     audiofmt = "." + str(str(str([i for i in this_run if i.startswith('AUDIOFMT')]).split('=')[1]).split('\\')[0])
-    priv_thresh = float(
+    priv_thresh = float("." + str(str(str([i for i in this_run if i.startswith('PRIVACY_THRESHOLD')]).split('=')[1]).split('\\')[0]))/10
-        "." + str(str(str([i for i in this_run if i.startswith('PRIVACY_THRESHOLD')]).split('=')[1]).split('\\')[0])) / 10
 
 
 def loadModel():
@@ -80,7 +85,6 @@ def loadModel():
 
     return myinterpreter
 
-
 def loadCustomSpeciesList(path):
 
     slist = []
@@ -91,7 +95,6 @@ def loadCustomSpeciesList(path):
 
     return slist
 
-
 def splitSignal(sig, rate, overlap, seconds=3.0, minlen=1.5):
 
     # Split signal with overlap
@@ -113,7 +116,6 @@ def splitSignal(sig, rate, overlap, seconds=3.0, minlen=1.5):
 
     return sig_splits
 
-
 def readAudioData(path, overlap, sample_rate=48000):
 
     print('READING AUDIO DATA...', end=' ', flush=True)
@@ -128,7 +130,6 @@ def readAudioData(path, overlap, sample_rate=48000):
 
     return chunks
 
-
 def convertMetadata(m):
 
     # Convert week to cosine
@@ -146,11 +147,9 @@ def convertMetadata(m):
 
     return np.concatenate([m, mask])
 
-
 def custom_sigmoid(x, sensitivity=1.0):
     return 1 / (1.0 + np.exp(-sensitivity * x))
 
-
 def predict(sample, sensitivity):
     global INTERPRETER
     # Make a prediction
@@ -182,7 +181,6 @@ def predict(sample, sensitivity):
 
     return p_sorted[:human_cutoff]
 
-
 def analyzeAudioData(chunks, lat, lon, week, sensitivity, overlap,):
     global INTERPRETER
 
@@ -215,7 +213,7 @@ def analyzeAudioData(chunks, lat, lon, week, sensitivity, overlap,):
         pred_end = pred_start + 3.0
         
         #If human detected set all detections to human to make sure voices are not saved
-        if HUMAN_DETECTED is True:
+        if HUMAN_DETECTED == True:
             p=[('Human_Human',0.0)]*10
 
         detections[str(pred_start) + ';' + str(pred_end)] = p
@@ -226,17 +224,14 @@ def analyzeAudioData(chunks, lat, lon, week, sensitivity, overlap,):
 #    print('DETECTIONS:::::',detections)
     return detections
 
-
 def sendAppriseNotifications(species,confidence):
     if os.path.exists(userDir + '/BirdNET-Pi/apprise.txt') and os.path.getsize(userDir + '/BirdNET-Pi/apprise.txt') > 0:
         with open(userDir + '/BirdNET-Pi/scripts/thisrun.txt', 'r') as f:
             this_run = f.readlines()
-            title = str(str(str([i for i in this_run if i.startswith('APPRISE_NOTIFICATION_TITLE')]
+            title = str(str(str([i for i in this_run if i.startswith('APPRISE_NOTIFICATION_TITLE')]).split('=')[1]).split('\\')[0]).replace('"', '')
-                                ).split('=')[1]).split('\\')[0]).replace('"', '')
+            body = str(str(str([i for i in this_run if i.startswith('APPRISE_NOTIFICATION_BODY')]).split('=')[1]).split('\\')[0]).replace('"', '')
-            body = str(str(str([i for i in this_run if i.startswith('APPRISE_NOTIFICATION_BODY')]
-                               ).split('=')[1]).split('\\')[0]).replace('"', '')
 
-        if str(str(str([i for i in this_run if i.startswith('APPRISE_NOTIFY_EACH_DETECTION')]).split('=')[1]).split('\\')[0]) == "1": # noqa E501
+        if str(str(str([i for i in this_run if i.startswith('APPRISE_NOTIFY_EACH_DETECTION')]).split('=')[1]).split('\\')[0]) == "1":
 
             apobj = apprise.Apprise()
             config = apprise.AppriseConfig()
@@ -244,17 +239,10 @@ def sendAppriseNotifications(species, confidence):
             apobj.add(config)
         
             apobj.notify(
-                body=body.replace(
+                body=body.replace("$sciname",species.split("_")[0]).replace("$comname",species.split("_")[1]).replace("$confidence",confidence),
-                    "$sciname",
-                    species.split("_")[0]).replace(
-                    "$comname",
-                    species.split("_")[1]).replace(
-                    "$confidence",
-                    confidence),
                 title=title,
             )
 
-
 def writeResultsToFile(detections, min_conf, path):
 
     print('WRITING RESULTS TO', path, '...', end=' ')
@@ -263,15 +251,13 @@ 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)
+                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] not in EXCLUDE_LIST or len(EXCLUDE_LIST) == 0)):
+                    sendAppriseNotifications(str(entry[0]),str(entry[1]));
-                    sendAppriseNotifications(str(entry[0]), str(entry[1]))
                     rfile.write(d + ';' + entry[0].replace('_', ';') + ';' + str(entry[1]) + '\n')
                     rcnt += 1
     print('DONE! WROTE', rcnt, 'RESULTS.')
     return
 
-
 def handle_client(conn, addr):
     global INCLUDE_LIST
     global EXCLUDE_LIST
@@ -302,6 +288,7 @@ def handle_client(conn, addr):
                 args.lat = -1
                 args.lon =  -1
 
+
                 for line in msg.split('||'):
                     inputvars = line.split('=')
                     if inputvars[0] == 'i':
@@ -327,6 +314,8 @@ def handle_client(conn, addr):
                     elif inputvars[0] == 'lon':
                         args.lon = float(inputvars[1])
 
+
+                   
                 # Load custom species lists - INCLUDED and EXCLUDED
                 if not args.include_list == 'null':
                     INCLUDE_LIST = loadCustomSpeciesList(args.include_list)
@@ -382,14 +371,13 @@ def handle_client(conn, addr):
                 for i in detections:
                   myReturn += str(i) + '-' + str(detections[i][0]) + '\n'
                 
+                
                 with open(userDir + '/BirdNET-Pi/BirdDB.txt', 'a') as rfile:
                     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 (
+                            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) ):
-                                    entry[0] not in EXCLUDE_LIST or len(EXCLUDE_LIST) == 0)):
+                                rfile.write(str(current_date) + ';' + str(current_time) + ';' + entry[0].replace('_', ';') + ';' \
-                                rfile.write(str(current_date) + ';' + str(current_time) + ';' + entry[0].replace('_', ';') + ';'
+                                + str(entry[1]) +";" + str(args.lat) + ';' + str(args.lon) + ';' + str(min_conf) + ';' + str(week) + ';' \
-                                            + str(entry[1]) + ";" + str(args.lat) + ';' + str(args.lon) +
-                                            ';' + str(min_conf) + ';' + str(week) + ';'
                                 + str(args.sensitivity) +';' + str(args.overlap) + '\n')
                                 
                                 Date = str(current_date)
@@ -413,78 +401,34 @@ def handle_client(conn, addr):
                                     try: 
                                         con = sqlite3.connect(userDir + '/BirdNET-Pi/scripts/birds.db')
                                         cur = con.cursor()
-                                        cur.execute(
+                                        cur.execute("INSERT INTO detections VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)", (Date, Time, Sci_Name, Com_Name, str(score), Lat, Lon, Cutoff, Week, Sens, Overlap, File_Name))
-                                            "INSERT INTO detections VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
-                                            (Date,
-                                             Time,
-                                             Sci_Name,
-                                             Com_Name,
-                                             str(score),
-                                                Lat,
-                                                Lon,
-                                                Cutoff,
-                                                Week,
-                                                Sens,
-                                                Overlap,
-                                                File_Name))
 
                                         con.commit()
                                         con.close()
                                         break
-                                    except BaseException:
+                                    except:
                                         print("Database busy")
                                         time.sleep(2)
 
-                                print(str(current_date) +
+                                print(str(current_date) + ';' + str(current_time) + ';' + entry[0].replace('_', ';') + ';' + str(entry[1]) + ';' + str(args.lat) + ';' + str(args.lon) + ';' + str(min_conf) + ';' + str(week) + ';' + str(args.sensitivity) +';' + str(args.overlap) + Com_Name.replace(" ", "_") + '-' + str(score) + '-' + str(current_date) + '-birdnet-' + str(current_time) + audiofmt  + '\n')
-                                      ';' +
-                                      str(current_time) +
-                                      ';' +
-                                      entry[0].replace('_', ';') +
-                                      ';' +
-                                      str(entry[1]) +
-                                      ';' +
-                                      str(args.lat) +
-                                      ';' +
-                                      str(args.lon) +
-                                      ';' +
-                                      str(min_conf) +
-                                      ';' +
-                                      str(week) +
-                                      ';' +
-                                      str(args.sensitivity) +
-                                      ';' +
-                                      str(args.overlap) +
-                                      Com_Name.replace(" ", "_") +
-                                      '-' +
-                                      str(score) +
-                                      '-' +
-                                      str(current_date) +
-                                      '-birdnet-' +
-                                      str(current_time) +
-                                      audiofmt +
-                                      '\n')
 
                                 if birdweather_id != "99999":
                                     try:
 
                                         if soundscape_uploaded is False:
                                             # POST soundscape to server
-                                            soundscape_url = "https://app.birdweather.com/api/v1/stations/" + \
+                                            soundscape_url = "https://app.birdweather.com/api/v1/stations/" + birdweather_id +  "/soundscapes" + "?timestamp=" + current_iso8601
-                                                birdweather_id + "/soundscapes" + "?timestamp=" + current_iso8601
     
                                             with open(args.i, 'rb') as f:
                                                 wav_data = f.read()
-                                            response = requests.post(
+                                            response = requests.post(url=soundscape_url, data=wav_data, headers={'Content-Type': 'application/octet-stream'})
-                                                url=soundscape_url, data=wav_data, headers={
-                                                    'Content-Type': 'application/octet-stream'})
                                             print("Soundscape POST Response Status - ", response.status_code)
                                             sdata = response.json()
                                             soundscape_id = sdata['soundscape']['id']
                                             soundscape_uploaded = True
     
                                         # POST detection to server
-                                        detection_url = "https://app.birdweather.com/api/v1/stations/" + \
+                                        detection_url = "https://app.birdweather.com/api/v1/stations/" + birdweather_id + "/detections"
-                                            birdweather_id + "/detections"
                                         start_time = d.split(';')[0]
                                         end_time = d.split(';')[1]
                                         post_begin = "{ "
@@ -502,15 +446,11 @@ def handle_client(conn, addr):
                                         post_confidence = "\"confidence\": " + str(entry[1])
                                         post_end = " }"
     
-                                        post_json = post_begin + \
+                                        post_json = post_begin + post_timestamp + post_lat + post_lon + post_soundscape_id + post_soundscape_start_time + post_soundscape_end_time + post_commonName + post_scientificName + post_algorithm + post_confidence + post_end
-                                            post_timestamp + post_lat + post_lon + \
-                                            post_soundscape_id + post_soundscape_start_time + \
-                                            post_soundscape_end_time + post_commonName + post_scientificName + \
-                                            post_algorithm + post_confidence + post_end
                                         print(post_json)
                                         response = requests.post(detection_url, json=json.loads(post_json))
                                         print("Detection POST Response Status - ", response.status_code)
-                                    except BaseException:
+                                    except:
                                         print("Cannot POST right now")
                 conn.send(myReturn.encode(FORMAT))
 
@@ -518,7 +458,6 @@ def handle_client(conn, addr):
 
     conn.close() 
 
-
 def start():
     # Load model
     global INTERPRETER, INCLUDE_LIST, EXCLUDE_LIST