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Updating script/privacy_server.py to satisfy pep8 style guide

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Used 'autopep8 --in-place --aggressive scripts/privacy_server.py' as initial style fixes.
This commit is contained in:
Jake Herbst
2022-05-11 08:05:54 -04:00
parent f81b2c3014
commit 5f5c320e61
1 changed files with 191 additions and 104 deletions
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scripts/privacy_server.py
+191 -104
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@@ -1,4 +1,19 @@
import socket
from pathlib import Path
from tzlocal import get_localzone
import pytz
from time import sleep
import datetime
import sqlite3
import requests
import json
from decimal import Decimal
import time
import math
import numpy as np
import librosa
import operator
import argparse
import socket
import threading
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
@@ -6,25 +21,9 @@ os.environ['CUDA_VISIBLE_DEVICES'] = ''
try:
import tflite_runtime.interpreter as tflite
except:
except BaseException:
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
HEADER = 64
PORT = 5050
@@ -36,17 +35,18 @@ DISCONNECT_MESSAGE = "!DISCONNECT"
server = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
try:
server.bind(ADDR)
except:
except BaseException:
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])
audiofmt = "." + \
str(str(str([i for i in this_run if i.startswith(
'AUDIOFMT')]).split('=')[1]).split('\\')[0])
def loadModel():
@@ -60,7 +60,7 @@ def loadModel():
# Load TFLite model and allocate tensors.
modelpath = userDir + '/BirdNET-Pi/model/BirdNET_6K_GLOBAL_MODEL.tflite'
myinterpreter = tflite.Interpreter(model_path=modelpath,num_threads=2)
myinterpreter = tflite.Interpreter(model_path=modelpath, num_threads=2)
myinterpreter.allocate_tensors()
# Get input and output tensors.
@@ -82,6 +82,7 @@ def loadModel():
return myinterpreter
def loadCustomSpeciesList(path):
slist = []
@@ -92,6 +93,7 @@ def loadCustomSpeciesList(path):
return slist
def splitSignal(sig, rate, overlap, seconds=3.0, minlen=1.5):
# Split signal with overlap
@@ -102,23 +104,25 @@ def splitSignal(sig, rate, overlap, seconds=3.0, minlen=1.5):
# End of signal?
if len(split) < int(minlen * rate):
break
# Signal chunk too short? Fill with zeros.
if len(split) < int(rate * seconds):
temp = np.zeros((int(rate * seconds)))
temp[:len(split)] = split
split = temp
sig_splits.append(split)
return sig_splits
def readAudioData(path, overlap, sample_rate=48000):
print('READING AUDIO DATA...', end=' ', flush=True)
# Open file with librosa (uses ffmpeg or libav)
sig, rate = librosa.load(path, sr=sample_rate, mono=True, res_type='kaiser_fast')
sig, rate = librosa.load(
path, sr=sample_rate, mono=True, res_type='kaiser_fast')
# Split audio into 3-second chunks
chunks = splitSignal(sig, rate, overlap)
@@ -127,11 +131,12 @@ def readAudioData(path, overlap, sample_rate=48000):
return chunks
def convertMetadata(m):
# Convert week to cosine
if m[2] >= 1 and m[2] <= 48:
m[2] = math.cos(math.radians(m[2] * 7.5)) + 1
m[2] = math.cos(math.radians(m[2] * 7.5)) + 1
else:
m[2] = -1
@@ -144,14 +149,20 @@ 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
INTERPRETER.set_tensor(INPUT_LAYER_INDEX, np.array(sample[0], dtype='float32'))
INTERPRETER.set_tensor(MDATA_INPUT_INDEX, np.array(sample[1], dtype='float32'))
INTERPRETER.set_tensor(
INPUT_LAYER_INDEX, np.array(
sample[0], dtype='float32'))
INTERPRETER.set_tensor(
MDATA_INPUT_INDEX, np.array(
sample[1], dtype='float32'))
INTERPRETER.invoke()
prediction = INTERPRETER.get_tensor(OUTPUT_LAYER_INDEX)[0]
@@ -162,26 +173,32 @@ def predict(sample, sensitivity):
p_labels = dict(zip(CLASSES, p_sigmoid))
# Sort by score
p_sorted = sorted(p_labels.items(), key=operator.itemgetter(1), reverse=True)
p_sorted = sorted(
p_labels.items(),
key=operator.itemgetter(1),
reverse=True)
# Remove species that are on blacklist
for i in range(min(10, len(p_sorted))):
if p_sorted[i][0] in ['Non-bird_Non-bird', 'Noise_Noise']:
p_sorted[i] = (p_sorted[i][0], 0.0)
if p_sorted[i][0]=='Human_Human':
print("HUMAN SCORE:",str(p_sorted[i]))
HUMAN_FLAG=True
if p_sorted[i][0] == 'Human_Human':
print("HUMAN SCORE:", str(p_sorted[i]))
HUMAN_FLAG = True
with open(userDir + '/BirdNET-Pi/HUMAN.txt', 'a') as rfile:
rfile.write(str(datetime.datetime.now())+str(p_sorted[i])+ '\n')
rfile.write(str(datetime.datetime.now()) +
str(p_sorted[i]) + '\n')
# date_stamp=datetime.datetime.now().strftime("%d_%m_%y_%H:%M:%S")
#
# sf.write('./home/*/human_sample.wav',np.random.randn(10,2) , 44100) #sample[0]
#
# sf.write('./home/*/human_sample.wav',np.random.randn(10,2) , 44100)
# #sample[0]
# Only return first the top ten results
#INCREASE THIS TO SEE IF HUMAN IS DETECTED MORE RELIABLY
# INCREASE THIS TO SEE IF HUMAN IS DETECTED MORE RELIABLY
# print('P_SORTED-------', p_sorted)
return p_sorted[:100]
def analyzeAudioData(chunks, lat, lon, week, sensitivity, overlap,):
global INTERPRETER
@@ -203,24 +220,24 @@ def analyzeAudioData(chunks, lat, lon, week, sensitivity, overlap,):
# Make prediction
p = predict([sig, mdata], sensitivity)
# print("PPPPP",p)
HUMAN_DETECTED=False
#Catch if Human is recognized
HUMAN_DETECTED = False
# Catch if Human is recognized
for x in range(len(p)):
if "Human" in p[x][0]:
# print("HUMAN DETECTED!!",p[x][0])
#clear list
HUMAN_DETECTED=True
print("CHUNK -----",c)
# print("HUMAN DETECTED!!",p[x][0])
# clear list
HUMAN_DETECTED = True
print("CHUNK -----", c)
# Save result and timestamp
pred_end = pred_start + 3.0
if HUMAN_DETECTED == True:
p=[('Human_Human',0.0)]*10
print("HUMAN DETECTED!!!",p)
p = [('Human_Human', 0.0)] * 10
print("HUMAN DETECTED!!!", p)
detections[str(pred_start) + ';' + str(pred_end)] = p
pred_start = pred_end - overlap
print('DONE! Time', int((time.time() - start) * 10) / 10.0, 'SECONDS')
@@ -233,15 +250,23 @@ def writeResultsToFile(detections, min_conf, path):
print('WRITING RESULTS TO', path, '...', end=' ')
rcnt = 0
with open(path, 'w') as rfile:
rfile.write('Start (s);End (s);Scientific name;Common name;Confidence\n')
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) ):
rfile.write(d + ';' + entry[0].replace('_', ';') + ';' + str(entry[1]) + '\n')
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)):
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
@@ -257,9 +282,9 @@ def handle_client(conn, addr):
connected = False
else:
#print(f"[{addr}] {msg}")
args = type('', (), {})()
args.i = ''
args.o = ''
args.birdweather_id = '99999'
@@ -270,8 +295,7 @@ def handle_client(conn, addr):
args.sensitivity = 1.25
args.min_conf = 0.70
args.lat = -1
args.lon = -1
args.lon = -1
for line in msg.split('||'):
inputvars = line.split('=')
@@ -298,14 +322,12 @@ 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)
else:
INCLUDE_LIST = []
if not args.exclude_list == 'null':
EXCLUDE_LIST = loadCustomSpeciesList(args.exclude_list)
else:
@@ -324,7 +346,8 @@ def handle_client(conn, addr):
file_date = file_name.split('-birdnet-')[0]
file_time = file_name.split('-birdnet-')[1]
date_time_str = file_date + ' ' + file_time
date_time_obj = datetime.datetime.strptime(date_time_str, '%Y-%m-%d %H:%M:%S')
date_time_obj = datetime.datetime.strptime(
date_time_str, '%Y-%m-%d %H:%M:%S')
#print('Date:', date_time_obj.date())
#print('Time:', date_time_obj.time())
print('Date-time:', date_time_obj)
@@ -332,44 +355,47 @@ def handle_client(conn, addr):
current_date = now.strftime("%Y-%m-%d")
current_time = now.strftime("%H:%M:%S")
current_iso8601 = now.astimezone(get_localzone()).isoformat()
week_number = int(now.strftime("%V"))
week = max(1, min(week_number, 48))
sensitivity = max(0.5, min(1.0 - (args.sensitivity - 1.0), 1.5))
sensitivity = max(
0.5, min(1.0 - (args.sensitivity - 1.0), 1.5))
# Process audio data and get detections
detections = analyzeAudioData(audioData, args.lat, args.lon, week, sensitivity, args.overlap)
detections = analyzeAudioData(
audioData, args.lat, args.lon, week, sensitivity, args.overlap)
# Write detections to output file
min_conf = max(0.01, min(args.min_conf, 0.99))
writeResultsToFile(detections, min_conf, args.o)
###############################################################################
###############################################################################
###################################################################
###################################################################
soundscape_uploaded = False
# Write detections to Database
myReturn = ''
for i in detections:
myReturn += str(i) + '-' + str(detections[i][0]) + '\n'
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 (entry[0] not in EXCLUDE_LIST or len(EXCLUDE_LIST) == 0) ):
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(args.sensitivity) +';' + str(args.overlap) + '\n')
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)):
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(args.sensitivity) + ';' + str(args.overlap) + '\n')
Date = str(current_date)
Time = str(current_time)
species = entry[0]
Sci_Name,Com_Name = species.split('_')
Sci_Name, Com_Name = species.split('_')
score = entry[1]
Confidence = str(round(score*100))
Confidence = str(round(score * 100))
Lat = str(args.lat)
Lon = str(args.lon)
Cutoff = str(args.min_conf)
@@ -378,66 +404,127 @@ def handle_client(conn, addr):
Overlap = str(args.overlap)
Com_Name = Com_Name.replace("'", "")
File_Name = Com_Name.replace(" ", "_") + '-' + Confidence + '-' + \
Date.replace("/", "-") + '-birdnet-' + Time + audiofmt
Date.replace(
"/", "-") + '-birdnet-' + Time + audiofmt
#Connect to SQLite Database
try:
con = sqlite3.connect(userDir + '/BirdNET-Pi/scripts/birds.db')
# Connect to SQLite Database
try:
con = sqlite3.connect(
userDir + '/BirdNET-Pi/scripts/birds.db')
cur = con.cursor()
cur.execute("INSERT INTO detections VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)", (Date, Time, Sci_Name, Com_Name, str(score), Lat, Lon, Cutoff, Week, Sens, Overlap, File_Name))
cur.execute(
"INSERT INTO detections VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
(Date,
Time,
Sci_Name,
Com_Name,
str(score),
Lat,
Lon,
Cutoff,
Week,
Sens,
Overlap,
File_Name))
con.commit()
con.close()
except:
except BaseException:
print("Database busy")
time.sleep(2)
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')
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')
if birdweather_id != "99999":
try:
if soundscape_uploaded is False:
# POST soundscape to server
soundscape_url = "https://app.birdweather.com/api/v1/stations/" + birdweather_id + "/soundscapes" + "?timestamp=" + current_iso8601
soundscape_url = "https://app.birdweather.com/api/v1/stations/" + \
birdweather_id + "/soundscapes" + "?timestamp=" + current_iso8601
with open(args.i, 'rb') as f:
wav_data = f.read()
response = requests.post(url=soundscape_url, data=wav_data, headers={'Content-Type': 'application/octet-stream'})
print("Soundscape POST Response Status - ", response.status_code)
response = requests.post(
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/" + birdweather_id + "/detections"
detection_url = "https://app.birdweather.com/api/v1/stations/" + \
birdweather_id + "/detections"
start_time = d.split(';')[0]
end_time = d.split(';')[1]
post_begin = "{ "
now_p_start = now + datetime.timedelta(seconds=float(start_time))
current_iso8601 = now_p_start.astimezone(get_localzone()).isoformat()
post_timestamp = "\"timestamp\": \"" + current_iso8601 + "\","
post_lat = "\"lat\": " + str(args.lat) + ","
post_lon = "\"lon\": " + str(args.lon) + ","
post_soundscape_id = "\"soundscapeId\": " + str(soundscape_id) + ","
now_p_start = now + \
datetime.timedelta(
seconds=float(start_time))
current_iso8601 = now_p_start.astimezone(
get_localzone()).isoformat()
post_timestamp = "\"timestamp\": \"" + current_iso8601 + "\","
post_lat = "\"lat\": " + \
str(args.lat) + ","
post_lon = "\"lon\": " + \
str(args.lon) + ","
post_soundscape_id = "\"soundscapeId\": " + \
str(soundscape_id) + ","
post_soundscape_start_time = "\"soundscapeStartTime\": " + start_time + ","
post_soundscape_end_time = "\"soundscapeEndTime\": " + end_time + ","
post_commonName = "\"commonName\": \"" + entry[0].split('_')[1] + "\","
post_scientificName = "\"scientificName\": \"" + entry[0].split('_')[0] + "\","
post_commonName = "\"commonName\": \"" + \
entry[0].split('_')[1] + "\","
post_scientificName = "\"scientificName\": \"" + \
entry[0].split('_')[0] + "\","
post_algorithm = "\"algorithm\": " + "\"alpha\"" + ","
post_confidence = "\"confidence\": " + str(entry[1])
post_confidence = "\"confidence\": " + \
str(entry[1])
post_end = " }"
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_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
print(post_json)
response = requests.post(detection_url, json=json.loads(post_json))
print("Detection POST Response Status - ", response.status_code)
except:
response = requests.post(
detection_url, json=json.loads(post_json))
print(
"Detection POST Response Status - ", response.status_code)
except BaseException:
print("Cannot POST right now")
conn.send(myReturn.encode(FORMAT))
#time.sleep(3)
# time.sleep(3)
conn.close()
conn.close()
def start():
# Load model