adding new server socket and analysis -- preparing
for test installation
This commit is contained in:
mcguirepr89
+44
-319
@@ -1,192 +1,24 @@
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# BirdWeather edits by @timsterc
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# Other edits by @CaiusX and @mcguirepr89
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import os
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os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
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os.environ['CUDA_VISIBLE_DEVICES'] = ''
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try:
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import tflite_runtime.interpreter as tflite
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except:
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from tensorflow import lite as tflite
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import argparse
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import operator
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import librosa
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import numpy as np
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import math
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import time
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from decimal import Decimal
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import json
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import requests
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import mysql.connector
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import datetime
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import pytz
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from tzlocal import get_localzone
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from pathlib import Path
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import socket
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def loadModel():
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HEADER = 64
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PORT = 5050
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FORMAT = 'utf-8'
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DISCONNECT_MESSAGE = "!DISCONNECT"
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SERVER = "127.0.1.1"
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ADDR = (SERVER, PORT)
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global INPUT_LAYER_INDEX
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global OUTPUT_LAYER_INDEX
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global MDATA_INPUT_INDEX
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global CLASSES
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client = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
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client.connect(ADDR)
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print('LOADING TF LITE MODEL...', end=' ')
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# Load TFLite model and allocate tensors.
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interpreter = tflite.Interpreter(model_path='../model/BirdNET_6K_GLOBAL_MODEL.tflite',num_threads=2)
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interpreter.allocate_tensors()
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# Get input and output tensors.
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input_details = interpreter.get_input_details()
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output_details = interpreter.get_output_details()
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# Get input tensor index
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INPUT_LAYER_INDEX = input_details[0]['index']
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MDATA_INPUT_INDEX = input_details[1]['index']
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OUTPUT_LAYER_INDEX = output_details[0]['index']
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# Load labels
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CLASSES = []
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with open('../model/labels.txt', '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('DONE!')
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return interpreter
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def loadCustomSpeciesList(path):
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slist = []
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if os.path.isfile(path):
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with open(path, 'r') as csfile:
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for line in csfile.readlines():
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slist.append(line.replace('\r', '').replace('\n', ''))
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return slist
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def splitSignal(sig, rate, overlap, seconds=3.0, minlen=1.5):
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# Split signal with overlap
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sig_splits = []
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for i in range(0, len(sig), int((seconds - overlap) * rate)):
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split = sig[i:i + int(seconds * rate)]
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# End of signal?
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if len(split) < int(minlen * rate):
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break
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# Signal chunk too short? Fill with zeros.
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if len(split) < int(rate * seconds):
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temp = np.zeros((int(rate * seconds)))
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temp[:len(split)] = split
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split = temp
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sig_splits.append(split)
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return sig_splits
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def readAudioData(path, overlap, sample_rate=48000):
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print('READING AUDIO DATA...', end=' ', flush=True)
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# Open file with librosa (uses ffmpeg or libav)
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sig, rate = librosa.load(path, sr=sample_rate, mono=True, res_type='kaiser_fast')
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# Split audio into 3-second chunks
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chunks = splitSignal(sig, rate, overlap)
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print('DONE! READ', str(len(chunks)), 'CHUNKS.')
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return chunks
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def convertMetadata(m):
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# Convert week to cosine
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if m[2] >= 1 and m[2] <= 48:
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m[2] = math.cos(math.radians(m[2] * 7.5)) + 1
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else:
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m[2] = -1
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# Add binary mask
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mask = np.ones((3,))
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if m[0] == -1 or m[1] == -1:
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mask = np.zeros((3,))
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if m[2] == -1:
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mask[2] = 0.0
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return np.concatenate([m, mask])
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def custom_sigmoid(x, sensitivity=1.0):
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return 1 / (1.0 + np.exp(-sensitivity * x))
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def predict(sample, interpreter, sensitivity):
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# Make a prediction
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interpreter.set_tensor(INPUT_LAYER_INDEX, np.array(sample[0], dtype='float32'))
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interpreter.set_tensor(MDATA_INPUT_INDEX, np.array(sample[1], dtype='float32'))
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interpreter.invoke()
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prediction = interpreter.get_tensor(OUTPUT_LAYER_INDEX)[0]
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# Apply custom sigmoid
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p_sigmoid = custom_sigmoid(prediction, sensitivity)
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# Get label and scores for pooled predictions
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p_labels = dict(zip(CLASSES, p_sigmoid))
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# Sort by score
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p_sorted = sorted(p_labels.items(), key=operator.itemgetter(1), reverse=True)
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# Remove species that are on blacklist
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for i in range(min(10, len(p_sorted))):
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if p_sorted[i][0] in ['Human_Human', 'Non-bird_Non-bird', 'Noise_Noise']:
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p_sorted[i] = (p_sorted[i][0], 0.0)
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# Only return first the top ten results
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return p_sorted[:10]
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def analyzeAudioData(chunks, lat, lon, week, sensitivity, overlap, interpreter):
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detections = {}
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start = time.time()
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print('ANALYZING AUDIO...', end=' ', flush=True)
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# Convert and prepare metadata
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mdata = convertMetadata(np.array([lat, lon, week]))
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mdata = np.expand_dims(mdata, 0)
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# Parse every chunk
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pred_start = 0.0
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for c in chunks:
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# Prepare as input signal
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sig = np.expand_dims(c, 0)
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# Make prediction
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p = predict([sig, mdata], interpreter, sensitivity)
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# Save result and timestamp
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pred_end = pred_start + 3.0
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detections[str(pred_start) + ';' + str(pred_end)] = p
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pred_start = pred_end - overlap
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print('DONE! Time', int((time.time() - start) * 10) / 10.0, 'SECONDS')
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return detections
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def writeResultsToFile(detections, min_conf, path):
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print('WRITING RESULTS TO', path, '...', end=' ')
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rcnt = 0
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with open(path, 'w') as rfile:
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rfile.write('Start (s);End (s);Scientific name;Common name;Confidence\n')
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for d in detections:
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for entry in detections[d]:
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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) ):
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rfile.write(d + ';' + entry[0].replace('_', ';') + ';' + str(entry[1]) + '\n')
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rcnt += 1
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print('DONE! WROTE', rcnt, 'RESULTS.')
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def send(msg):
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message = msg.encode(FORMAT)
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msg_length = len(message)
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send_length = str(msg_length).encode(FORMAT)
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send_length += b' ' * (HEADER - len(send_length))
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client.send(send_length)
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client.send(message)
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print(client.recv(2048).decode(FORMAT))
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def main():
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@@ -203,145 +35,39 @@ def main():
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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.')
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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.')
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parser.add_argument('--min_conf', type=float, default=0.1, help='Minimum confidence threshold. Values in [0.01, 0.99]. Defaults to 0.1.')
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parser.add_argument('--include_list', default='', help='Path to text file containing a list of included species. Not used if not provided.')
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parser.add_argument('--exclude_list', default='', help='Path to text file containing a list of excluded species. Not used if not provided.')
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parser.add_argument('--include_list', default='null', help='Path to text file containing a list of included species. Not used if not provided.')
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parser.add_argument('--exclude_list', default='null', help='Path to text file containing a list of excluded species. Not used if not provided.')
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parser.add_argument('--birdweather_id', default='99999', help='Private Station ID for BirdWeather.')
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args = parser.parse_args()
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# Load model
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interpreter = loadModel()
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# Load custom species lists - INCLUDED and EXCLUDED
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if not args.include_list == '':
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INCLUDE_LIST = loadCustomSpeciesList(args.include_list)
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else:
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INCLUDE_LIST = []
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sockParams = ''
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if args.i:
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sockParams += 'i=' + args.i + '||'
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if args.o:
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sockParams += 'o=' + args.o + '||'
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if args.birdweather_id:
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sockParams += 'birdweather_id=' + args.birdweather_id + '||'
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if args.include_list:
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sockParams += 'include_list=' + args.include_list + '||'
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if args.exclude_list:
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sockParams += 'exclude_list=' + args.exclude_list + '||'
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if args.overlap:
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sockParams += 'overlap=' + args.overlap + '||'
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if args.week:
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sockParams += 'week=' + str(args.week) + '||'
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if args.sensitivity:
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sockParams += 'sensitivity=' + str(args.sensitivity) + '||'
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if args.min_conf:
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sockParams += 'min_conf=' + str(args.min_conf) + '||'
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if args.lat:
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sockParams += 'lat=' + str(args.lat) + '||'
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if args.lon:
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sockParams += 'lon=' + str(args.lon) + '||'
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if not args.exclude_list == '':
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EXCLUDE_LIST = loadCustomSpeciesList(args.exclude_list)
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else:
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EXCLUDE_LIST = []
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birdweather_id = args.birdweather_id
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# Read audio data
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audioData = readAudioData(args.i, args.overlap)
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# Get Date/Time from filename in case Pi gets behind
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#now = datetime.now()
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full_file_name = args.i
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file_name = Path(full_file_name).stem
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file_date = file_name.split('-birdnet-')[0]
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file_time = file_name.split('-birdnet-')[1]
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date_time_str = file_date + ' ' + file_time
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date_time_obj = datetime.datetime.strptime(date_time_str, '%Y-%m-%d %H:%M:%S')
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#print('Date:', date_time_obj.date())
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#print('Time:', date_time_obj.time())
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print('Date-time:', date_time_obj)
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now = date_time_obj
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current_date = now.strftime("%Y/%m/%d")
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current_time = now.strftime("%H:%M:%S")
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current_iso8601 = now.astimezone(get_localzone()).isoformat()
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week_number = int(now.strftime("%V"))
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week = max(1, min(week_number, 48))
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sensitivity = max(0.5, min(1.0 - (args.sensitivity - 1.0), 1.5))
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# Process audio data and get detections
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detections = analyzeAudioData(audioData, args.lat, args.lon, week, sensitivity, args.overlap, interpreter)
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# Write detections to output file
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min_conf = max(0.01, min(args.min_conf, 0.99))
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writeResultsToFile(detections, min_conf, args.o)
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###############################################################################
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###############################################################################
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soundscape_uploaded = False
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# Write detections to Database
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for i in detections:
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print("\n", detections[i][0],"\n")
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with open('../BirdDB.txt', 'a') as rfile:
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for d in detections:
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for entry in detections[d]:
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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) ):
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rfile.write(str(current_date) + ';' + str(current_time) + ';' + entry[0].replace('_', ';') + ';' \
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+ str(entry[1]) +";" + str(args.lat) + ';' + str(args.lon) + ';' + str(min_conf) + ';' + str(week) + ';' \
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+ str(sensitivity) +';' + str(args.overlap) + '\n')
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def insert_variables_into_table(Date, Time, Sci_Name, Com_Name, Confidence, Lat, Lon, Cutoff, Week, Sens, Overlap):
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try:
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connection = mysql.connector.connect(host='localhost',
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database='birds',
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user='birder',
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password='databasepassword')
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cursor = connection.cursor()
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mySql_insert_query = """INSERT INTO detections (Date, Time, Sci_Name, Com_Name, Confidence, Lat, Lon, Cutoff, Week, Sens, Overlap)
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VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s) """
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record = (Date, Time, Sci_Name, Com_Name, Confidence, Lat, Lon, Cutoff, Week, Sens, Overlap)
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cursor.execute(mySql_insert_query, record)
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connection.commit()
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print("Record inserted successfully into detections table")
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except mysql.connector.Error as error:
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print("Failed to insert record into detections table {}".format(error))
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finally:
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if connection.is_connected():
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connection.close()
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print("MySQL connection is closed")
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species = entry[0]
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sci_name,com_name = species.split('_')
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insert_variables_into_table(str(current_date), str(current_time), sci_name, com_name, \
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str(entry[1]), str(args.lat), str(args.lon), str(min_conf), str(week), \
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str(args.sensitivity), str(args.overlap))
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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) + '\n')
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if birdweather_id != "99999":
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if soundscape_uploaded is False:
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# POST soundscape to server
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soundscape_url = "https://app.birdweather.com/api/v1/stations/" + birdweather_id + "/soundscapes" + "?timestamp=" + current_iso8601
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with open(args.i, 'rb') as f:
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wav_data = f.read()
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response = requests.post(url=soundscape_url, data=wav_data, headers={'Content-Type': 'application/octet-stream'})
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print("Soundscape POST Response Status - ", response.status_code)
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sdata = response.json()
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soundscape_id = sdata['soundscape']['id']
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soundscape_uploaded = True
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# POST detection to server
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detection_url = "https://app.birdweather.com/api/v1/stations/" + birdweather_id + "/detections"
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start_time = d.split(';')[0]
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end_time = d.split(';')[1]
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post_begin = "{ "
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now_p_start = now + datetime.timedelta(seconds=float(start_time))
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current_iso8601 = now_p_start.astimezone(get_localzone()).isoformat()
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post_timestamp = "\"timestamp\": \"" + current_iso8601 + "\","
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post_lat = "\"lat\": " + str(args.lat) + ","
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post_lon = "\"lon\": " + str(args.lon) + ","
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post_soundscape_id = "\"soundscapeId\": " + str(soundscape_id) + ","
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post_soundscape_start_time = "\"soundscapeStartTime\": " + start_time + ","
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post_soundscape_end_time = "\"soundscapeEndTime\": " + end_time + ","
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post_commonName = "\"commonName\": \"" + entry[0].split('_')[1] + "\","
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post_scientificName = "\"scientificName\": \"" + entry[0].split('_')[0] + "\","
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post_algorithm = "\"algorithm\": " + "\"alpha\"" + ","
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post_confidence = "\"confidence\": " + str(entry[1])
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post_end = " }"
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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
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print(post_json)
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response = requests.post(detection_url, json=json.loads(post_json))
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print("Detection POST Response Status - ", response.status_code)
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send(sockParams)
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send(DISCONNECT_MESSAGE)
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#time.sleep(3)
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###############################################################################
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@@ -354,4 +80,3 @@ if __name__ == '__main__':
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# Example calls
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# python3 analyze.py --i 'example/XC558716 - Soundscape.mp3' --lat 35.4244 --lon -120.7463 --week 18
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# 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'
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@@ -39,7 +39,7 @@ GRANT ALL ON birds.* TO 'birder'@'localhost' IDENTIFIED BY '${DB_PWD}' WITH GRAN
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FLUSH PRIVILEGES;
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exit
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EOF
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sudo -u${USER} sed -i "s/databasepassword/${DB_PWD}/g" /home/pi/BirdNET-Pi/scripts/analyze.py
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sudo -u${USER} sed -i "s/databasepassword/${DB_PWD}/g" /home/pi/BirdNET-Pi/scripts/server.py
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sed -i "s/mysqli.default_host =.*/mysqli.default_host = localhost/g" /etc/php/7.4/fpm/php.ini
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sed -i "s/mysqli.default_user =.*/mysqli.default_user = birder/g" /etc/php/7.4/fpm/php.ini
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sed -i "s/mysqli.default_pw =.*/mysqli.default_pw = ${DB_PWD}/g" /etc/php/7.4/fpm/php.ini
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@@ -57,9 +57,10 @@ install_birdnet_analysis() {
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cat << EOF > /etc/systemd/system/birdnet_analysis.service
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[Unit]
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Description=BirdNET Analysis
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After=birdnet_server.service
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Requires=birdnet_server.service
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[Service]
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Restart=always
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RuntimeMaxSec=10800
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Type=simple
|
||||
RestartSec=2
|
||||
User=${USER}
|
||||
@@ -70,6 +71,24 @@ EOF
|
||||
systemctl enable birdnet_analysis.service
|
||||
}
|
||||
|
||||
install_birdnet_server() {
|
||||
echo "Installing the birdnet_server.service"
|
||||
cat << EOF > /etc/systemd/system/birdnet_server.service
|
||||
[Unit]
|
||||
Description=BirdNET Analysis Server
|
||||
Before=birdnet_analysis.service
|
||||
[Service]
|
||||
Restart=always
|
||||
Type=simple
|
||||
RestartSec=10
|
||||
User=${USER}
|
||||
ExecStart=/user/local/bin/server.py
|
||||
[Install]
|
||||
WantedBy=multi-user.target
|
||||
EOF
|
||||
systemctl enable birdnet_server.service
|
||||
}
|
||||
|
||||
install_extraction_service() {
|
||||
echo "Installing the extraction.service and extraction.timer"
|
||||
cat << EOF > /etc/systemd/system/extraction.service
|
||||
@@ -392,7 +411,7 @@ RestartSec=3
|
||||
Type=simple
|
||||
User=${USER}
|
||||
Environment=TERM=xterm-256color
|
||||
ExecStart=/usr/local/bin/gotty -p 8080 --title-format "BirdNET-Pi Log" journalctl -o cat -fu birdnet_analysis.service
|
||||
ExecStart=/usr/local/bin/gotty -p 8080 --title-format "BirdNET-Pi Log" journalctl -o cat -fu birdnet_server.service
|
||||
[Install]
|
||||
WantedBy=multi-user.target
|
||||
EOF
|
||||
@@ -517,6 +536,7 @@ install_selected_services() {
|
||||
update_system
|
||||
install_scripts
|
||||
install_birdnet_analysis
|
||||
install_birdnet_server
|
||||
|
||||
if [[ "${DO_EXTRACTIONS}" =~ [Yy] ]];then
|
||||
install_extraction_service
|
||||
|
||||
Executable
+424
@@ -0,0 +1,424 @@
|
||||
#!/home/pi/BirdNET-Pi/birdnet/bin/python3
|
||||
import socket
|
||||
import threading
|
||||
import os
|
||||
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
|
||||
os.environ['CUDA_VISIBLE_DEVICES'] = ''
|
||||
|
||||
try:
|
||||
import tflite_runtime.interpreter as tflite
|
||||
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 mysql.connector
|
||||
###############################################################################
|
||||
import datetime
|
||||
import pytz
|
||||
from tzlocal import get_localzone
|
||||
from pathlib import Path
|
||||
|
||||
|
||||
HEADER = 64
|
||||
PORT = 5050
|
||||
SERVER = socket.gethostbyname(socket.gethostname())
|
||||
ADDR = (SERVER, PORT)
|
||||
FORMAT = 'utf-8'
|
||||
DISCONNECT_MESSAGE = "!DISCONNECT"
|
||||
|
||||
server = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
|
||||
server.bind(ADDR)
|
||||
|
||||
def loadModel():
|
||||
|
||||
global INPUT_LAYER_INDEX
|
||||
global OUTPUT_LAYER_INDEX
|
||||
global MDATA_INPUT_INDEX
|
||||
global CLASSES
|
||||
|
||||
print('LOADING TF LITE MODEL...', end=' ')
|
||||
|
||||
# Load TFLite model and allocate tensors.
|
||||
myinterpreter = tflite.Interpreter(model_path='/home/pi/BirdNET-Pi/model/BirdNET_6K_GLOBAL_MODEL.tflite',num_threads=2)
|
||||
myinterpreter.allocate_tensors()
|
||||
|
||||
# Get input and output tensors.
|
||||
input_details = myinterpreter.get_input_details()
|
||||
output_details = myinterpreter.get_output_details()
|
||||
|
||||
# Get input tensor index
|
||||
INPUT_LAYER_INDEX = input_details[0]['index']
|
||||
MDATA_INPUT_INDEX = input_details[1]['index']
|
||||
OUTPUT_LAYER_INDEX = output_details[0]['index']
|
||||
|
||||
# Load labels
|
||||
CLASSES = []
|
||||
with open('/home/pi/BirdNET-Pi/model/labels.txt', 'r') as lfile:
|
||||
for line in lfile.readlines():
|
||||
CLASSES.append(line.replace('\n', ''))
|
||||
|
||||
print('DONE!')
|
||||
|
||||
return myinterpreter
|
||||
|
||||
def loadCustomSpeciesList(path):
|
||||
|
||||
slist = []
|
||||
if os.path.isfile(path):
|
||||
with open(path, 'r') as csfile:
|
||||
for line in csfile.readlines():
|
||||
slist.append(line.replace('\r', '').replace('\n', ''))
|
||||
|
||||
return slist
|
||||
|
||||
def splitSignal(sig, rate, overlap, seconds=3.0, minlen=1.5):
|
||||
|
||||
# Split signal with overlap
|
||||
sig_splits = []
|
||||
for i in range(0, len(sig), int((seconds - overlap) * rate)):
|
||||
split = sig[i:i + int(seconds * rate)]
|
||||
|
||||
# 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')
|
||||
|
||||
# Split audio into 3-second chunks
|
||||
chunks = splitSignal(sig, rate, overlap)
|
||||
|
||||
print('DONE! READ', str(len(chunks)), 'CHUNKS.')
|
||||
|
||||
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
|
||||
else:
|
||||
m[2] = -1
|
||||
|
||||
# Add binary mask
|
||||
mask = np.ones((3,))
|
||||
if m[0] == -1 or m[1] == -1:
|
||||
mask = np.zeros((3,))
|
||||
if m[2] == -1:
|
||||
mask[2] = 0.0
|
||||
|
||||
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.invoke()
|
||||
prediction = INTERPRETER.get_tensor(OUTPUT_LAYER_INDEX)[0]
|
||||
|
||||
# Apply custom sigmoid
|
||||
p_sigmoid = custom_sigmoid(prediction, sensitivity)
|
||||
|
||||
# Get label and scores for pooled predictions
|
||||
p_labels = dict(zip(CLASSES, p_sigmoid))
|
||||
|
||||
# Sort by score
|
||||
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 ['Human_Human', 'Non-bird_Non-bird', 'Noise_Noise']:
|
||||
p_sorted[i] = (p_sorted[i][0], 0.0)
|
||||
|
||||
# Only return first the top ten results
|
||||
return p_sorted[:10]
|
||||
|
||||
def analyzeAudioData(chunks, lat, lon, week, sensitivity, overlap,):
|
||||
global INTERPRETER
|
||||
|
||||
detections = {}
|
||||
start = time.time()
|
||||
print('ANALYZING AUDIO...', end=' ', flush=True)
|
||||
|
||||
# Convert and prepare metadata
|
||||
mdata = convertMetadata(np.array([lat, lon, week]))
|
||||
mdata = np.expand_dims(mdata, 0)
|
||||
|
||||
# Parse every chunk
|
||||
pred_start = 0.0
|
||||
for c in chunks:
|
||||
|
||||
# Prepare as input signal
|
||||
sig = np.expand_dims(c, 0)
|
||||
|
||||
# Make prediction
|
||||
p = predict([sig, mdata], sensitivity)
|
||||
|
||||
# Save result and timestamp
|
||||
pred_end = pred_start + 3.0
|
||||
detections[str(pred_start) + ';' + str(pred_end)] = p
|
||||
pred_start = pred_end - overlap
|
||||
|
||||
print('DONE! Time', int((time.time() - start) * 10) / 10.0, 'SECONDS')
|
||||
|
||||
return detections
|
||||
|
||||
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')
|
||||
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')
|
||||
rcnt += 1
|
||||
print('DONE! WROTE', rcnt, 'RESULTS.')
|
||||
return
|
||||
|
||||
def handle_client(conn, addr):
|
||||
global INCLUDE_LIST
|
||||
global EXCLUDE_LIST
|
||||
print(f"[NEW CONNECTION] {addr} connected.")
|
||||
|
||||
connected = True
|
||||
while connected:
|
||||
msg_length = conn.recv(HEADER).decode(FORMAT)
|
||||
if msg_length:
|
||||
msg_length = int(msg_length)
|
||||
msg = conn.recv(msg_length).decode(FORMAT)
|
||||
if msg == DISCONNECT_MESSAGE:
|
||||
connected = False
|
||||
else:
|
||||
#print(f"[{addr}] {msg}")
|
||||
|
||||
args = type('', (), {})()
|
||||
|
||||
args.i = '/home/pi/test.wav'
|
||||
args.o = '/home/pi/test.wav.csv'
|
||||
args.birdweather_id = '99999'
|
||||
args.include_list = 'null'
|
||||
args.exclude_list = 'null'
|
||||
args.overlap = 0.0
|
||||
args.week = -1
|
||||
args.sensitivity = 1.25
|
||||
args.min_conf = 0.70
|
||||
args.lat = -1
|
||||
args.lon = -1
|
||||
|
||||
|
||||
for line in msg.split('||'):
|
||||
inputvars = line.split('=')
|
||||
if inputvars[0] == 'i':
|
||||
args.i = inputvars[1]
|
||||
elif inputvars[0] == 'o':
|
||||
args.o = inputvars[1]
|
||||
elif inputvars[0] == 'birdweather_id':
|
||||
args.birdweather_id = inputvars[1]
|
||||
elif inputvars[0] == 'include_list':
|
||||
args.include_list = inputvars[1]
|
||||
elif inputvars[0] == 'exclude_list':
|
||||
args.exclude_list = inputvars[1]
|
||||
elif inputvars[0] == 'overlap':
|
||||
args.overlap = float(inputvars[1])
|
||||
elif inputvars[0] == 'week':
|
||||
args.week = int(inputvars[1])
|
||||
elif inputvars[0] == 'sensitivity':
|
||||
args.sensitivity = float(inputvars[1])
|
||||
elif inputvars[0] == 'min_conf':
|
||||
args.min_conf = float(inputvars[1])
|
||||
elif inputvars[0] == 'lat':
|
||||
args.lat = float(inputvars[1])
|
||||
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:
|
||||
EXCLUDE_LIST = []
|
||||
|
||||
birdweather_id = args.birdweather_id
|
||||
|
||||
# Read audio data
|
||||
audioData = readAudioData(args.i, args.overlap)
|
||||
|
||||
# Get Date/Time from filename in case Pi gets behind
|
||||
#now = datetime.now()
|
||||
full_file_name = args.i
|
||||
print('FULL FILENAME: -' + full_file_name + '-')
|
||||
file_name = Path(full_file_name).stem
|
||||
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')
|
||||
#print('Date:', date_time_obj.date())
|
||||
#print('Time:', date_time_obj.time())
|
||||
print('Date-time:', date_time_obj)
|
||||
now = date_time_obj
|
||||
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))
|
||||
|
||||
# Process audio data and get detections
|
||||
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:
|
||||
print("\n", detections[i][0],"\n")
|
||||
myReturn += str(detections[i][0]) + '||'
|
||||
|
||||
|
||||
|
||||
|
||||
with open('/home/pi/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(sensitivity) +';' + str(args.overlap) + '\n')
|
||||
|
||||
def insert_variables_into_table(Date, Time, Sci_Name, Com_Name, Confidence, Lat, Lon, Cutoff, Week, Sens, Overlap):
|
||||
try:
|
||||
connection = mysql.connector.connect(host='localhost',
|
||||
database='birds',
|
||||
user='birder',
|
||||
password='databasepassword')
|
||||
cursor = connection.cursor()
|
||||
mySql_insert_query = """INSERT INTO detections (Date, Time, Sci_Name, Com_Name, Confidence, Lat, Lon, Cutoff, Week, Sens, Overlap)
|
||||
VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s) """
|
||||
|
||||
record = (Date, Time, Sci_Name, Com_Name, Confidence, Lat, Lon, Cutoff, Week, Sens, Overlap)
|
||||
|
||||
cursor.execute(mySql_insert_query, record)
|
||||
connection.commit()
|
||||
print("Record inserted successfully into detections table")
|
||||
|
||||
|
||||
except mysql.connector.Error as error:
|
||||
print("Failed to insert record into detections table {}".format(error))
|
||||
|
||||
finally:
|
||||
if connection.is_connected():
|
||||
connection.close()
|
||||
print("MySQL connection is closed")
|
||||
|
||||
species = entry[0]
|
||||
sci_name,com_name = species.split('_')
|
||||
insert_variables_into_table(str(current_date), str(current_time), sci_name, com_name, \
|
||||
str(entry[1]), str(args.lat), str(args.lon), str(min_conf), str(week), \
|
||||
str(args.sensitivity), str(args.overlap))
|
||||
|
||||
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) + '\n')
|
||||
|
||||
if birdweather_id != "99999":
|
||||
|
||||
if soundscape_uploaded is False:
|
||||
# POST soundscape to server
|
||||
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)
|
||||
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"
|
||||
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) + ","
|
||||
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_algorithm = "\"algorithm\": " + "\"alpha\"" + ","
|
||||
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
|
||||
print(post_json)
|
||||
response = requests.post(detection_url, json=json.loads(post_json))
|
||||
print("Detection POST Response Status - ", response.status_code)
|
||||
|
||||
|
||||
conn.send("Msg received".encode(FORMAT))
|
||||
|
||||
#time.sleep(3)
|
||||
|
||||
conn.close()
|
||||
|
||||
def start():
|
||||
# Load model
|
||||
global INTERPRETER, INCLUDE_LIST, EXCLUDE_LIST
|
||||
INTERPRETER = loadModel()
|
||||
server.listen()
|
||||
print(f"[LISTENING] Server is listening on {SERVER}")
|
||||
while True:
|
||||
conn, addr = server.accept()
|
||||
thread = threading.Thread(target=handle_client, args=(conn, addr))
|
||||
thread.start()
|
||||
print(f"[ACTIVE CONNECTIONS] {threading.activeCount() - 1}")
|
||||
|
||||
|
||||
print("[STARTING] server is starting...")
|
||||
start()
|
||||
@@ -5,9 +5,9 @@ source /etc/birdnet/birdnet.conf
|
||||
mysql -e "
|
||||
SET PASSWORD FOR 'birder'@'localhost' = PASSWORD('${DB_PWD}');
|
||||
FLUSH PRIVILEGES";
|
||||
sudo -u ${USER} git -C /home/pi/BirdNET-Pi checkout -f scripts/analyze.py
|
||||
sudo -u ${USER} git -C /home/pi/BirdNET-Pi checkout -f scripts/server.py
|
||||
sudo -u ${USER} git -C /home/pi/BirdNET-Pi checkout -f scripts/viewdb.php
|
||||
sudo -u ${USER} sed -i "s/databasepassword/${DB_PWD}/g" /home/pi/BirdNET-Pi/scripts/analyze.py
|
||||
sudo -u ${USER} sed -i "s/databasepassword/${DB_PWD}/g" /home/pi/BirdNET-Pi/scripts/server.py
|
||||
sed -i "s/mysqli.default_host =.*/mysqli.default_host = localhost/g" /etc/php/7.4/fpm/php.ini
|
||||
sed -i "s/mysqli.default_user =.*/mysqli.default_user = birder/g" /etc/php/7.4/fpm/php.ini
|
||||
sed -i "s/mysqli.default_pw =.*/mysqli.default_pw = ${DB_PWD}/g" /etc/php/7.4/fpm/php.ini
|
||||
|
||||
@@ -43,9 +43,10 @@ install_birdnet_analysis() {
|
||||
cat << EOF > /etc/systemd/system/birdnet_analysis.service
|
||||
[Unit]
|
||||
Description=BirdNET Analysis
|
||||
After=birdnet_server.service
|
||||
Requires=birdnet_server.service
|
||||
[Service]
|
||||
Restart=always
|
||||
RuntimeMaxSec=10800
|
||||
Type=simple
|
||||
RestartSec=2
|
||||
User=${USER}
|
||||
@@ -56,6 +57,25 @@ EOF
|
||||
systemctl enable birdnet_analysis.service
|
||||
}
|
||||
|
||||
install_birdnet_server() {
|
||||
echo "Installing the birdnet_server.service"
|
||||
cat << EOF > /etc/systemd/system/birdnet_server.service
|
||||
[Unit]
|
||||
Description=BirdNET Analysis Server
|
||||
Before=birdnet_analysis.service
|
||||
[Service]
|
||||
Restart=always
|
||||
Type=simple
|
||||
RestartSec=2
|
||||
User=${USER}
|
||||
ExecStart=/usr/local/bin/server.py
|
||||
[Install]
|
||||
WantedBy=multi-user.target
|
||||
EOF
|
||||
systemctl enable birdnet_server.service
|
||||
}
|
||||
|
||||
|
||||
install_extraction_service() {
|
||||
echo "Installing the extraction.service and extraction.timer"
|
||||
cat << EOF > /etc/systemd/system/extraction.service
|
||||
@@ -386,7 +406,7 @@ RestartSec=3
|
||||
Type=simple
|
||||
User=${USER}
|
||||
Environment=TERM=xterm-256color
|
||||
ExecStart=/usr/local/bin/gotty -p 8080 --title-format "BirdNET-Pi Log" journalctl -o cat -fu birdnet_analysis.service
|
||||
ExecStart=/usr/local/bin/gotty -p 8080 --title-format "BirdNET-Pi Log" journalctl -o cat -fu birdnet_server.service
|
||||
|
||||
[Install]
|
||||
WantedBy=multi-user.target
|
||||
@@ -513,6 +533,7 @@ install_cleanup_cron() {
|
||||
install_selected_services() {
|
||||
install_scripts
|
||||
install_birdnet_analysis
|
||||
install_birdnet_server
|
||||
|
||||
if [[ "${DO_EXTRACTIONS}" =~ [Yy] ]];then
|
||||
install_extraction_service
|
||||
|
||||
Reference in New Issue
Block a user