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Update DOCS.md
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@@ -181,3 +181,284 @@ amixer -c 0 cset numid=52 'Locked' # 'Sync Status'
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echo "Mono optimization applied. Only using primary input and balanced outputs."
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echo "Mono optimization applied. Only using primary input and balanced outputs."
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```
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```
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# Autogain script for microphone
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```python
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#!/usr/bin/env python3
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"""
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Microphone Gain Adjustment Script
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This script captures audio from an RTSP stream, processes it to calculate the RMS
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within the 2000-4000 Hz frequency band, and adjusts the microphone gain based on
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predefined noise thresholds and trends.
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Dependencies:
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- numpy
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- scipy
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- ffmpeg (installed and accessible in PATH)
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- amixer (for microphone gain control)
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Author: OpenAI ChatGPT
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Date: 2024-04-27
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"""
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import subprocess
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import numpy as np
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from scipy.signal import butter, sosfilt
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import time
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import re
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# ---------------------------- Configuration ----------------------------
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# Microphone Settings
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MICROPHONE_NAME = "Line In 1 Gain" # Adjust to match your microphone's control name
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MIN_GAIN_DB = 20 # Minimum gain in dB
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MAX_GAIN_DB = 50 # Maximum gain in dB
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DECREASE_GAIN_STEP_DB = 1 # Gain decrease step in dB
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INCREASE_GAIN_STEP_DB = 5 # Gain increase step in dB
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# Noise Thresholds
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NOISE_THRESHOLD_HIGH = 0.0035 # Upper threshold for noise RMS amplitude
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NOISE_THRESHOLD_LOW = 0.00035 # Lower threshold for noise RMS amplitude
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# Trend Detection
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TREND_COUNT_THRESHOLD = 1 # Number of consecutive trends needed to adjust gain
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# RTSP Stream URL
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RTSP_URL = "rtsp://192.168.178.124:8554/birdmic" # Replace with your RTSP stream URL
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# Debug Mode (1 for enabled, 0 for disabled)
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DEBUG = 1
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# -----------------------------------------------------------------------
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def debug(msg):
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"""
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Prints debug messages if DEBUG mode is enabled.
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:param msg: The debug message to print.
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"""
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if DEBUG:
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print(f"[DEBUG] {msg}")
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def get_gain_db(mic_name):
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"""
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Retrieves the current gain setting of the specified microphone using amixer.
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:param mic_name: The name of the microphone control in amixer.
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:return: The current gain in dB as a float, or None if retrieval fails.
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"""
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cmd = ['amixer', 'sget', mic_name]
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try:
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output = subprocess.check_output(cmd, stderr=subprocess.STDOUT).decode()
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# Regex to find patterns like [30.00dB]
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match = re.search(r'\[(-?\d+(\.\d+)?)dB\]', output)
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if match:
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gain_db = float(match.group(1))
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debug(f"Retrieved gain: {gain_db} dB")
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return gain_db
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else:
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debug("No gain information found in amixer output.")
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return None
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except subprocess.CalledProcessError as e:
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debug(f"amixer sget failed: {e}")
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return None
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def set_gain_db(mic_name, gain_db):
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"""
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Sets the gain of the specified microphone using amixer.
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:param mic_name: The name of the microphone control in amixer.
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:param gain_db: The desired gain in dB.
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:return: True if the gain was set successfully, False otherwise.
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"""
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cmd = ['amixer', 'sset', mic_name, f'{gain_db}dB']
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try:
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subprocess.check_call(cmd, stderr=subprocess.STDOUT)
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debug(f"Set gain to: {gain_db} dB")
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return True
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except subprocess.CalledProcessError as e:
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debug(f"amixer sset failed: {e}")
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return False
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def calculate_noise_rms(rtsp_url, bandpass_sos, num_bins=5):
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"""
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Captures audio from an RTSP stream, applies a bandpass filter, divides the
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audio into segments, and calculates the RMS of the quietest segment.
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:param rtsp_url: The RTSP stream URL.
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:param bandpass_sos: Precomputed bandpass filter coefficients (Second-Order Sections).
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:param num_bins: Number of segments to divide the audio into.
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:return: The RMS amplitude of the quietest segment as a float, or None on failure.
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"""
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cmd = [
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'ffmpeg',
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'-loglevel', 'error',
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'-rtsp_transport', 'tcp',
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'-i', rtsp_url,
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'-vn',
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'-f', 's16le',
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'-acodec', 'pcm_s16le',
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'-ar', '32000',
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'-ac', '1',
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'-t', '5',
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'-'
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]
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try:
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debug(f"Starting audio capture from {rtsp_url}")
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process = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
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stdout, stderr = process.communicate()
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if process.returncode != 0:
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debug(f"ffmpeg failed with error: {stderr.decode()}")
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return None
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# Convert raw PCM data to numpy array
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audio = np.frombuffer(stdout, dtype=np.int16).astype(np.float32) / 32768.0
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debug(f"Captured {len(audio)} samples from audio stream.")
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if len(audio) == 0:
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debug("No audio data captured.")
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return None
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# Apply bandpass filter
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filtered = sosfilt(bandpass_sos, audio)
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debug("Applied bandpass filter to audio data.")
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# Divide into num_bins
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total_samples = len(filtered)
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bin_size = total_samples // num_bins
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if bin_size == 0:
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debug("Bin size is 0; insufficient audio data.")
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return 0.0
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trimmed_length = bin_size * num_bins
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trimmed_filtered = filtered[:trimmed_length]
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segments = trimmed_filtered.reshape(num_bins, bin_size)
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debug(f"Divided audio into {num_bins} bins of {bin_size} samples each.")
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# Calculate RMS for each segment
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rms_values = np.sqrt(np.mean(segments ** 2, axis=1))
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debug(f"Calculated RMS values for each segment: {rms_values}")
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# Return the minimum RMS value
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min_rms = rms_values.min()
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debug(f"Minimum RMS value among segments: {min_rms}")
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return min_rms
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except Exception as e:
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debug(f"Exception during noise RMS calculation: {e}")
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return None
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def main():
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"""
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Main loop that continuously monitors background noise and adjusts microphone gain.
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"""
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TREND_COUNT = 0
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PREVIOUS_TREND = 0
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# Precompute the bandpass filter coefficients
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LOWCUT = 2000 # Lower frequency bound in Hz
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HIGHCUT = 8000 # Upper frequency bound in Hz
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FILTER_ORDER = 5 # Order of the Butterworth filter
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sos = butter(FILTER_ORDER, [LOWCUT, HIGHCUT], btype='band', fs=44100, output='sos')
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debug("Precomputed Butterworth bandpass filter coefficients.")
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# Set the microphone gain to the maximum gain at the start
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success = set_gain_db(MICROPHONE_NAME, MAX_GAIN_DB)
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if success:
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print(f"Microphone gain set to {MAX_GAIN_DB} dB at start.")
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else:
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print("Failed to set microphone gain at start. Exiting.")
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return
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while True:
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min_rms = calculate_noise_rms(RTSP_URL, sos, num_bins=5)
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if min_rms is None:
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print("Failed to compute noise RMS. Retrying in 1 minute...")
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time.sleep(60)
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continue
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if not isinstance(min_rms, (float, int)):
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print(f"Invalid noise RMS output detected: {min_rms}. Retrying in 1 minute...")
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time.sleep(60)
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continue
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# Print the final converted RMS amplitude (only once)
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print(f"Converted RMS Amplitude: {min_rms}")
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debug(f"Current background noise (RMS amplitude): {min_rms}")
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# Determine the noise trend
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if min_rms > NOISE_THRESHOLD_HIGH:
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CURRENT_TREND = 1
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elif min_rms < NOISE_THRESHOLD_LOW:
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CURRENT_TREND = -1
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else:
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CURRENT_TREND = 0
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debug(f"Current trend: {CURRENT_TREND}")
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if CURRENT_TREND != 0:
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if CURRENT_TREND == PREVIOUS_TREND:
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TREND_COUNT += 1
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else:
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TREND_COUNT = 1
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PREVIOUS_TREND = CURRENT_TREND
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else:
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TREND_COUNT = 0
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debug(f"Trend count: {TREND_COUNT}")
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CURRENT_GAIN_DB = get_gain_db(MICROPHONE_NAME)
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if CURRENT_GAIN_DB is None:
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print("Failed to get current gain level. Retrying in 1 minute...")
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time.sleep(60)
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continue
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debug(f"Current gain: {CURRENT_GAIN_DB} dB")
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if TREND_COUNT >= TREND_COUNT_THRESHOLD:
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if CURRENT_TREND == 1:
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# Decrease gain by 1 dB
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NEW_GAIN_DB = CURRENT_GAIN_DB - DECREASE_GAIN_STEP_DB
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if NEW_GAIN_DB < MIN_GAIN_DB:
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NEW_GAIN_DB = MIN_GAIN_DB
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success = set_gain_db(MICROPHONE_NAME, NEW_GAIN_DB)
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if success:
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print(f"Decreased gain to {NEW_GAIN_DB} dB")
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debug(f"Gain adjusted to {NEW_GAIN_DB} dB")
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else:
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print("Failed to set new gain.")
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elif CURRENT_TREND == -1:
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# Increase gain by 5 dB
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NEW_GAIN_DB = CURRENT_GAIN_DB + INCREASE_GAIN_STEP_DB
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if NEW_GAIN_DB > MAX_GAIN_DB:
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NEW_GAIN_DB = MAX_GAIN_DB
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success = set_gain_db(MICROPHONE_NAME, NEW_GAIN_DB)
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if success:
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print(f"Increased gain to {NEW_GAIN_DB} dB")
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debug(f"Gain adjusted to {NEW_GAIN_DB} dB")
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else:
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print("Failed to set new gain.")
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TREND_COUNT = 0
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else:
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debug("No gain adjustment needed.")
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# Sleep for 1 minute before the next iteration
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time.sleep(60)
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if __name__ == "__main__":
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main()
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```
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