From 96a26562a3dd93dae98aa560469648e0bf152a35 Mon Sep 17 00:00:00 2001 From: Sg4Dylan Date: Sun, 26 Feb 2017 17:23:32 +0800 Subject: [PATCH 01/14] init ver Alpha.1 --- EmiyaEngine.py | 520 ++++++++++++++++-------------------------- GUI_EmiyaEngine.py | 557 --------------------------------------------- README.md | 73 ++---- 3 files changed, 212 insertions(+), 938 deletions(-) delete mode 100644 GUI_EmiyaEngine.py diff --git a/EmiyaEngine.py b/EmiyaEngine.py index 7e67a88..18042b6 100644 --- a/EmiyaEngine.py +++ b/EmiyaEngine.py @@ -2,340 +2,210 @@ # -*- coding: utf-8 -*- # Emiya Engine -# Version: Alpha.0 Rev.3 +# Version: Alpha.1 Rev.0 # Author: Sg4Dylan - -# Created: 02/07/2017 +# Created: 02/26/2017 # 真正重要的東西,只用眼睛是看不見的, # 只要蘊藏著想成為真物的意志,偽物就比真物還要來得真實 -import os -import argparse -import datetime -import uuid -import random -import math + import numpy as np import scipy import librosa import resampy -import logging -from colorama import Fore, Back, init - -logging.basicConfig( - level=logging.DEBUG, - format='%(asctime)s [line:%(lineno)d] \ - %(levelname)s %(message)s', - datefmt='%a, %d %b %Y %H:%M:%S', - filename='EmiyaEngine.log', - filemode='w+' -) -logger = logging.getLogger("EmiyaLog") -# console = logging.StreamHandler() -# console.setLevel(logging.INFO) -# logger.addHandler(console) - - -class EmiyaEngineCore: - - ReadyFilePath = '' # 输入文件名 - BeforeSignal = '' # 输入原始信号 - BeforeSignalSR = 0 # 原始信号采样 - MidSignal = '' # 重采样到96K信号 - MidSignalSR = 0 # 96K - AfterSignalLeft = '' # 处理后的左信号 - AfterSignalRight = '' # 处理后的右信号 - AfterSignal = '' # 处理后的信号 - AfterSignalSR = 0 # 处理后的采样率 - SplitSize = 0 # 倒腾区大小 - AnalysisWindow = False # 分析接续点用的单边FFT是否加窗 - MidSRCFalse = False # SRC开关, 为True时就会取消掉SRC步骤 - MidPrint = False # 打印细节日志开关 - MidPrintProgress = True # 打印进度信息 - - def __init__(self, _InputFilePath, _DebugSwitch, _SplitSize, _WindowSwitch): - # 输入样本: - # 信号被加载为ndarray结构,有两个声道各以一维array形式存在 - self.ReadyFilePath = _InputFilePath - self.SplitSize = _SplitSize - if _WindowSwitch == 1: - self.AnalysisWindow = True - if _DebugSwitch == 0: - MidPrintProgress = False - elif _DebugSwitch == 1: - MidPrintProgress = True - elif _DebugSwitch == 2: - MidPrint = True - else: - pass - self.LoadFile() - self.MidUpSRC() - self.ProcessCore() - - def LoadFile(self): - self.BeforeSignal, self.BeforeSignalSR = librosa.load( - self.ReadyFilePath, sr=None, mono=False) - self.AfterSignalLeft = np.array([()]) - self.AfterSignalRight = np.array([()]) +import multiprocessing + + +class EmiyaEngine: + + # 输入参数 + input_file_path = '' + input_sr = 0 + input_signal_array = '' + # 中间处理参数 + cpu_thread = 0 + mid_signal_larray = '' + mid_signal_rarray = '' + mid_signal_carray = '' + mid_process_ponit = 32 + mid_src_point = 2048 + # 输出用参数 + output_file_path = '' + output_sr = 0 + split_size = 500 + + def __init__(self, input=None, output=None, output_sr=96000, split_size=500): + # 导入参数 + if not input or not output: + print("Missing parameters.") + return + self.input_file_path = input + self.output_file_path = output + self.output_sr = output_sr + self.split_size = split_size + # 初始化程序 + self.init_engine() + # 启动处理 + self.process_leader() + + def init_engine(self): + # 将输入文件转为 numpy 数组 + self.input_signal_array, self.input_sr = librosa.load( + self.input_file_path, sr=None, mono=False) print("Load signal complete. ChannelCount: %s SampleRate: %s Hz" % ( - str(len(self.BeforeSignal)), str(self.BeforeSignalSR))) - logger.info("Load signal complete. ChannelCount: %s SampleRate: %s Hz" % ( - str(len(self.BeforeSignal)), str(self.BeforeSignalSR))) - - def MidUpSRC(self): - # 重采样loss样本到96K - print("Please wait for SRC.") - logger.info("Please wait for SRC.") - self.MidSignalSR = 96000 - self.AfterSignalSR = self.MidSignalSR - if self.MidSRCFalse: - self.MidSignal = self.BeforeSignal - else: - self.MidSignal = resampy.resample( - self.BeforeSignal, self.BeforeSignalSR, self.MidSignalSR, filter='kaiser_best') - print("Signal SRC complete.") - logging.info("Signal SRC complete.") - - def MidFindThresholdPoint(self, _MidFFTResultSingle, _FFTPointCount): - # 鉴定频谱基本参数 - _MidAmpData = abs(_MidFFTResultSingle[range(_FFTPointCount // 2)]) - # Step0. 找出基波幅度 - _MidBaseFreqAmp = _MidAmpData.max() - if self.MidPrint: - print("Signal max AMP -> %s" % _MidBaseFreqAmp) - logger.debug("Signal max AMP -> %s" % _MidBaseFreqAmp) - # Step1. 找出接续的阈值 - _MidThresholdHit = 1.0e-11 # 方差判定阈值 - _MidThresholdPoint = 0 # 最后的阈值点 - _MidFindRange = int((_FFTPointCount / 2) - 1) # 搜索的范围 - _MidStartFindPos = round(2000 / (self.BeforeSignalSR / (_FFTPointCount / 2))) # 从2K频点附近开始寻找,加快速度 - _MidStartFlag = True # 循环用的启动Flag - _MidLoopCount = 0 # 循环计数器 - _MidLegalFreq = (self.BeforeSignalSR / 2) - 500 # 判定结果合法的阈值频率 - _MidForwardFreq = 3000 # 前向修正频率 - _MidOrderFreq = (self.BeforeSignalSR / 2) - 6000 # 钦定频率 - # Rev.1: 检查接续点是否符合常理 - while _MidStartFlag or _MidThresholdPoint > round(_MidLegalFreq / (self.BeforeSignalSR / (_FFTPointCount / 2))): - _MidStartFlag = False - if (_MidThresholdPoint * (self.BeforeSignalSR / (_FFTPointCount / 2))) > int(self.BeforeSignalSR / 2): - _MidThresholdHit *= 2 - for i in range(_MidStartFindPos, _MidFindRange): - if i + 5 > _MidFindRange: - break - # 计算连续五个采样*3 的方差,与阈值比较,判断频谱消失的位置 - if np.var(_MidAmpData[i:i + 4]) < _MidThresholdHit and \ - np.var(_MidAmpData[i + 1:i + 5]) < _MidThresholdHit: - # 定位到当前位置的前500Hz位置 - _MidThresholdPoint = i - round(_MidForwardFreq / (self.BeforeSignalSR / (_FFTPointCount / 2))) - break - # 错误超过5把就强行钦定频率 - _MidLoopCount += 1 - if _MidLoopCount > 5: - _MidThresholdPoint = round( - _MidOrderFreq / (self.BeforeSignalSR / (_FFTPointCount / 2))) - break - # 打印函数返回信息 - if self.MidPrint: - print("Signal threshold point -> %s @ %sHz Max Amp -> %s" % (_MidThresholdPoint, - _MidThresholdPoint * - (self.BeforeSignalSR / (_MidFindRange + 1)), - _MidBaseFreqAmp)) - logger.debug("Signal threshold point -> %s @ %sHz Max Amp -> %s" % (_MidThresholdPoint, - _MidThresholdPoint * - (self.BeforeSignalSR / (_MidFindRange + 1)), - _MidBaseFreqAmp)) - # _MidThresholdPoint = round(21000/(self.BeforeSignalSR/(_FFTPointCount/2))) - return _MidBaseFreqAmp, _MidThresholdPoint - - def MidInsertJitter(self, _MidFFTResultDouble, _FFTPointCount, _MidThresholdPoint, _MidBaseFreqAmp): - # 构造抖动 - if _MidThresholdPoint <= 0: - return _MidFFTResultDouble - for i in range(_MidThresholdPoint, _FFTPointCount - _MidThresholdPoint): - # Rev.0: 调整生成概率,频率越高概率越低 - # Rev.1: 加入幅值判定,幅度越大概率越大 - _GenPossible = abs((_FFTPointCount / 2) - i) / ((_FFTPointCount / - 2) - _MidThresholdPoint) * (_MidBaseFreqAmp / 0.22) - if random.randint(0, 1000000) < 800000 * _GenPossible: # 0<=x<=10 - _MidRealValue = abs(_MidFFTResultDouble.real[i]) - _BaseJitterMin = _MidRealValue * 0.5 * (1 - _GenPossible) - _BaseJitterMax = _MidRealValue * 6 * _GenPossible - _AmpJitterMin = _MidBaseFreqAmp * _MidRealValue * 0.5 - _AmpJitterMax = _MidBaseFreqAmp * _MidRealValue * 2 - _AmpJitterPrefix = - \ - 1 if random.randint(0, 100000) < 50000 else 1 - _MiditterPrefix = - \ - 1 if random.randint(0, 100000) < 50000 else 1 - _MidDeltaJitterValue = random.uniform( - _BaseJitterMin, _BaseJitterMax) + _AmpJitterPrefix * random.uniform(_AmpJitterMin, _AmpJitterMax) - _MidFFTResultDouble.real[ - i] += _MiditterPrefix * _MidDeltaJitterValue - return _MidFFTResultDouble - - def FinSaveFile(self): - init(autoreset=True) - OutputFilePath = os.path.abspath( - os.path.join(self.ReadyFilePath, os.pardir)) + "\\" - OutputFileName = OutputFilePath + 'Output_%s.wav' % uuid.uuid4().hex - librosa.output.write_wav( - OutputFileName, self.AfterSignal, self.AfterSignalSR) - print(Back.GREEN + Fore.WHITE + "SAVE DONE" + - Back.BLACK + " Output path -> " + OutputFileName) - logger.info(Back.GREEN + Fore.WHITE + "SAVE DONE" + - Back.BLACK + " Output path -> " + OutputFileName) - - def ProcessCore(self): - # 初始化彩色命令行 - init(autoreset=True) - # 两个声道 - for ChannelIndex in range(2): - # 记录开始时间 - _MidStartTime = datetime.datetime.now() - # 信号总长度 - _MidSignalLength = len(self.MidSignal[ChannelIndex]) - # FFT分割数量 - _FFTPointCount = 1024 # 至少2048点,避免计算错误 - _MidDivCount = math.floor(_MidSignalLength / _FFTPointCount) - # 实际重叠操作数量 = FFT分割数量 * 分块次数 - _EachLength = 512 - # 补偿标记, 标记有效时, 说明已经到了序列尾部, 因停止继续循环运算 - SuffixFlag = False - SuffixLength = 0 - # Rev.2: 加入临时数组加速Append, 临时数组每Append操作设定次数就倒腾一次 - _TempArrayLeft = np.array([()]) - _TempArrayRight = np.array([()]) - _TempAppendCount = 0 - # 除了最后一块,每一块都是取计算结果时域的前512点 - for SamplePointIndex in range(_MidDivCount + 1): - StartPos = SamplePointIndex * _FFTPointCount - EndPos = SamplePointIndex * _FFTPointCount + _FFTPointCount - _EachPieceLeft = np.array([()]) - _EachPieceRight = np.array([()]) - for EachFourPiece in range(int(_FFTPointCount / _EachLength)): - StartPos += EachFourPiece * _EachLength - EndPos += EachFourPiece * _EachLength - # 若超出范围, 需将本次计算完整保留接续有效部分(除去补零部分) - if EndPos > _MidSignalLength: - EndPos = _MidSignalLength - SuffixFlag = True - _TempSignal = self.MidSignal[ChannelIndex][StartPos:EndPos] - # 不足FFT点数的补零 - while len(_TempSignal) != _FFTPointCount: - _TempSignal = np.append(_TempSignal, [0]) - SuffixLength += 1 - # 执行FFT运算, 单边谱用于分析, 双边谱用于处理 - _MidFFTResultDouble = np.fft.fft( - _TempSignal, _FFTPointCount) / (_FFTPointCount) - if self.AnalysisWindow: - _TempSignal *= scipy.signal.hann(_FFTPointCount, sym=0) - _MidFFTResultSingle = np.fft.fft( - _TempSignal, _FFTPointCount) / (_FFTPointCount / 2) - # 获取当前分段最大振幅, 处理阈值点 - _MidBaseFreqAmp, _MidThresholdPoint = self.MidFindThresholdPoint( - _MidFFTResultSingle, _FFTPointCount) - # 构造抖动到当前FFT实际值上 - _MidFFTAfterJitter = self.MidInsertJitter( - _MidFFTResultDouble, _FFTPointCount, _MidThresholdPoint, _MidBaseFreqAmp) - # 逆变换IFFT - _MidTimerDomSignal = np.fft.ifft( - _MidFFTAfterJitter, n=_FFTPointCount) - # 接续到新信号上 - _AppendLength = _EachLength - if SuffixFlag: - _AppendLength = _FFTPointCount - SuffixLength - _MidAppendSignal = _MidTimerDomSignal[0:_AppendLength] - if self.MidPrint: - print("Per each length -> %s" % len(_MidAppendSignal)) - logger.debug("Per each length -> %s" % len(_MidAppendSignal)) - if ChannelIndex == 0: - _EachPieceLeft = np.append( - _EachPieceLeft, _MidAppendSignal) - else: - _EachPieceRight = np.append( - _EachPieceRight, _MidAppendSignal) - # 及时跳出尾部 - if SuffixFlag: - break - # 先倒腾到临时数组,倒腾500次给放回大数组 - if _TempAppendCount < self.SplitSize and not SuffixFlag: - # 已消耗时间 - _MidUsedTime = datetime.datetime.now() - _MidStartTime - # 估算剩余时间 - _MidEtaTime = ((datetime.datetime.now() - _MidStartTime) / - ((SamplePointIndex + 1) / _MidDivCount)) - _MidUsedTime - # 构造显示文本 - if ChannelIndex == 0: - _TempArrayLeft = np.append( - _TempArrayLeft, _EachPieceLeft) - if self.MidPrintProgress: - print("Left channel progress rate -> " + Fore.CYAN + str(SamplePointIndex) + " / " + - str(_MidDivCount - 1) + Fore.WHITE + " TIME USED -> " + Fore.YELLOW + - str(_MidUsedTime) + Fore.WHITE + " ETA -> " + Fore.GREEN + str(_MidEtaTime)) - logger.info("Left channel progress rate -> " + str(SamplePointIndex) + " / " + - str(_MidDivCount - 1) + " TIME USED -> " + - str(_MidUsedTime) + " ETA -> " + str(_MidEtaTime)) - else: - _TempArrayRight = np.append( - _TempArrayRight, _EachPieceRight) - if self.MidPrintProgress: - print("Right channel progress rate -> " + Fore.CYAN + str(SamplePointIndex) + " / " + - str(_MidDivCount - 1) + Fore.WHITE + " TIME USED -> " + Fore.YELLOW + - str(_MidUsedTime) + Fore.WHITE + " ETA -> " + Fore.GREEN + str(_MidEtaTime)) - logger.info("Right channel progress rate -> " + str(SamplePointIndex) + " / " + - str(_MidDivCount - 1) + " TIME USED -> " + - str(_MidUsedTime) + " ETA -> " + str(_MidEtaTime)) - else: - _TempAppendCount = 0 - if ChannelIndex == 0: - self.AfterSignalLeft = np.append(self.AfterSignalLeft, _TempArrayLeft) - _TempArrayLeft = np.array([()]) - else: - self.AfterSignalRight = np.append(self.AfterSignalRight, _TempArrayRight) - _TempArrayRight = np.array([()]) - # 倒腾计数器 - _TempAppendCount += 1 - if SuffixFlag: - break - self.AfterSignal = np.array([self.AfterSignalLeft.real, self.AfterSignalRight.real]) - self.FinSaveFile() - - -def Main(_input, _debug, _size, _window): - Processor = EmiyaEngineCore(_input, _debug, _size, _window) + str(len(self.input_signal_array)), str(self.input_sr))) + # 读取 CPU 线程数 + self.cpu_thread = multiprocessing.cpu_count() + + def process_leader(self): + # 左右声道 + for channel_index in range(2): + # 生成进程池 + pool = multiprocessing.Pool(processes=self.cpu_thread) + # 初始化结果字典 + result_dict = {} + # 分割时间域 + each_piece_length = round(len(self.input_signal_array[channel_index]) / self.cpu_thread) + for i in range(self.cpu_thread): + # 计算分发分片的起始位置 + piece_start_pos = i * each_piece_length + piece_end_pos = (i + 1) * each_piece_length + if piece_end_pos > len(self.input_signal_array[channel_index]): + piece_end_pos = len(self.input_signal_array[channel_index]) + # 生成分片 + process_piece = self.input_signal_array[channel_index][piece_start_pos:piece_end_pos] + # 下发分片 + result_dict[i] = pool.apply_async(self.process_core, (process_piece, i, )) + pool.close() + pool.join() + # 拼合分片 + # 接下来处理这里的同步拼接问题 + temp_array = np.array([()]) + for i in range(self.cpu_thread): + temp_array = np.append(result_dict[i].get(), temp_array) + if channel_index == 0: + self.mid_signal_larray = temp_array + else: + self.mid_signal_rarray = temp_array + self.mid_signal_carray = np.array([self.mid_signal_larray, self.mid_signal_rarray]) + self.save_file() + + def process_core(self, signal_piece, index): + print("Entering process Index %s" % index) + print(len(signal_piece)) + return signal_piece + + def save_file(self): + librosa.output.write_wav(self.output_file_path, self.mid_signal_carray, self.input_sr) if __name__ == "__main__": - parser = argparse.ArgumentParser(formatter_class=argparse.RawTextHelpFormatter, - description='Emiya Engine\n' - 'Version: Alpha.0 Rev.2\n' - 'Author: Sg4Dylan - \n' - '真正重要的東西, 只用眼睛是看不見的, \n' - '只要蘊藏著想成為真物的意志, 偽物就比真物還要來得真實.') - parser.add_argument('-i', '--input', help='待处理文件的绝对路径, 同一路径可直接输入文件名. 例如: \n' - 'Music_ready_test.mp3') - parser.add_argument('-d', '--debug', help='调试等级设定. 默认 1 级. \n' - '设置为 0 时, 只显示任务起始日志; \n' - '设置为 1 时, 额外显示进度日志; \n' - '设置为 2 时, 额外显示处理细节日志') - parser.add_argument('-s', '--size', help='倒腾区大小. 默认 500. \n' - '使用倒腾区是因为 numpy 做大数组 append 速度远低于小数组, \n' - '故加入小数组多倒腾一手, 这个参数就是小数组的尺寸.') - parser.add_argument('-w', '--window', help='分析用汉宁Hann双余弦窗启用开关. 默认不使用.\n' - '输入 0 代表不使用, 1 代表使用.') - - args = parser.parse_args() - _input = args.input - _debug = args.debug - _size = args.size - _window = args.window - - if not _input: - print("缺少输入文件参数,请使用 --help 参考!") - exit(1) - if not _debug: - _debug = 1 - if not _size: - _size = 500 - if not _window: - _window = 0 - - Main(_input, _debug, _size, _window) + multiprocessing.freeze_support() + EmiyaEngine("lossless_short.wav","lossless_test.wav") + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/GUI_EmiyaEngine.py b/GUI_EmiyaEngine.py deleted file mode 100644 index c818ef4..0000000 --- a/GUI_EmiyaEngine.py +++ /dev/null @@ -1,557 +0,0 @@ -# -*- coding: utf-8 -*- - -import os -import argparse -import datetime -import uuid -import random -import math -import numpy as np -import scipy -import librosa -import resampy -import logging -from colorama import Fore, Back, init -from PyQt5 import QtCore, QtGui, QtWidgets - -logging.basicConfig( - level=logging.DEBUG, - format='%(asctime)s [line:%(lineno)d] \ - %(levelname)s %(message)s', - datefmt='%a, %d %b %Y %H:%M:%S', - filename='EmiyaEngineGUI.log', - filemode='w+' -) -logger = logging.getLogger("EmiyaLog") -# console = logging.StreamHandler() -# console.setLevel(logging.INFO) -# logger.addHandler(console) - - -class EmiyaEngineCore(QtCore.QThread): - - Update = QtCore.pyqtSignal([str, str, int]) - Finish = QtCore.pyqtSignal() - - ReadyFilePath = '' # 输入文件 - OutputFilePath = '' # 输出文件 - BeforeSignal = '' # 输入原始信号 - BeforeSignalSR = 0 # 原始信号采样 - MidSignal = '' # 重采样到96K信号 - MidSignalSR = 0 # 96K - AfterSignalLeft = '' # 处理后的左信号 - AfterSignalRight = '' # 处理后的右信号 - AfterSignal = '' # 处理后的信号 - AfterSignalSR = 0 # 处理后的采样率 - SplitSize = 0 # 倒腾区大小 - AnalysisWindow = False # 分析接续点用的单边FFT是否加窗 - MidSRCFalse = False # SRC开关, 为True时就会取消掉SRC步骤 - MidPrint = False # 打印细节日志开关 - MidPrintProgress = True # 打印进度信息 - - def __init__(self, parent, _InputFilePath, _OutputFilePath, _DebugSwitch, _SplitSize, _WindowSwitch): - super(EmiyaEngineCore, self).__init__(parent) - # QtCore.QThread.__init__(self,parent) - self.ReadyFilePath = _InputFilePath - self.OutputFilePath = _OutputFilePath - self.SplitSize = _SplitSize - self.AnalysisWindow = _WindowSwitch - if _DebugSwitch == 0: - MidPrintProgress = False - elif _DebugSwitch == 1: - MidPrintProgress = True - elif _DebugSwitch == 2: - MidPrint = True - else: - pass - - def LoadFile(self): - self.BeforeSignal, self.BeforeSignalSR = librosa.load(self.ReadyFilePath, sr=None, mono=False) - self.AfterSignalLeft = np.array([()]) - self.AfterSignalRight = np.array([()]) - print("Load signal complete. ChannelCount: %s SampleRate: %s Hz" % (str(len(self.BeforeSignal)), - str(self.BeforeSignalSR))) - logger.info("Load signal complete. ChannelCount: %s SampleRate: %s Hz" % (str(len(self.BeforeSignal)), - str(self.BeforeSignalSR))) - - def MidUpSRC(self): - # 重采样loss样本到96K - print("Please wait for SRC.") - logger.info("Please wait for SRC.") - self.MidSignalSR = 96000 - self.AfterSignalSR = self.MidSignalSR - if self.MidSRCFalse: - self.MidSignal = self.BeforeSignal - else: - self.MidSignal = resampy.resample(self.BeforeSignal, self.BeforeSignalSR, - self.MidSignalSR, filter='kaiser_best') - print("Signal SRC complete.") - logger.info("Signal SRC complete.") - - def MidFindThresholdPoint(self, _MidFFTResultSingle, _FFTPointCount): - # 鉴定频谱基本参数 - _MidAmpData = abs(_MidFFTResultSingle[range(_FFTPointCount//2)]) - # Step0. 找出基波幅度 - _MidBaseFreqAmp = _MidAmpData.max() - if self.MidPrint: - print("Signal max AMP -> %s" % _MidBaseFreqAmp) - logger.debug("Signal max AMP -> %s" % _MidBaseFreqAmp) - # Step1. 找出接续的阈值 - _MidThresholdHit = 1.0e-11 # 方差判定阈值 - _MidThresholdPoint = 0 # 最后的阈值点 - _MidFindRange = int((_FFTPointCount/2)-1) # 搜索的范围 - _MidStartFindPos = round(2000 / (self.BeforeSignalSR / (_FFTPointCount / 2))) # 从2K频点附近开始寻找,加快速度 - _MidStartFlag = True # 循环用的启动Flag - _MidLoopCount = 0 # 循环计数器 - _MidLegalFreq = (self.BeforeSignalSR / 2) - 500 # 判定结果合法的阈值频率 - _MidForwardFreq = 3000 # 前向修正频率 - _MidOrderFreq = (self.BeforeSignalSR / 2) - 6000 # 钦定频率 - # Rev.1: 检查接续点是否符合常理 - while _MidStartFlag or _MidThresholdPoint > round(_MidLegalFreq / (self.BeforeSignalSR / (_FFTPointCount / 2))): - _MidStartFlag = False - if (_MidThresholdPoint * (self.BeforeSignalSR / (_FFTPointCount / 2))) > int(self.BeforeSignalSR / 2): - _MidThresholdHit *= 2 - for i in range(_MidStartFindPos, _MidFindRange): - if i + 5 > _MidFindRange: - break - # 计算连续五个采样*3 的方差,与阈值比较,判断频谱消失的位置 - if np.var(_MidAmpData[i:i + 4]) < _MidThresholdHit and \ - np.var(_MidAmpData[i + 1:i + 5]) < _MidThresholdHit: - # 定位到当前位置的前500Hz位置 - _MidThresholdPoint = i - round(_MidForwardFreq / (self.BeforeSignalSR / (_FFTPointCount / 2))) - break - # 错误超过5把就强行钦定频率 - _MidLoopCount += 1 - if _MidLoopCount > 5: - _MidThresholdPoint = round(_MidOrderFreq / (self.BeforeSignalSR / (_FFTPointCount / 2))) - break - # 打印函数返回信息 - if self.MidPrint: - print("Signal threshold point -> %s @ %sHz Max Amp -> %s" % (_MidThresholdPoint, - _MidThresholdPoint * - (self.BeforeSignalSR / (_MidFindRange + 1)), - _MidBaseFreqAmp)) - logger.debug("Signal threshold point -> %s @ %sHz Max Amp -> %s" % (_MidThresholdPoint, - _MidThresholdPoint * - (self.BeforeSignalSR / (_MidFindRange + 1)), - _MidBaseFreqAmp)) - # _MidThresholdPoint = round(21000/(self.BeforeSignalSR/(_FFTPointCount/2))) - return _MidBaseFreqAmp, _MidThresholdPoint - - def MidInsertJitter(self, _MidFFTResultDouble, _FFTPointCount, _MidThresholdPoint, _MidBaseFreqAmp): - # 构造抖动 - if _MidThresholdPoint <= 0: - return _MidFFTResultDouble - for i in range(_MidThresholdPoint, _FFTPointCount - _MidThresholdPoint): - # Rev.0: 调整生成概率,频率越高概率越低 - # Rev.1: 加入幅值判定,幅度越大概率越大 - _GenPossible = abs((_FFTPointCount/2)-i)/((_FFTPointCount/2)-_MidThresholdPoint)*(_MidBaseFreqAmp/0.22) - if random.randint(0, 1000000) < 800000 * _GenPossible: # 0<=x<=10 - _MidRealValue = abs(_MidFFTResultDouble.real[i]) - _BaseJitterMin = _MidRealValue * 0.5 * (1-_GenPossible) - _BaseJitterMax = _MidRealValue * 6 * _GenPossible - _AmpJitterMin = _MidBaseFreqAmp * _MidRealValue * 0.5 - _AmpJitterMax = _MidBaseFreqAmp * _MidRealValue * 2 - _AmpJitterPrefix = -1 if random.randint(0, 100000) < 50000 else 1 - _MiditterPrefix = -1 if random.randint(0, 100000) < 50000 else 1 - _MidDeltaJitterValue = random.uniform(_BaseJitterMin, _BaseJitterMax) + \ - _AmpJitterPrefix * random.uniform(_AmpJitterMin, _AmpJitterMax) - _MidFFTResultDouble.real[i] += _MiditterPrefix * _MidDeltaJitterValue - return _MidFFTResultDouble - - def FinSaveFile(self): - init(autoreset=True) - SaveFilePath = self.OutputFilePath - if self.OutputFilePath == '': - SaveFilePath = os.path.abspath(os.path.join(self.ReadyFilePath, os.pardir)) + "\\" - OutputFileName = SaveFilePath + 'Output_%s.wav' % uuid.uuid4().hex - librosa.output.write_wav(SaveFilePath, self.AfterSignal, self.AfterSignalSR) - print(Back.GREEN + Fore.WHITE + "SAVE DONE" + Back.BLACK + " Output path -> " + SaveFilePath) - logger.info("SAVE DONE Output path -> " + SaveFilePath) - - def run(self): - # 加载文件启动SRC - self.LoadFile() - self.MidUpSRC() - # 初始化彩色命令行 - init(autoreset=True) - # 记录整个任务开始时间 - _MidStartTimeGlobal = datetime.datetime.now() - # 两个声道 - for ChannelIndex in range(2): - # 记录开始时间 - _MidStartTime = datetime.datetime.now() - # 信号总长度 - _MidSignalLength = len(self.MidSignal[ChannelIndex]) - # FFT分割数量 - _FFTPointCount = 1024 # 至少2048点,避免计算错误 - _MidDivCount = math.floor(_MidSignalLength/_FFTPointCount) - # 实际重叠操作数量 = FFT分割数量 * 分块次数 - _EachLength = 512 - # 补偿标记, 标记有效时, 说明已经到了序列尾部, 因停止继续循环运算 - SuffixFlag = False - SuffixLength = 0 - # Rev.2: 加入临时数组加速Append, 临时数组每Append操作设定次数就倒腾一次 - _TempArrayLeft = np.array([()]) - _TempArrayRight = np.array([()]) - _TempAppendCount = 0 - # 除了最后一块,每一块都是取计算结果时域的前512点 - for SamplePointIndex in range(_MidDivCount+1): - StartPos = SamplePointIndex*_FFTPointCount - EndPos = SamplePointIndex*_FFTPointCount+_FFTPointCount - _EachPieceLeft = np.array([()]) - _EachPieceRight = np.array([()]) - for EachFourPiece in range(int(_FFTPointCount/_EachLength)): - StartPos += EachFourPiece * _EachLength - EndPos += EachFourPiece * _EachLength - # 若超出范围, 需将本次计算完整保留接续有效部分(除去补零部分) - if EndPos > _MidSignalLength: - EndPos = _MidSignalLength - SuffixFlag = True - _TempSignal = self.MidSignal[ChannelIndex][StartPos:EndPos] - # 不足FFT点数的补零 - while len(_TempSignal) != _FFTPointCount: - _TempSignal = np.append(_TempSignal, [0]) - SuffixLength += 1 - # 执行FFT运算, 单边谱用于分析, 双边谱用于处理 - _MidFFTResultDouble = np.fft.fft(_TempSignal, _FFTPointCount) / (_FFTPointCount) - if self.AnalysisWindow: - _TempSignal *= scipy.signal.hann(_FFTPointCount, sym=0) - _MidFFTResultSingle = np.fft.fft(_TempSignal, _FFTPointCount) / (_FFTPointCount / 2) - # 获取当前分段最大振幅, 处理阈值点 - _MidBaseFreqAmp, _MidThresholdPoint = self.MidFindThresholdPoint(_MidFFTResultSingle, - _FFTPointCount) - # 构造抖动到当前FFT实际值上 - _MidFFTAfterJitter = self.MidInsertJitter(_MidFFTResultDouble, _FFTPointCount, - _MidThresholdPoint, _MidBaseFreqAmp) - # 逆变换IFFT - _MidTimerDomSignal = np.fft.ifft(_MidFFTAfterJitter, n=_FFTPointCount) - # 接续到新信号上 - _AppendLength = _EachLength - if SuffixFlag: - _AppendLength = _FFTPointCount-SuffixLength - _MidAppendSignal = _MidTimerDomSignal[0:_AppendLength] - if self.MidPrint: - print("Per each length -> %s" % len(_MidAppendSignal)) - logger.debug("Per each length -> %s" % len(_MidAppendSignal)) - if ChannelIndex == 0: - _EachPieceLeft = np.append(_EachPieceLeft, _MidAppendSignal) - else: - _EachPieceRight = np.append(_EachPieceRight, _MidAppendSignal) - # 及时跳出尾部 - if SuffixFlag: - break - # 先倒腾到临时数组,倒腾500次给放回大数组 - if _TempAppendCount < self.SplitSize and not SuffixFlag: - # 已消耗时间 - _MidUsedTime = datetime.datetime.now()-_MidStartTime - # 估算剩余时间 - _MidEtaTime = (_MidUsedTime/((SamplePointIndex+1)/_MidDivCount))-_MidUsedTime - # 完整任务消耗时间 - _MidTotalUsedTime = datetime.datetime.now()-_MidStartTimeGlobal - # 预计总消耗时间 - if ChannelIndex == 0: - _MidTotalEtaTime = (_MidTotalUsedTime/((SamplePointIndex+1)/_MidDivCount))*2-_MidTotalUsedTime - else: - _MidTotalEtaTime = _MidEtaTime - # 进度比例 - _MidProgressRate = round(50 * (SamplePointIndex + 1) / _MidDivCount) + \ - (50 if ChannelIndex == 1 else 0) - self.Update.emit(str(_MidTotalUsedTime)[:-5], str(_MidTotalEtaTime)[:-5], _MidProgressRate) - # 构造显示文本 - if ChannelIndex == 0: - _TempArrayLeft = np.append(_TempArrayLeft, _EachPieceLeft) - if self.MidPrintProgress: - print("Left channel progress rate -> " + Fore.CYAN + str(SamplePointIndex) + " / " + - str(_MidDivCount-1) + Fore.WHITE + " TIME USED -> " + Fore.YELLOW + - str(_MidUsedTime) + Fore.WHITE + " ETA -> " + Fore.GREEN + str(_MidEtaTime)) - logger.info("Left channel progress rate -> " + str(SamplePointIndex) + " / " + - str(_MidDivCount-1) + " TIME USED -> " + - str(_MidUsedTime) + " ETA -> " + str(_MidEtaTime)) - else: - _TempArrayRight = np.append(_TempArrayRight, _EachPieceRight) - if self.MidPrintProgress: - print("Right channel progress rate -> " + Fore.CYAN + str(SamplePointIndex) + " / " + - str(_MidDivCount-1) + Fore.WHITE + " TIME USED -> " + Fore.YELLOW + - str(_MidUsedTime) + Fore.WHITE + " ETA -> " + Fore.GREEN + str(_MidEtaTime)) - logger.info("Right channel progress rate -> " + str(SamplePointIndex) + " / " + - str(_MidDivCount-1) + " TIME USED -> " + - str(_MidUsedTime) + " ETA -> " + str(_MidEtaTime)) - else: - _TempAppendCount = 0 - if ChannelIndex == 0: - self.AfterSignalLeft = np.append(self.AfterSignalLeft, _TempArrayLeft) - _TempArrayLeft = np.array([()]) - else: - self.AfterSignalRight = np.append(self.AfterSignalRight, _TempArrayRight) - _TempArrayRight = np.array([()]) - # 倒腾计数器 - _TempAppendCount += 1 - if SuffixFlag: - break - self.AfterSignal = np.array([self.AfterSignalLeft.real, self.AfterSignalRight.real]) - self.FinSaveFile() - self.Finish.emit() - - -class EmiyaEngineGUI(object): - - # Emiya Engine GUI ARGS - - InputFilePath = '' - OutputFilePath = '' - IsUseWindow = False - SplitSize = 500 - IsStarted = False - SubCore = QtCore.pyqtSignal() - - def __init__(self, MainWindow): - - MainWindow.setObjectName("MainWindow") - MainWindow.resize(615, 272) - MainWindow.setMinimumSize(QtCore.QSize(615, 272)) - MainWindow.setMaximumSize(QtCore.QSize(615, 272)) - font = QtGui.QFont() - font.setFamily("微软雅黑") - font.setPointSize(10) - MainWindow.setFont(font) - MainWindow.setWindowTitle("Emiya Engine - 只要蘊藏著想成為真物的意志, 偽物就比真物還要來得真實") - self.centralwidget = QtWidgets.QWidget(MainWindow) - self.centralwidget.setObjectName("centralwidget") - - self.Input_Label = QtWidgets.QLabel(self.centralwidget) - self.Input_Label.setGeometry(QtCore.QRect(20, 20, 101, 16)) - font = QtGui.QFont() - font.setFamily("微软雅黑") - font.setPointSize(11) - self.Input_Label.setFont(font) - self.Input_Label.setObjectName("Input_Label") - - self.InputLineBox = QtWidgets.QLineEdit(self.centralwidget) - self.InputLineBox.setGeometry(QtCore.QRect(130, 20, 401, 21)) - font = QtGui.QFont() - font.setFamily("微软雅黑") - font.setPointSize(10) - self.InputLineBox.setFont(font) - self.InputLineBox.setObjectName("InputLineBox") - - self.InputButton = QtWidgets.QPushButton(self.centralwidget) - self.InputButton.setGeometry(QtCore.QRect(540, 20, 51, 21)) - font = QtGui.QFont() - font.setFamily("微软雅黑") - font.setPointSize(11) - self.InputButton.setFont(font) - self.InputButton.setObjectName("InputButton") - self.InputButton.clicked.connect(self.SetInputFilePath) - - self.OutputLineBox = QtWidgets.QLineEdit(self.centralwidget) - self.OutputLineBox.setGeometry(QtCore.QRect(130, 50, 401, 21)) - font = QtGui.QFont() - font.setFamily("微软雅黑") - font.setPointSize(10) - self.OutputLineBox.setFont(font) - self.OutputLineBox.setObjectName("OutputLineBox") - - self.OutputButton = QtWidgets.QPushButton(self.centralwidget) - self.OutputButton.setGeometry(QtCore.QRect(540, 50, 51, 21)) - font = QtGui.QFont() - font.setFamily("微软雅黑") - font.setPointSize(11) - self.OutputButton.setFont(font) - self.OutputButton.setObjectName("OutputButton") - self.OutputButton.clicked.connect(self.SetOutputFilePath) - - self.Output_Label = QtWidgets.QLabel(self.centralwidget) - self.Output_Label.setGeometry(QtCore.QRect(20, 50, 101, 16)) - font = QtGui.QFont() - font.setFamily("微软雅黑") - font.setPointSize(11) - self.Output_Label.setFont(font) - self.Output_Label.setObjectName("Output_Label") - - self.IsUseWindowCheck = QtWidgets.QCheckBox(self.centralwidget) - self.IsUseWindowCheck.setGeometry(QtCore.QRect(50, 90, 181, 31)) - font = QtGui.QFont() - font.setFamily("微软雅黑") - font.setPointSize(11) - self.IsUseWindowCheck.setFont(font) - self.IsUseWindowCheck.setChecked(False) - self.IsUseWindowCheck.setObjectName("IsUseWindowCheck") - self.IsUseWindowCheck.stateChanged.connect(self.SetIsUseWindowCheck) - - self.SplitSizeSpin = QtWidgets.QSpinBox(self.centralwidget) - self.SplitSizeSpin.setGeometry(QtCore.QRect(350, 90, 71, 31)) - self.SplitSizeSpin.setMinimum(100) - self.SplitSizeSpin.setMaximum(5000) - self.SplitSizeSpin.setSingleStep(100) - self.SplitSizeSpin.setProperty("value", 500) - self.SplitSizeSpin.setObjectName("SplitSizeSpin") - self.SplitSizeSpin.valueChanged.connect(self.SetSplitSize) - - self.SplitSize_Label = QtWidgets.QLabel(self.centralwidget) - self.SplitSize_Label.setGeometry(QtCore.QRect(250, 90, 91, 31)) - font = QtGui.QFont() - font.setFamily("微软雅黑") - font.setPointSize(11) - self.SplitSize_Label.setFont(font) - self.SplitSize_Label.setObjectName("SplitSize_Label") - - self.StartButton = QtWidgets.QPushButton(self.centralwidget) - self.StartButton.setGeometry(QtCore.QRect(460, 90, 91, 31)) - font = QtGui.QFont() - font.setFamily("微软雅黑") - font.setPointSize(11) - self.StartButton.setFont(font) - self.StartButton.setObjectName("StartButton") - self.StartButton.clicked.connect(self.RunProcess) - - self.groupBox = QtWidgets.QGroupBox(self.centralwidget) - self.groupBox.setGeometry(QtCore.QRect(20, 130, 571, 101)) - self.groupBox.setObjectName("groupBox") - - self.UsedTime_Label = QtWidgets.QLabel(self.groupBox) - self.UsedTime_Label.setGeometry(QtCore.QRect(30, 30, 101, 16)) - font = QtGui.QFont() - font.setFamily("微软雅黑") - font.setPointSize(11) - self.UsedTime_Label.setFont(font) - self.UsedTime_Label.setObjectName("UsedTime_Label") - - self.GlobalProgressBar = QtWidgets.QProgressBar(self.groupBox) - self.GlobalProgressBar.setGeometry(QtCore.QRect(100, 60, 451, 23)) - self.GlobalProgressBar.setProperty("value", 0) - self.GlobalProgressBar.setObjectName("GlobalProgressBar") - - self.GlobalProgressBar_Label = QtWidgets.QLabel(self.groupBox) - self.GlobalProgressBar_Label.setGeometry(QtCore.QRect(30, 60, 61, 21)) - font = QtGui.QFont() - font.setFamily("微软雅黑") - font.setPointSize(11) - self.GlobalProgressBar_Label.setFont(font) - self.GlobalProgressBar_Label.setObjectName("GlobalProgressBar_Label") - - self.UsedTime = QtWidgets.QLabel(self.groupBox) - self.UsedTime.setGeometry(QtCore.QRect(150, 30, 101, 16)) - font = QtGui.QFont() - font.setFamily("微软雅黑") - font.setPointSize(11) - self.UsedTime.setFont(font) - self.UsedTime.setAlignment(QtCore.Qt.AlignRight | QtCore.Qt.AlignTrailing | QtCore.Qt.AlignVCenter) - self.UsedTime.setObjectName("UsedTime") - - self.EtaTime = QtWidgets.QLabel(self.groupBox) - self.EtaTime.setGeometry(QtCore.QRect(410, 30, 91, 16)) - font = QtGui.QFont() - font.setFamily("微软雅黑") - font.setPointSize(11) - self.EtaTime.setFont(font) - self.EtaTime.setAlignment(QtCore.Qt.AlignRight | QtCore.Qt.AlignTrailing | QtCore.Qt.AlignVCenter) - self.EtaTime.setObjectName("EtaTime") - - self.EtaTime_Label = QtWidgets.QLabel(self.groupBox) - self.EtaTime_Label.setGeometry(QtCore.QRect(290, 30, 101, 16)) - font = QtGui.QFont() - font.setFamily("微软雅黑") - font.setPointSize(11) - self.EtaTime_Label.setFont(font) - self.EtaTime_Label.setObjectName("EtaTime_Label") - - MainWindow.setCentralWidget(self.centralwidget) - self.menubar = QtWidgets.QMenuBar(MainWindow) - self.menubar.setGeometry(QtCore.QRect(0, 0, 615, 22)) - self.menubar.setObjectName("menubar") - self.menu_F = QtWidgets.QMenu(self.menubar) - self.menu_F.setObjectName("menu_F") - MainWindow.setMenuBar(self.menubar) - self.action_OpenFile = QtWidgets.QAction(MainWindow) - self.action_OpenFile.setObjectName("action_OpenFile") - self.action_OpenFile.triggered.connect(self.SetInputFilePath) - self.action_Exit = QtWidgets.QAction(MainWindow) - self.action_Exit.setObjectName("action_Exit") - self.action_Exit.triggered.connect(self.ExitAll) - self.menu_F.addAction(self.action_OpenFile) - self.menu_F.addAction(self.action_Exit) - self.menubar.addAction(self.menu_F.menuAction()) - - self.TextedUI(MainWindow) - QtCore.QMetaObject.connectSlotsByName(MainWindow) - - def TextedUI(self, MainWindow): - _translate = QtCore.QCoreApplication.translate - self.Input_Label.setText(_translate("MainWindow", "输入文件路径:")) - self.InputButton.setText(_translate("MainWindow", "<<<")) - self.OutputButton.setText(_translate("MainWindow", "<<<")) - self.Output_Label.setText(_translate("MainWindow", "输出文件路径:")) - self.IsUseWindowCheck.setToolTip(_translate("MainWindow", "汉宁Hann双余弦窗可以使FFT分析中的频谱泄漏更少")) - self.IsUseWindowCheck.setText(_translate("MainWindow", "分析音频时使用Hann窗")) - self.SplitSize_Label.setText(_translate("MainWindow", "倒腾区大小:")) - self.StartButton.setText(_translate("MainWindow", "开始处理")) - self.groupBox.setTitle(_translate("MainWindow", "输出状态")) - self.UsedTime_Label.setText(_translate("MainWindow", "当前处理耗时:")) - self.GlobalProgressBar_Label.setText(_translate("MainWindow", "当前进度")) - self.UsedTime.setText(_translate("MainWindow", "00:00:00")) - self.EtaTime.setText(_translate("MainWindow", "00:00:00")) - self.EtaTime_Label.setText(_translate("MainWindow", "预计剩余时间:")) - self.menu_F.setTitle(_translate("MainWindow", "文件(&F)")) - self.action_OpenFile.setText(_translate("MainWindow", "打开(&O)")) - self.action_Exit.setText(_translate("MainWindow", "退出(&E)")) - - def SetInputFilePath(self): - self.InputFilePath = str(QtWidgets.QFileDialog.getOpenFileName(None, "选择待处理的文件")[0]) - if self.InputFilePath: - self.InputLineBox.setText(self.InputFilePath) - - def SetOutputFilePath(self): - self.OutputFilePath = str(QtWidgets.QFileDialog.getSaveFileName(None, "设置输出文件的位置及文件名")[0]) - if self.OutputFilePath: - self.OutputLineBox.setText(self.OutputFilePath) - - def SetIsUseWindowCheck(self): - self.IsUseWindow = True if self.IsUseWindowCheck.checkState() == 2 else False - - def SetSplitSize(self): - self.SplitSize = int(self.SplitSizeSpin.value()) - - def ExitAll(self): - QtWidgets.QApplication.quit() - - def RunProcess(self): - if not self.IsStarted: - self.InputFilePath = self.InputLineBox.text() - self.OutputFilePath = self.OutputLineBox.text() - if self.InputFilePath and self.OutputFilePath: - self.IsStarted = True - self.StartButton.setText("停止处理") - self.CoreObject = EmiyaEngineCore(None, self.InputFilePath, self.OutputFilePath, - 1, self.SplitSize, self.IsUseWindow) - self.CoreObject.Update.connect(self.UpdateState) - self.CoreObject.Finish.connect(self.DetectEnd) - self.CoreObject.start() - else: - self.IsStarted = False - self.StartButton.setText("开始处理") - self.CoreObject.terminate() - self.UsedTime.setText("00:00:00") - self.EtaTime.setText("00:00:00") - self.GlobalProgressBar.setValue(0) - print("所有处理已停止") - logger.info("所有处理已停止") - - def DetectEnd(self): - self.IsStarted = False - self.StartButton.setText("开始处理") - - def UpdateState(self, _TimeUsed, _EtaTime, _ProgressRate): - self.UsedTime.setText(str(_TimeUsed)) - self.EtaTime.setText(str(_EtaTime)) - self.GlobalProgressBar.setValue(_ProgressRate) - - -if __name__ == "__main__": - import sys - app = QtWidgets.QApplication(sys.argv) - MainWindow = QtWidgets.QMainWindow() - ui = EmiyaEngineGUI(MainWindow) - # ui.setupUi(MainWindow) - MainWindow.show() - sys.exit(app.exec_()) diff --git a/README.md b/README.md index 2f59774..b104c52 100644 --- a/README.md +++ b/README.md @@ -4,65 +4,26 @@ > "只要蘊藏著想成為真物的意志,偽物就比真物還要來得真實。" Emiya Engine 是一个用来丰富音频频谱的脚本。可以将频谱变得好看那么一点。 -原理是使用 FFT (快速傅立叶变换) 将音频信号采样转到频域,在频域上为空白的频谱加上与时域幅值相称的微小抖动。 +原理是使用 FFT (快速傅立叶变换) 将音频信号采样转到频域,在频域上为空白的频谱加上与时域幅值相称的微小抖动。 -###使用须知: +###敬告: +你当前处于 dev 分支,本分支下的程序还处于测试开发阶段,使用前请三思。 - - 由于 FFT 的栅栏效应,程序的处理过程不可避免地会损失部分采样信号。**故不建议将本程序用于玄学领域。** - - 由于程序缺乏细致调教,当前算法会导致部分采样块未被有效处理。 - - 由于玄学原因,最后生成的文件有一定几率出现时长一百余个采样点(0.0016s)的爆音区域。 - - 由于处理需要消耗大约是音源时长的 2 - 10 倍的时间,故不建议输入较长的音频文件。 - - 鉴于脚本输出为 96KHz 采样 32bit 单精度浮点型 的 WAV 文件,请不要输入比输出精度更高的文件。 +###当前版本: +Alpha.1 Rev.0 +~~终于 Alpha.1 了~~ -###程序依赖: +###接下来做的: - - Python 3 - - numpy - - scipy - - librosa - - resampy - - colorama - - PyQt5 (GUI版依赖) + - 重构原有程序结构 (进行中) + - 改成多进程处理结构(目前还不知道和现有 GUI 会发生怎样的碰撞) + +###当前改进思路: +提高因采样点数不足而下降的 FFT 精度: +对低采样点数做时域重采样。 -####依赖安装建议 -Windows平台: - -> 实际上 librosa 的依赖非常多,如果使用 `pip`安装,可能会导致出错, -> 建议直接在[这里](http://www.lfd.uci.edu/~gohlke/pythonlibs/)下载二进制包使用`pip`离线安装。 -> 除了以上列表的依赖,还有`Cython` 和 `scikit-learn`,建议一块装了。 -> `librosa` 需要配置 `ffmpeg` 的目录, -> 找到 `Python` 安装目录下 `Lib\site-packages\audioread` 文件夹的 `ffdec.py` 文件。 -> 修改第 32 行,修改为你的 `ffmpeg` 程序路径,比如我的放在 F 盘根目录,设置成这样: -> `COMMANDS = ('F:\\ffmpeg.exe', 'avconv')` - -Linux平台: - -> ArchLinux 上建议用 pacman 一路搞定 numpy scipy scikit-learn Cython,当然使用pip也是OK的。 -> Debian/Ubuntu 上默认源似乎必须用 apt-get 安装,有一些包用 pip 安装有些问题。 -> 与 Windows 平台一样,也需要为 librosa安装后端解码音频文件, -> 直接使用发行版自带的包管理器安装 ffmpeg 就可以。 -> 如果出错了,建议从源编译最新的放在原来的路径下。 - -###命令行帮助: - - -h, --help 显示帮助信息. - -i INPUT, --input INPUT - 待处理文件的绝对路径, 同一路径可直接输入文件名. 例如: - Music_ready_test.mp3 - -d DEBUG, --debug DEBUG - 调试等级设定. 默认 1 级. - 设置为 0 时, 只显示任务起始日志; - 设置为 1 时, 额外显示进度日志; - 设置为 2 时, 额外显示处理细节日志 - -s SIZE, --size SIZE - 倒腾区大小. 默认 500. - 使用倒腾区是因为 numpy 做大数组 append 速度远低于小数组, - 故加入小数组多倒腾一手, 这个参数就是小数组的尺寸. - -w WINDOW, --window WINDOW - 分析用汉宁Hann双余弦窗启用开关. 默认不使用. - 输入 0 代表不使用, 1 代表使用. - -###效果预览: -音源:44.1KHz@16bit WAV -![enter image description here](https://i.imgur.com/VU9Obqw.jpg) +设置灵活的输出采样率: +处理过程中生成目标采样率。 +多进程处理结构: +分割时域处理后等待同步合并。 \ No newline at end of file From a20c82bc9956bb5cb0a5231b7891dc1b2acad269 Mon Sep 17 00:00:00 2001 From: Sg4Dylan Date: Sun, 26 Feb 2017 19:38:04 +0800 Subject: [PATCH 02/14] =?UTF-8?q?=E5=90=8C=E6=AD=A5=E5=90=84=E8=BF=9B?= =?UTF-8?q?=E7=A8=8B=E8=BF=94=E5=9B=9E=E6=95=B0=E6=8D=AE=E5=AE=8C=E5=B7=A5?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- EmiyaEngine.py | 28 ++++++++++++++-------------- 1 file changed, 14 insertions(+), 14 deletions(-) diff --git a/EmiyaEngine.py b/EmiyaEngine.py index 18042b6..67fb7f6 100644 --- a/EmiyaEngine.py +++ b/EmiyaEngine.py @@ -63,37 +63,37 @@ def process_leader(self): # 生成进程池 pool = multiprocessing.Pool(processes=self.cpu_thread) # 初始化结果字典 + raw_result_dict = {} result_dict = {} # 分割时间域 - each_piece_length = round(len(self.input_signal_array[channel_index]) / self.cpu_thread) + splited_input_signal = np.array_split(self.input_signal_array[channel_index], self.cpu_thread) for i in range(self.cpu_thread): - # 计算分发分片的起始位置 - piece_start_pos = i * each_piece_length - piece_end_pos = (i + 1) * each_piece_length - if piece_end_pos > len(self.input_signal_array[channel_index]): - piece_end_pos = len(self.input_signal_array[channel_index]) - # 生成分片 - process_piece = self.input_signal_array[channel_index][piece_start_pos:piece_end_pos] # 下发分片 - result_dict[i] = pool.apply_async(self.process_core, (process_piece, i, )) + raw_result_dict[i] = pool.apply_async(self.process_core, (splited_input_signal[i], i, )) pool.close() pool.join() # 拼合分片 - # 接下来处理这里的同步拼接问题 temp_array = np.array([()]) + # 理清顺序 for i in range(self.cpu_thread): - temp_array = np.append(result_dict[i].get(), temp_array) + result_dict[raw_result_dict[i].get()[1]] = raw_result_dict[i].get()[0] + # 追加分片 + for i in range(self.cpu_thread): + temp_array = np.append(temp_array, result_dict[i]) + # 合并到各声道 if channel_index == 0: self.mid_signal_larray = temp_array else: self.mid_signal_rarray = temp_array + # 拼合左右声道 self.mid_signal_carray = np.array([self.mid_signal_larray, self.mid_signal_rarray]) + # 保存文件 self.save_file() def process_core(self, signal_piece, index): - print("Entering process Index %s" % index) - print(len(signal_piece)) - return signal_piece + + + return [signal_piece, index] def save_file(self): librosa.output.write_wav(self.output_file_path, self.mid_signal_carray, self.input_sr) From 6726b312c69579c45dcc9465a5c7d43c29353c1d Mon Sep 17 00:00:00 2001 From: Sg4Dylan Date: Sun, 26 Feb 2017 22:08:08 +0800 Subject: [PATCH 03/14] =?UTF-8?q?=E5=89=A9=E4=B8=8B=E5=88=86=E5=89=B2?= =?UTF-8?q?=E5=AD=90=E5=88=86=E7=89=87=E5=A4=84=E7=90=86=E8=BF=87=E7=A8=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- EmiyaEngine.py | 86 +++++++++++++++++++++++++++++++++++++++++++++++--- 1 file changed, 81 insertions(+), 5 deletions(-) diff --git a/EmiyaEngine.py b/EmiyaEngine.py index 67fb7f6..62035af 100644 --- a/EmiyaEngine.py +++ b/EmiyaEngine.py @@ -9,10 +9,12 @@ # 只要蘊藏著想成為真物的意志,偽物就比真物還要來得真實 +import math import numpy as np import scipy import librosa import resampy +import random import multiprocessing @@ -27,8 +29,9 @@ class EmiyaEngine: mid_signal_larray = '' mid_signal_rarray = '' mid_signal_carray = '' - mid_process_ponit = 32 - mid_src_point = 2048 + # 各进程处理参数 + proc_mid_sr_rate = 32 + proc_fft_length = 2048 # 输出用参数 output_file_path = '' output_sr = 0 @@ -91,12 +94,85 @@ def process_leader(self): self.save_file() def process_core(self, signal_piece, index): + # SRC 预处理 + proc_mid_data = resampy.resample(signal_piece, + self.input_sr, + self.input_sr * self.proc_mid_sr_rate, + filter='kaiser_fast') + # 加抖动处理 - - return [signal_piece, index] + # SRC 后处理 + proc_fin_piece = resampy.resample(proc_mid_data, + self.input_sr * self.proc_mid_sr_rate, + self.output_sr, + filter='kaiser_fast') + return [proc_fin_piece, index] + + def find_threshold_point(self, input_fft): + # 鉴定频谱基本参数 + amp_fft = abs(input_fft[range(self.proc_fft_length // 2)]) + # Step0. 找出基波幅度 + base_amp_freq = amp_fft.max() + # Step1. 找出接续的阈值 + threshold_hit = 1.0e-11 # 方差判定阈值 + fin_threshold_point = 0 # 最后的阈值点 + find_range = int((self.proc_fft_length / 2) - 1) # 搜索的范围 + start_find_pos = round(2000 / (self.input_sr / (self.proc_fft_length / 2))) # 从2K频点附近开始寻找,加快速度 + start_flag = True # 循环用的启动Flag + loop_count = 0 # 循环计数器 + legal_freq = (self.input_sr / 2) - 500 # 判定结果合法的阈值频率 + forward_freq = 3000 # 前向修正频率 + order_freq = (self.input_sr / 2) - 6000 # 钦定频率 + # Rev.1: 检查接续点是否符合常理 + while start_flag or fin_threshold_point > round(legal_freq / (self.input_sr / (self.proc_fft_length / 2))): + start_flag = False + if (fin_threshold_point * (self.input_sr / (self.proc_fft_length / 2))) > int(self.input_sr / 2): + threshold_hit *= 2 + for i in range(start_find_pos, find_range): + if i + 5 > find_range: + break + # 计算连续五个采样*3 的方差,与阈值比较,判断频谱消失的位置 + if np.var(amp_fft[i:i + 4]) < threshold_hit and \ + np.var(amp_fft[i + 1:i + 5]) < threshold_hit: + # 定位到当前位置的前500Hz位置 + fin_threshold_point = i - round(forward_freq / (self.input_sr / (self.proc_fft_length / 2))) + break + # 错误超过5把就强行钦定频率 + loop_count += 1 + if loop_count > 5: + fin_threshold_point = round( + order_freq / (self.input_sr / (self.proc_fft_length / 2))) + break + return base_amp_freq, fin_threshold_point + + def generate_jitter(self, input_fft, fin_threshold_point, base_amp_freq): + # 构造抖动 + if fin_threshold_point <= 0: + return input_fft + for i in range(fin_threshold_point, self.proc_fft_length - fin_threshold_point): + # Rev.0: 调整生成概率,频率越高概率越低 + # Rev.1: 加入幅值判定,幅度越大概率越大 + gen_possible = abs((self.proc_fft_length / 2) - i) / ((self.proc_fft_length / + 2) - fin_threshold_point) * (base_amp_freq / 0.22) + if random.randint(0, 1000000) < 800000 * gen_possible: # 0<=x<=10 + real_value = abs(input_fft.real[i]) + base_jitter_min = real_value * 0.5 * (1 - gen_possible) + base_jitter_max = real_value * 6 * gen_possible + amp_jitter_min = base_amp_freq * real_value * 0.5 + amp_jitter_max = base_amp_freq * real_value * 2 + amp_jitter_prefix = - \ + 1 if random.randint(0, 100000) < 50000 else 1 + jitter_prefix = - \ + 1 if random.randint(0, 100000) < 50000 else 1 + delta_jitter_value = random.uniform( + base_jitter_min, base_jitter_max) + amp_jitter_prefix * random.uniform(amp_jitter_min, amp_jitter_max) + input_fft.real[ + i] += jitter_prefix * delta_jitter_value + return input_fft def save_file(self): - librosa.output.write_wav(self.output_file_path, self.mid_signal_carray, self.input_sr) + librosa.output.write_wav(self.output_file_path, self.mid_signal_carray, self.output_sr) + if __name__ == "__main__": From 59e873b14bba80227bd801f03c76ed758f692d50 Mon Sep 17 00:00:00 2001 From: Sg4Dylan Date: Mon, 27 Feb 2017 20:41:12 +0800 Subject: [PATCH 04/14] =?UTF-8?q?=E6=8E=A5=E4=B8=8B=E6=9D=A5=E5=B0=B1?= =?UTF-8?q?=E6=98=AF=E4=BF=AE=E8=80=81=E9=97=AE=E9=A2=98=E4=BA=86?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- EmiyaEngine.py | 187 ++++++++++++++++--------------------------------- 1 file changed, 61 insertions(+), 126 deletions(-) diff --git a/EmiyaEngine.py b/EmiyaEngine.py index 62035af..e87b48f 100644 --- a/EmiyaEngine.py +++ b/EmiyaEngine.py @@ -30,7 +30,7 @@ class EmiyaEngine: mid_signal_rarray = '' mid_signal_carray = '' # 各进程处理参数 - proc_mid_sr_rate = 32 + proc_mid_sr_rate = 2 proc_fft_length = 2048 # 输出用参数 output_file_path = '' @@ -68,11 +68,18 @@ def process_leader(self): # 初始化结果字典 raw_result_dict = {} result_dict = {} + # SRC 预处理 + pre_src_data = resampy.resample(self.input_signal_array[channel_index], + self.input_sr, + self.input_sr * self.proc_mid_sr_rate, + filter='kaiser_fast') + print(len(pre_src_data)) # 分割时间域 - splited_input_signal = np.array_split(self.input_signal_array[channel_index], self.cpu_thread) + splited_input_signal = np.array_split(pre_src_data, self.cpu_thread) for i in range(self.cpu_thread): # 下发分片 raw_result_dict[i] = pool.apply_async(self.process_core, (splited_input_signal[i], i, )) + # raw_result_dict[i] = self.process_core(splited_input_signal[i], i) pool.close() pool.join() # 拼合分片 @@ -80,33 +87,68 @@ def process_leader(self): # 理清顺序 for i in range(self.cpu_thread): result_dict[raw_result_dict[i].get()[1]] = raw_result_dict[i].get()[0] + # result_dict[raw_result_dict[i][1]] = raw_result_dict[i][0] # 追加分片 for i in range(self.cpu_thread): temp_array = np.append(temp_array, result_dict[i]) + print(len(temp_array)) + # SRC 后处理 + temp_src_array = resampy.resample(temp_array, + self.input_sr * self.proc_mid_sr_rate, + self.output_sr, + filter='kaiser_fast') + # temp_src_array = temp_array # 合并到各声道 if channel_index == 0: - self.mid_signal_larray = temp_array + self.mid_signal_larray = temp_src_array else: - self.mid_signal_rarray = temp_array + self.mid_signal_rarray = temp_src_array # 拼合左右声道 self.mid_signal_carray = np.array([self.mid_signal_larray, self.mid_signal_rarray]) # 保存文件 self.save_file() def process_core(self, signal_piece, index): - # SRC 预处理 - proc_mid_data = resampy.resample(signal_piece, - self.input_sr, - self.input_sr * self.proc_mid_sr_rate, - filter='kaiser_fast') - # 加抖动处理 - - # SRC 后处理 - proc_fin_piece = resampy.resample(proc_mid_data, - self.input_sr * self.proc_mid_sr_rate, - self.output_sr, - filter='kaiser_fast') - return [proc_fin_piece, index] + # + this_whole_length = len(signal_piece) + this_div_count = round(this_whole_length/self.proc_fft_length) + # + this_output = np.array([()]) + for i in range(this_div_count): + # + this_start_pos = i * self.proc_fft_length + this_end_pos = i * self.proc_fft_length + self.proc_fft_length + # + this_proc_piece = signal_piece[this_start_pos:this_end_pos] + # + this_suffix_flag = False + this_suffix_length = 0 + # + if len(this_proc_piece) != 2048: + print(len(this_proc_piece)) + this_suffix_flag = True + # + while len(this_proc_piece) != 2048: + this_proc_piece = np.append(this_proc_piece, [0]) + this_suffix_length += 1 + # + this_proc_piece_fft = np.fft.fft(this_proc_piece, self.proc_fft_length) / (self.proc_fft_length) + # + this_base_freq, this_threshold_point = self.find_threshold_point(this_proc_piece_fft*2) + print("%sHZ %s" % (this_base_freq, this_threshold_point)) + # + this_proc_piece_fft = self.generate_jitter(this_proc_piece_fft, this_base_freq, this_threshold_point) + # + this_proc_piece_ifft = np.fft.ifft(this_proc_piece_fft, n=self.proc_fft_length) + # + this_proc_piece = this_proc_piece_ifft.real + # + this_append_length = self.proc_fft_length + if this_suffix_flag: + this_append_length -= this_suffix_length + # + this_output = np.append(this_output, this_proc_piece[0:this_append_length]) + return [this_output, index] def find_threshold_point(self, input_fft): # 鉴定频谱基本参数 @@ -145,7 +187,7 @@ def find_threshold_point(self, input_fft): break return base_amp_freq, fin_threshold_point - def generate_jitter(self, input_fft, fin_threshold_point, base_amp_freq): + def generate_jitter(self, input_fft, base_amp_freq, fin_threshold_point): # 构造抖动 if fin_threshold_point <= 0: return input_fft @@ -166,8 +208,7 @@ def generate_jitter(self, input_fft, fin_threshold_point, base_amp_freq): 1 if random.randint(0, 100000) < 50000 else 1 delta_jitter_value = random.uniform( base_jitter_min, base_jitter_max) + amp_jitter_prefix * random.uniform(amp_jitter_min, amp_jitter_max) - input_fft.real[ - i] += jitter_prefix * delta_jitter_value + input_fft.real[i] += jitter_prefix * delta_jitter_value return input_fft def save_file(self): @@ -179,109 +220,3 @@ def save_file(self): multiprocessing.freeze_support() EmiyaEngine("lossless_short.wav","lossless_test.wav") - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - From 84c5138a4e22840419a96cf38c7cca420c1d9293 Mon Sep 17 00:00:00 2001 From: Sg4Dylan Date: Mon, 27 Feb 2017 23:00:49 +0800 Subject: [PATCH 05/14] =?UTF-8?q?=E5=8A=A0=E5=85=A5=E7=BC=93=E5=86=B2?= =?UTF-8?q?=E5=8C=BA=EF=BC=8C=E4=BF=AE=E6=AD=A3=E9=95=BF=E5=BA=A6=E5=BC=82?= =?UTF-8?q?=E5=B8=B8=E7=9A=84=E9=97=AE=E9=A2=98=EF=BC=8C=E5=A4=A7=E7=BA=A6?= =?UTF-8?q?=E5=8F=AF=E4=BB=A5=E5=8A=A0=E9=80=9F0-3=E5=80=8D?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- EmiyaEngine.py | 56 ++++++++++++++++++++++++++++++++------------------ 1 file changed, 36 insertions(+), 20 deletions(-) diff --git a/EmiyaEngine.py b/EmiyaEngine.py index e87b48f..1e73405 100644 --- a/EmiyaEngine.py +++ b/EmiyaEngine.py @@ -73,7 +73,6 @@ def process_leader(self): self.input_sr, self.input_sr * self.proc_mid_sr_rate, filter='kaiser_fast') - print(len(pre_src_data)) # 分割时间域 splited_input_signal = np.array_split(pre_src_data, self.cpu_thread) for i in range(self.cpu_thread): @@ -91,7 +90,7 @@ def process_leader(self): # 追加分片 for i in range(self.cpu_thread): temp_array = np.append(temp_array, result_dict[i]) - print(len(temp_array)) + print("Whole length: before -> %s after -> %s" % (len(pre_src_data), len(temp_array))) # SRC 后处理 temp_src_array = resampy.resample(temp_array, self.input_sr * self.proc_mid_sr_rate, @@ -109,45 +108,61 @@ def process_leader(self): self.save_file() def process_core(self, signal_piece, index): - # + # 总长及分割数目 this_whole_length = len(signal_piece) this_div_count = round(this_whole_length/self.proc_fft_length) - # + # 输出数组 this_output = np.array([()]) + # 输出临时数组 + this_temp_block = np.array([()]) + this_temp_count = 0 + # 各分片运算 for i in range(this_div_count): - # + # 起始点 this_start_pos = i * self.proc_fft_length this_end_pos = i * self.proc_fft_length + self.proc_fft_length - # + # 当前分片 this_proc_piece = signal_piece[this_start_pos:this_end_pos] - # + # 待修正尾部指示及尾部补齐长度 this_suffix_flag = False this_suffix_length = 0 - # + # 真尾部指示 + this_tail_flag = False + if i == (this_div_count - 1): + this_tail_flag = True + # 尾部判定 if len(this_proc_piece) != 2048: - print(len(this_proc_piece)) this_suffix_flag = True - # + # 尾部补齐及长度记录 while len(this_proc_piece) != 2048: this_proc_piece = np.append(this_proc_piece, [0]) this_suffix_length += 1 - # + # FFT this_proc_piece_fft = np.fft.fft(this_proc_piece, self.proc_fft_length) / (self.proc_fft_length) - # + # 计算接续点及最大幅值 this_base_freq, this_threshold_point = self.find_threshold_point(this_proc_piece_fft*2) - print("%sHZ %s" % (this_base_freq, this_threshold_point)) - # + print("Max Amp -> %s Threshold point -> %s" % (this_base_freq, this_threshold_point)) + # 加抖动 this_proc_piece_fft = self.generate_jitter(this_proc_piece_fft, this_base_freq, this_threshold_point) - # + # IFFT this_proc_piece_ifft = np.fft.ifft(this_proc_piece_fft, n=self.proc_fft_length) - # + # 输出分片实部 this_proc_piece = this_proc_piece_ifft.real - # + # 计算最终输出长度 (尾部需要排除掉补零部分) this_append_length = self.proc_fft_length if this_suffix_flag: this_append_length -= this_suffix_length - # - this_output = np.append(this_output, this_proc_piece[0:this_append_length]) + # 直接追加到目标输出返回数组 + # this_output = np.append(this_output, this_proc_piece[0:this_append_length]) + # 使用缓冲区再输出返回 (内存消耗和上边的方法差不多,但是能稍微抵消掉 numpy 对大数组拼接的问题) + this_temp_block = np.append(this_temp_block, this_proc_piece[0:this_append_length]) + this_temp_count += 1 + # 尾部判定追加 + if this_temp_count > self.split_size or this_tail_flag: + this_output = np.append(this_output, this_temp_block) + this_temp_block = np.array([()]) + this_temp_count = 0 + return [this_output, index] def find_threshold_point(self, input_fft): @@ -218,5 +233,6 @@ def save_file(self): if __name__ == "__main__": multiprocessing.freeze_support() - EmiyaEngine("lossless_short.wav","lossless_test.wav") + # 输入文件路径, 输出文件路径 + EmiyaEngine("demi.mp3","demi-output.wav") From e5c8aea41e689d5b1da97a4cb18fee0a7acb87af Mon Sep 17 00:00:00 2001 From: Sg4Dylan Date: Thu, 2 Mar 2017 21:03:44 +0800 Subject: [PATCH 06/14] =?UTF-8?q?=E9=87=8D=E6=9E=84=E5=AF=BB=E6=89=BE?= =?UTF-8?q?=E6=8E=A5=E7=BB=AD=E7=82=B9=E5=92=8C=E6=9E=84=E9=80=A0=E6=8A=96?= =?UTF-8?q?=E5=8A=A8=E7=9A=84=E5=87=BD=E6=95=B0=EF=BC=8C=E6=A0=B8=E5=BF=83?= =?UTF-8?q?=E9=83=A8=E5=88=86=E9=87=8D=E6=9E=84=E5=AE=8C=E6=88=90?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- EmiyaEngine.py | 130 +++++++++++++++++++++++++++---------------------- README.md | 18 +++++-- 2 files changed, 87 insertions(+), 61 deletions(-) diff --git a/EmiyaEngine.py b/EmiyaEngine.py index 1e73405..a6c1fd0 100644 --- a/EmiyaEngine.py +++ b/EmiyaEngine.py @@ -30,18 +30,21 @@ class EmiyaEngine: mid_signal_rarray = '' mid_signal_carray = '' # 各进程处理参数 - proc_mid_sr_rate = 2 + proc_mid_sr_rate = 4 proc_fft_length = 2048 # 输出用参数 output_file_path = '' output_sr = 0 split_size = 500 - def __init__(self, input=None, output=None, output_sr=96000, split_size=500): + def __init__(self, input=None, output=None, output_sr=96000, split_size=500, cpu_thread=None): # 导入参数 if not input or not output: print("Missing parameters.") return + # 读取 CPU 线程数 + if not cpu_thread: + self.cpu_thread = multiprocessing.cpu_count() self.input_file_path = input self.output_file_path = output self.output_sr = output_sr @@ -57,8 +60,6 @@ def init_engine(self): self.input_file_path, sr=None, mono=False) print("Load signal complete. ChannelCount: %s SampleRate: %s Hz" % ( str(len(self.input_signal_array)), str(self.input_sr))) - # 读取 CPU 线程数 - self.cpu_thread = multiprocessing.cpu_count() def process_leader(self): # 左右声道 @@ -140,10 +141,10 @@ def process_core(self, signal_piece, index): # FFT this_proc_piece_fft = np.fft.fft(this_proc_piece, self.proc_fft_length) / (self.proc_fft_length) # 计算接续点及最大幅值 - this_base_freq, this_threshold_point = self.find_threshold_point(this_proc_piece_fft*2) - print("Max Amp -> %s Threshold point -> %s" % (this_base_freq, this_threshold_point)) + this_freq_thd, this_base_amp, this_threshold_point = self.find_threshold_point(this_proc_piece_fft*2) + # print("Max Amp -> %s Threshold point -> %s" % (this_base_freq, this_threshold_point)) # 加抖动 - this_proc_piece_fft = self.generate_jitter(this_proc_piece_fft, this_base_freq, this_threshold_point) + this_proc_piece_fft = self.generate_jitter(this_proc_piece_fft, this_freq_thd, this_base_amp, this_threshold_point) # IFFT this_proc_piece_ifft = np.fft.ifft(this_proc_piece_fft, n=self.proc_fft_length) # 输出分片实部 @@ -168,61 +169,74 @@ def process_core(self, signal_piece, index): def find_threshold_point(self, input_fft): # 鉴定频谱基本参数 amp_fft = abs(input_fft[range(self.proc_fft_length // 2)]) - # Step0. 找出基波幅度 - base_amp_freq = amp_fft.max() - # Step1. 找出接续的阈值 - threshold_hit = 1.0e-11 # 方差判定阈值 - fin_threshold_point = 0 # 最后的阈值点 - find_range = int((self.proc_fft_length / 2) - 1) # 搜索的范围 - start_find_pos = round(2000 / (self.input_sr / (self.proc_fft_length / 2))) # 从2K频点附近开始寻找,加快速度 - start_flag = True # 循环用的启动Flag - loop_count = 0 # 循环计数器 - legal_freq = (self.input_sr / 2) - 500 # 判定结果合法的阈值频率 - forward_freq = 3000 # 前向修正频率 - order_freq = (self.input_sr / 2) - 6000 # 钦定频率 - # Rev.1: 检查接续点是否符合常理 - while start_flag or fin_threshold_point > round(legal_freq / (self.input_sr / (self.proc_fft_length / 2))): - start_flag = False - if (fin_threshold_point * (self.input_sr / (self.proc_fft_length / 2))) > int(self.input_sr / 2): - threshold_hit *= 2 - for i in range(start_find_pos, find_range): - if i + 5 > find_range: - break - # 计算连续五个采样*3 的方差,与阈值比较,判断频谱消失的位置 - if np.var(amp_fft[i:i + 4]) < threshold_hit and \ - np.var(amp_fft[i + 1:i + 5]) < threshold_hit: - # 定位到当前位置的前500Hz位置 - fin_threshold_point = i - round(forward_freq / (self.input_sr / (self.proc_fft_length / 2))) - break - # 错误超过5把就强行钦定频率 - loop_count += 1 - if loop_count > 5: - fin_threshold_point = round( - order_freq / (self.input_sr / (self.proc_fft_length / 2))) + # Step0. 计算基波幅度及该幅度所在的位置 + base_amp = amp_fft.max() + base_amp_freq = np.argmax(amp_fft) + # Step0.1. 计算次峰对应的位置 + secondary_array = amp_fft + secondary_array[base_amp_freq] = 0 + secondary_amp = secondary_array.max() + secondary_amp_freq = np.argmax(secondary_array) + # Step1. 找出接续点的搜索范围 + fft_resolution = (self.proc_mid_sr_rate * self.input_sr / 2) / (self.proc_fft_length / 2) + hit_start = base_amp_freq * 2 + hit_end = int((self.input_sr / 2) / fft_resolution) + # Step1.1 计算保护阈值频率所在位置 + freq_thd = int(secondary_amp_freq*4 / fft_resolution) + # Setp2. 找出接续点 + threshold_hit = 8.0e-10 + fin_threshold_point = 0 + for hit_pos in range(hit_start, hit_end): + if hit_pos+6>1023: break - return base_amp_freq, fin_threshold_point - - def generate_jitter(self, input_fft, base_amp_freq, fin_threshold_point): - # 构造抖动 - if fin_threshold_point <= 0: + if np.var(amp_fft[hit_pos:hit_pos+4]) < threshold_hit and \ + np.var(amp_fft[hit_pos+1:hit_pos+5]) < threshold_hit and \ + np.var(amp_fft[hit_pos+2:hit_pos+6]) < threshold_hit: + fin_threshold_point = hit_pos - 3 + break + # Setp3. 检查接续点 + # Step3.1 检查最高电平是否达标 + threshold_amp = 7.45e-8 + if base_amp < threshold_amp: + fin_threshold_point = 0 + else: + # Step3.2 检查目标频率是否小于等于 0 + if fin_threshold_point <= 0: + if base_amp_freq != 0: + fin_threshold_point = hit_start * 3 # 钦定三次谐波位置 + else: + fin_threshold_point = secondary_amp_freq * 2 # 钦定二次谐波位置 + # 打印 DEBUG + print("AMP-> %s THD-> %s START-> %s END-> %s HIT_POINT-> %s " % (base_amp, freq_thd, hit_start, hit_end, fin_threshold_point)) + return freq_thd, base_amp, fin_threshold_point + + def generate_jitter(self, input_fft, freq_thd, base_amp, fin_threshold_point): + # 判定点为0时做忽略处理 + if fin_threshold_point == 0: return input_fft + # 插入抖动 for i in range(fin_threshold_point, self.proc_fft_length - fin_threshold_point): - # Rev.0: 调整生成概率,频率越高概率越低 - # Rev.1: 加入幅值判定,幅度越大概率越大 - gen_possible = abs((self.proc_fft_length / 2) - i) / ((self.proc_fft_length / - 2) - fin_threshold_point) * (base_amp_freq / 0.22) + # 生成概率,频率越高概率越低 + if fin_threshold_point >= freq_thd: + gen_possible = abs((self.proc_fft_length / 2) - i) / ((self.proc_fft_length / 2) - fin_threshold_point) + else: + if i > (self.proc_fft_length / 2): + gen_possible = (i - (self.proc_fft_length - freq_thd)) / (freq_thd - fin_threshold_point) + else: + gen_possible = (freq_thd - i) / (freq_thd - fin_threshold_point) if random.randint(0, 1000000) < 800000 * gen_possible: # 0<=x<=10 - real_value = abs(input_fft.real[i]) - base_jitter_min = real_value * 0.5 * (1 - gen_possible) - base_jitter_max = real_value * 6 * gen_possible - amp_jitter_min = base_amp_freq * real_value * 0.5 - amp_jitter_max = base_amp_freq * real_value * 2 - amp_jitter_prefix = - \ - 1 if random.randint(0, 100000) < 50000 else 1 - jitter_prefix = - \ - 1 if random.randint(0, 100000) < 50000 else 1 - delta_jitter_value = random.uniform( - base_jitter_min, base_jitter_max) + amp_jitter_prefix * random.uniform(amp_jitter_min, amp_jitter_max) + # 计算基础抖动范围 + base_jitter_delta = abs(input_fft.real[i]) + base_jitter_min = base_jitter_delta * 0.15 * (1 - gen_possible) + base_jitter_max = base_jitter_delta * 1.75 * gen_possible + # 根据基波电平的额外抖动 + amp_jitter_min = base_amp * base_jitter_delta * 0.05 + amp_jitter_max = base_amp * base_jitter_delta * 1.5 + # 随机正负号添加 + amp_jitter_prefix = -1 if random.randint(0, 100000) < 50000 else 1 + jitter_prefix = - 1 if random.randint(0, 100000) < 50000 else 1 + # 加入抖动 + delta_jitter_value = random.uniform(base_jitter_min, base_jitter_max) + amp_jitter_prefix * random.uniform(amp_jitter_min, amp_jitter_max) input_fft.real[i] += jitter_prefix * delta_jitter_value return input_fft diff --git a/README.md b/README.md index b104c52..c530507 100644 --- a/README.md +++ b/README.md @@ -13,12 +13,24 @@ Emiya Engine 是一个用来丰富音频频谱的脚本。可以将频谱变得 Alpha.1 Rev.0 ~~终于 Alpha.1 了~~ +###使用注意 +新架构已采用多进程并行处理。在数据未处理完成前,数据将占用大量内存。 +没有 16GB 以上物理内存的机器,请尝试降低 proc_mid_sr_rate (不低于2), +或者初始化类加入 cpu_thread 参数指定使用的进程数量 (不包含主进程)。 +作者听歌去了,觉得有意思就点个 star 吧。 + +###已经做的: + + - 重构程序结构 + - 改成多进程处理结构 + ###接下来做的: - - 重构原有程序结构 (进行中) - - 改成多进程处理结构(目前还不知道和现有 GUI 会发生怎样的碰撞) + - 测试消除掉可以听见的噪音 + - 构建 GUI 界面 -###当前改进思路: +###当前改进思路(已经完成): + 提高因采样点数不足而下降的 FFT 精度: 对低采样点数做时域重采样。 From fae1d9349c11e69e3aff6a9d5db4e6d8a5d4743a Mon Sep 17 00:00:00 2001 From: Sg4Dylan Date: Thu, 2 Mar 2017 21:05:14 +0800 Subject: [PATCH 07/14] =?UTF-8?q?=E5=8A=A0=E4=B8=80=E4=B8=AA=E6=8D=A2?= =?UTF-8?q?=E8=A1=8C?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index c530507..41b65f7 100644 --- a/README.md +++ b/README.md @@ -16,7 +16,7 @@ Alpha.1 Rev.0 ###使用注意 新架构已采用多进程并行处理。在数据未处理完成前,数据将占用大量内存。 没有 16GB 以上物理内存的机器,请尝试降低 proc_mid_sr_rate (不低于2), -或者初始化类加入 cpu_thread 参数指定使用的进程数量 (不包含主进程)。 +或者初始化类加入 cpu_thread 参数指定使用的进程数量 (不包含主进程)。 作者听歌去了,觉得有意思就点个 star 吧。 ###已经做的: From aa3931b1ba48c7934fe8cffec0a2ac94fc572bac Mon Sep 17 00:00:00 2001 From: Sg4Dylan Date: Thu, 2 Mar 2017 21:41:13 +0800 Subject: [PATCH 08/14] =?UTF-8?q?=E4=B8=80=E7=82=B9=E5=BE=AE=E5=B0=8F?= =?UTF-8?q?=E7=9A=84=E5=B7=A5=E4=BD=9C?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- EmiyaEngine.py | 13 ++++++++----- demi-output.wav | Bin 0 -> 5046330 bytes demi.mp3 | Bin 0 -> 638188 bytes 3 files changed, 8 insertions(+), 5 deletions(-) create mode 100644 demi-output.wav create mode 100644 demi.mp3 diff --git a/EmiyaEngine.py b/EmiyaEngine.py index a6c1fd0..29334b0 100644 --- a/EmiyaEngine.py +++ b/EmiyaEngine.py @@ -30,7 +30,7 @@ class EmiyaEngine: mid_signal_rarray = '' mid_signal_carray = '' # 各进程处理参数 - proc_mid_sr_rate = 4 + proc_mid_sr_rate = 16 proc_fft_length = 2048 # 输出用参数 output_file_path = '' @@ -176,13 +176,13 @@ def find_threshold_point(self, input_fft): secondary_array = amp_fft secondary_array[base_amp_freq] = 0 secondary_amp = secondary_array.max() - secondary_amp_freq = np.argmax(secondary_array) + secondary_amp_freq = np.argmax(secondary_array) + 1 # Step1. 找出接续点的搜索范围 fft_resolution = (self.proc_mid_sr_rate * self.input_sr / 2) / (self.proc_fft_length / 2) hit_start = base_amp_freq * 2 hit_end = int((self.input_sr / 2) / fft_resolution) # Step1.1 计算保护阈值频率所在位置 - freq_thd = int(secondary_amp_freq*4 / fft_resolution) + freq_thd = secondary_amp_freq * 2 # Setp2. 找出接续点 threshold_hit = 8.0e-10 fin_threshold_point = 0 @@ -225,10 +225,13 @@ def generate_jitter(self, input_fft, freq_thd, base_amp, fin_threshold_point): else: gen_possible = (freq_thd - i) / (freq_thd - fin_threshold_point) if random.randint(0, 1000000) < 800000 * gen_possible: # 0<=x<=10 + # 基础范围倍率 + base_jitter_rate = [0.15,1.75] # 适用于乐器纯音乐、古典乐、轻音乐(频谱不是特别亮) + # base_jitter_rate = [0.7,2.5] # 适用于流行乐、电子乐、摇滚乐(频谱亮且充满理论范围) # 计算基础抖动范围 base_jitter_delta = abs(input_fft.real[i]) - base_jitter_min = base_jitter_delta * 0.15 * (1 - gen_possible) - base_jitter_max = base_jitter_delta * 1.75 * gen_possible + base_jitter_min = base_jitter_delta * base_jitter_rate[0] * (1 - gen_possible) + base_jitter_max = base_jitter_delta * base_jitter_rate[1] * gen_possible # 根据基波电平的额外抖动 amp_jitter_min = base_amp * base_jitter_delta * 0.05 amp_jitter_max = base_amp * base_jitter_delta * 1.5 diff --git a/demi-output.wav b/demi-output.wav new file mode 100644 index 0000000000000000000000000000000000000000..e686e814a355bc692e706d779126549a4a407a7f GIT binary patch literal 5046330 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