VANILA_+Make_spectogram+save_to_csv.ipynb 77.8 KB
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\n평가방법 : positive를 높이는방식\\n\\n본논문\\n- STFT magnitude Spectrun\\n- n=40 log mel filter bank\\n\\n다른논문\\n-STFT maginitude spectogram\\n- n=80 mel scaled filter bank\\n- scale log magnitude\\n- batch nomalization (0,1)\\n- subtract mean overtime on spectogram (for remove frequency dependency noise = colored noise)\\n'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''\n",
    "평가방법 : positive를 높이는방식\n",
    "\n",
    "본논문\n",
    "- STFT magnitude Spectrun\n",
    "- n=40 log mel filter bank\n",
    "\n",
    "다른논문\n",
    "-STFT maginitude spectogram\n",
    "- n=80 mel scaled filter bank\n",
    "- scale log magnitude\n",
    "- batch nomalization (0,1)\n",
    "- subtract mean overtime on spectogram (for remove frequency dependency noise = colored noise)\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "#path 관련 라이브러리\n",
    "import glob\n",
    "import csv\n",
    "\n",
    "#csv저장 라이브러리\n",
    "import pandas as pd\n",
    "\n",
    "# Scientific Math 라이브러리  \n",
    "import numpy as np\n",
    "import librosa\n",
    "import librosa.display\n",
    "import os\n",
    "\n",
    "# Visualization 라이브러리\n",
    "import matplotlib.pyplot as plt\n",
    "import IPython.display as ipd\n",
    "\n",
    "#keras\n",
    "from keras.utils import np_utils\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Dense, Conv2D, MaxPooling2D, GRU,Dropout, Flatten,Reshape,BatchNormalization\n",
    "from keras.callbacks import ModelCheckpoint, EarlyStopping\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "audio_path = './SOUNDS/warbler/'\n",
    "n_mels = 40\n",
    "n_frame = 500\n",
    "window_size=1024\n",
    "hop_size=512\n",
    "sample_rate=25600\n",
    "num_file = 0 #데이터갯수 이후에 덮어씌워짐"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Preparing file lists.\n",
      "Done.\n",
      "45\n"
     ]
    }
   ],
   "source": [
    "#prepare labels\n",
    "labels = []\n",
    "with open(audio_path+'labels.csv', mode='r',encoding='utf-8') as f:\n",
    "    reader = csv.reader(f)\n",
    "    for row in reader : \n",
    "        labels.append(row)\n",
    "labels.sort(key=lambda x:x[0])\n",
    "labels = np.array(labels) \n",
    "labels = labels[0:-1,1]\n",
    "\n",
    "# prepare file lists\n",
    "print(\"Preparing file lists.\")\n",
    "dirs = []\n",
    "for filename in glob.glob(audio_path+'wav/'+'*.wav'):\n",
    "    dirs.append(filename)\n",
    "dirs.sort()\n",
    "print(\"Done.\")\n",
    "\n",
    "num_file = len(dirs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#librosa spectogram_Checking\n",
    "\n",
    "S=librosa.feature.melspectrogram(y=y, sr=sr,n_fft=window_size, hop_length=hop_size, power=2.0, n_mels=40)\n",
    "S=S[:,0:500]\n",
    "\n",
    "plt.figure(figsize=(10,4))\n",
    "librosa.display.specshow(librosa.power_to_db(S,ref=np.max),y_axis='mel',x_axis='time')\n",
    "plt.colorbar(format='%+2.0f dB')\n",
    "plt.title('Mel Spectogram')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "making mel_spectogram.\n",
      "1000\n",
      "2000\n",
      "3000\n",
      "4000\n",
      "5000\n",
      "6000\n",
      "7000\n",
      "8000\n"
     ]
    }
   ],
   "source": [
    "print('making mel_spectogram.')\n",
    "mel_spectogram = []\n",
    "count = 0\n",
    "for direct in dirs:\n",
    "    y,sr=librosa.core.load(direct,sr=sample_rate)\n",
    "    S=librosa.feature.melspectrogram(y=y, sr=sr,n_fft=window_size, hop_length=hop_size, power=2.0, n_mels=40)\n",
    "    if np.shape(S)[1]<500 : \n",
    "        S = np.concatenate((S,S),axis=1)\n",
    "    S=S[:,0:500]     \n",
    "    mel_spectogram.append(S)\n",
    "    count= count+1\n",
    "    if(count%1000==0) :\n",
    "        print(count)\n",
    "print('done')\n",
    "\n",
    "#np배열로 바꿔줌\n",
    "mel_spectogram=np.array(mel_spectogram)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "581\n",
      "2451\n",
      "4721\n",
      "5115\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(40, 98)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 10초 이하인거는 반복해서  10초로 길이 늘려주기\n",
    "for i in range(0,num_file) : \n",
    "    if np.shape(mel_spectogram[i])[1] != 500:\n",
    "        mel_spectogram[i] = np.concatenate((mel_spectogram[i],mel_spectogram[i]),axis=1)\n",
    "        mel_spectogram[i] = np.concatenate((mel_spectogram[i],mel_spectogram[i]),axis=1)\n",
    "        mel_spectogram[i] = (mel_spectogram[i]) [:,0:500]\n",
    "        np.shape(mel_spectogram[i])\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "#csv파일로 저장하려고 2차원배월로 만듬\n",
    "mel_spectogram=np.reshape(mel_spectogram,(np.shape(mel_spectogram)[0],-1))\n",
    "df = pd.DataFrame(mel_spectogram[0:num_file,:])\n",
    "df.to_csv(audio_path+\"/mel_spec.csv\")\n",
    "\n",
    "if(np.shape(labels)[0]!=num_file) :\n",
    "    print('something wrong')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}