notebook_final.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "73e98ba2-3a44-4719-af2c-fe4b10a3974f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from pathlib import Path\n",
    "import IPython.display as ipd\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import librosa \n",
    "import sklearn \n",
    "import sklearn.preprocessing as skp\n",
    "\n",
    "from joblib import dump, load\n",
    "\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import tensorflow as tf \n",
    "from tensorflow import keras\n",
    "plt.style.use('default')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6316b880-283f-4189-be02-6e704fe4b20a",
   "metadata": {},
   "source": [
    "**NB: use the following part of the code only if you want to select another data instance from the dataset**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "d14d4e91-eba6-4d20-b32a-6cb8c34d89d4",
   "metadata": {},
   "outputs": [
    {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>filename</th>\n",
       "      <th>length</th>\n",
       "      <th>chroma_stft_mean</th>\n",
       "      <th>chroma_stft_var</th>\n",
       "      <th>rms_mean</th>\n",
       "      <th>rms_var</th>\n",
       "      <th>spectral_centroid_mean</th>\n",
       "      <th>spectral_centroid_var</th>\n",
       "      <th>spectral_bandwidth_mean</th>\n",
       "      <th>spectral_bandwidth_var</th>\n",
       "      <th>...</th>\n",
       "      <th>mfcc16_var</th>\n",
       "      <th>mfcc17_mean</th>\n",
       "      <th>mfcc17_var</th>\n",
       "      <th>mfcc18_mean</th>\n",
       "      <th>mfcc18_var</th>\n",
       "      <th>mfcc19_mean</th>\n",
       "      <th>mfcc19_var</th>\n",
       "      <th>mfcc20_mean</th>\n",
       "      <th>mfcc20_var</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>blues.00000.wav</td>\n",
       "      <td>661794</td>\n",
       "      <td>0.350088</td>\n",
       "      <td>0.088757</td>\n",
       "      <td>0.130228</td>\n",
       "      <td>0.002827</td>\n",
       "      <td>1784.165850</td>\n",
       "      <td>129774.064525</td>\n",
       "      <td>2002.449060</td>\n",
       "      <td>85882.761315</td>\n",
       "      <td>...</td>\n",
       "      <td>52.420910</td>\n",
       "      <td>-1.690215</td>\n",
       "      <td>36.524071</td>\n",
       "      <td>-0.408979</td>\n",
       "      <td>41.597103</td>\n",
       "      <td>-2.303523</td>\n",
       "      <td>55.062923</td>\n",
       "      <td>1.221291</td>\n",
       "      <td>46.936035</td>\n",
       "      <td>blues</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>blues.00001.wav</td>\n",
       "      <td>661794</td>\n",
       "      <td>0.340914</td>\n",
       "      <td>0.094980</td>\n",
       "      <td>0.095948</td>\n",
       "      <td>0.002373</td>\n",
       "      <td>1530.176679</td>\n",
       "      <td>375850.073649</td>\n",
       "      <td>2039.036516</td>\n",
       "      <td>213843.755497</td>\n",
       "      <td>...</td>\n",
       "      <td>55.356403</td>\n",
       "      <td>-0.731125</td>\n",
       "      <td>60.314529</td>\n",
       "      <td>0.295073</td>\n",
       "      <td>48.120598</td>\n",
       "      <td>-0.283518</td>\n",
       "      <td>51.106190</td>\n",
       "      <td>0.531217</td>\n",
       "      <td>45.786282</td>\n",
       "      <td>blues</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>blues.00002.wav</td>\n",
       "      <td>661794</td>\n",
       "      <td>0.363637</td>\n",
       "      <td>0.085275</td>\n",
       "      <td>0.175570</td>\n",
       "      <td>0.002746</td>\n",
       "      <td>1552.811865</td>\n",
       "      <td>156467.643368</td>\n",
       "      <td>1747.702312</td>\n",
       "      <td>76254.192257</td>\n",
       "      <td>...</td>\n",
       "      <td>40.598766</td>\n",
       "      <td>-7.729093</td>\n",
       "      <td>47.639427</td>\n",
       "      <td>-1.816407</td>\n",
       "      <td>52.382141</td>\n",
       "      <td>-3.439720</td>\n",
       "      <td>46.639660</td>\n",
       "      <td>-2.231258</td>\n",
       "      <td>30.573025</td>\n",
       "      <td>blues</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>blues.00003.wav</td>\n",
       "      <td>661794</td>\n",
       "      <td>0.404785</td>\n",
       "      <td>0.093999</td>\n",
       "      <td>0.141093</td>\n",
       "      <td>0.006346</td>\n",
       "      <td>1070.106615</td>\n",
       "      <td>184355.942417</td>\n",
       "      <td>1596.412872</td>\n",
       "      <td>166441.494769</td>\n",
       "      <td>...</td>\n",
       "      <td>44.427753</td>\n",
       "      <td>-3.319597</td>\n",
       "      <td>50.206673</td>\n",
       "      <td>0.636965</td>\n",
       "      <td>37.319130</td>\n",
       "      <td>-0.619121</td>\n",
       "      <td>37.259739</td>\n",
       "      <td>-3.407448</td>\n",
       "      <td>31.949339</td>\n",
       "      <td>blues</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>blues.00004.wav</td>\n",
       "      <td>661794</td>\n",
       "      <td>0.308526</td>\n",
       "      <td>0.087841</td>\n",
       "      <td>0.091529</td>\n",
       "      <td>0.002303</td>\n",
       "      <td>1835.004266</td>\n",
       "      <td>343399.939274</td>\n",
       "      <td>1748.172116</td>\n",
       "      <td>88445.209036</td>\n",
       "      <td>...</td>\n",
       "      <td>86.099236</td>\n",
       "      <td>-5.454034</td>\n",
       "      <td>75.269707</td>\n",
       "      <td>-0.916874</td>\n",
       "      <td>53.613918</td>\n",
       "      <td>-4.404827</td>\n",
       "      <td>62.910812</td>\n",
       "      <td>-11.703234</td>\n",
       "      <td>55.195160</td>\n",
       "      <td>blues</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 60 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          filename  length  chroma_stft_mean  chroma_stft_var  rms_mean  \\\n",
       "0  blues.00000.wav  661794          0.350088         0.088757  0.130228   \n",
       "1  blues.00001.wav  661794          0.340914         0.094980  0.095948   \n",
       "2  blues.00002.wav  661794          0.363637         0.085275  0.175570   \n",
       "3  blues.00003.wav  661794          0.404785         0.093999  0.141093   \n",
       "4  blues.00004.wav  661794          0.308526         0.087841  0.091529   \n",
       "\n",
       "    rms_var  spectral_centroid_mean  spectral_centroid_var  \\\n",
       "0  0.002827             1784.165850          129774.064525   \n",
       "1  0.002373             1530.176679          375850.073649   \n",
       "2  0.002746             1552.811865          156467.643368   \n",
       "3  0.006346             1070.106615          184355.942417   \n",
       "4  0.002303             1835.004266          343399.939274   \n",
       "\n",
       "   spectral_bandwidth_mean  spectral_bandwidth_var  ...  mfcc16_var  \\\n",
       "0              2002.449060            85882.761315  ...   52.420910   \n",
       "1              2039.036516           213843.755497  ...   55.356403   \n",
       "2              1747.702312            76254.192257  ...   40.598766   \n",
       "3              1596.412872           166441.494769  ...   44.427753   \n",
       "4              1748.172116            88445.209036  ...   86.099236   \n",
       "\n",
       "   mfcc17_mean  mfcc17_var  mfcc18_mean  mfcc18_var  mfcc19_mean  mfcc19_var  \\\n",
       "0    -1.690215   36.524071    -0.408979   41.597103    -2.303523   55.062923   \n",
       "1    -0.731125   60.314529     0.295073   48.120598    -0.283518   51.106190   \n",
       "2    -7.729093   47.639427    -1.816407   52.382141    -3.439720   46.639660   \n",
       "3    -3.319597   50.206673     0.636965   37.319130    -0.619121   37.259739   \n",
       "4    -5.454034   75.269707    -0.916874   53.613918    -4.404827   62.910812   \n",
       "\n",
       "   mfcc20_mean  mfcc20_var  label  \n",
       "0     1.221291   46.936035  blues  \n",
       "1     0.531217   45.786282  blues  \n",
       "2    -2.231258   30.573025  blues  \n",
       "3    -3.407448   31.949339  blues  \n",
       "4   -11.703234   55.195160  blues  \n",
       "\n",
       "[5 rows x 60 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_folder_path = 'Data/'\n",
    "\n",
    "dataset = pd.read_csv(data_folder_path + 'features_30_sec.csv')\n",
    "\n",
    "dataset.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e75c8823-7fb4-4ebc-aaff-bc2e17512dc7",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset.drop(['filename', 'length'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "b27b5701-5e3e-4e90-8105-d127dbaaaed3",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset = dataset.sample(frac=1, random_state=42).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "9c6be6cc-1611-45d8-83b5-c64c78522e54",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chroma_stft_mean</th>\n",
       "      <th>chroma_stft_var</th>\n",
       "      <th>rms_mean</th>\n",
       "      <th>rms_var</th>\n",
       "      <th>spectral_centroid_mean</th>\n",
       "      <th>spectral_centroid_var</th>\n",
       "      <th>spectral_bandwidth_mean</th>\n",
       "      <th>spectral_bandwidth_var</th>\n",
       "      <th>rolloff_mean</th>\n",
       "      <th>rolloff_var</th>\n",
       "      <th>...</th>\n",
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       "      <th>mfcc17_mean</th>\n",
       "      <th>mfcc17_var</th>\n",
       "      <th>mfcc18_mean</th>\n",
       "      <th>mfcc18_var</th>\n",
       "      <th>mfcc19_mean</th>\n",
       "      <th>mfcc19_var</th>\n",
       "      <th>mfcc20_mean</th>\n",
       "      <th>mfcc20_var</th>\n",
       "      <th>label</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.432707</td>\n",
       "      <td>0.087017</td>\n",
       "      <td>0.047977</td>\n",
       "      <td>0.000411</td>\n",
       "      <td>2915.017702</td>\n",
       "      <td>465988.571671</td>\n",
       "      <td>2420.421212</td>\n",
       "      <td>55397.978934</td>\n",
       "      <td>5864.933419</td>\n",
       "      <td>1.067012e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>52.428093</td>\n",
       "      <td>-6.002379</td>\n",
       "      <td>44.046604</td>\n",
       "      <td>2.347543</td>\n",
       "      <td>57.231190</td>\n",
       "      <td>-3.352306</td>\n",
       "      <td>68.406425</td>\n",
       "      <td>2.508936</td>\n",
       "      <td>58.562813</td>\n",
       "      <td>jazz</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.451825</td>\n",
       "      <td>0.085256</td>\n",
       "      <td>0.240985</td>\n",
       "      <td>0.008035</td>\n",
       "      <td>3238.215472</td>\n",
       "      <td>635263.200965</td>\n",
       "      <td>2954.126414</td>\n",
       "      <td>167148.237400</td>\n",
       "      <td>6701.364299</td>\n",
       "      <td>2.241874e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>47.259617</td>\n",
       "      <td>-2.177770</td>\n",
       "      <td>38.882034</td>\n",
       "      <td>-1.600560</td>\n",
       "      <td>51.832035</td>\n",
       "      <td>-0.616253</td>\n",
       "      <td>57.315872</td>\n",
       "      <td>-4.048588</td>\n",
       "      <td>53.083454</td>\n",
       "      <td>pop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.292264</td>\n",
       "      <td>0.085571</td>\n",
       "      <td>0.199328</td>\n",
       "      <td>0.005632</td>\n",
       "      <td>1962.036801</td>\n",
       "      <td>261307.494531</td>\n",
       "      <td>2325.013206</td>\n",
       "      <td>179382.875864</td>\n",
       "      <td>3820.419899</td>\n",
       "      <td>1.860261e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>72.924728</td>\n",
       "      <td>-0.548955</td>\n",
       "      <td>78.905830</td>\n",
       "      <td>-0.568484</td>\n",
       "      <td>87.446632</td>\n",
       "      <td>0.643941</td>\n",
       "      <td>66.528664</td>\n",
       "      <td>-1.999727</td>\n",
       "      <td>107.257652</td>\n",
       "      <td>pop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.540349</td>\n",
       "      <td>0.059563</td>\n",
       "      <td>0.125761</td>\n",
       "      <td>0.000635</td>\n",
       "      <td>2315.317248</td>\n",
       "      <td>115250.776839</td>\n",
       "      <td>2066.651952</td>\n",
       "      <td>37095.019096</td>\n",
       "      <td>4615.982658</td>\n",
       "      <td>4.207177e+05</td>\n",
       "      <td>...</td>\n",
       "      <td>21.919737</td>\n",
       "      <td>-6.810860</td>\n",
       "      <td>24.919960</td>\n",
       "      <td>4.214549</td>\n",
       "      <td>15.420555</td>\n",
       "      <td>-3.401198</td>\n",
       "      <td>20.339085</td>\n",
       "      <td>1.762156</td>\n",
       "      <td>17.411707</td>\n",
       "      <td>metal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.444012</td>\n",
       "      <td>0.085203</td>\n",
       "      <td>0.203773</td>\n",
       "      <td>0.006599</td>\n",
       "      <td>2095.420824</td>\n",
       "      <td>430313.487168</td>\n",
       "      <td>2241.060906</td>\n",
       "      <td>110796.012282</td>\n",
       "      <td>4581.850948</td>\n",
       "      <td>1.717499e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>76.894180</td>\n",
       "      <td>-2.812528</td>\n",
       "      <td>101.614967</td>\n",
       "      <td>6.798242</td>\n",
       "      <td>107.964317</td>\n",
       "      <td>-5.803802</td>\n",
       "      <td>103.876694</td>\n",
       "      <td>-3.767237</td>\n",
       "      <td>92.247749</td>\n",
       "      <td>hiphop</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 58 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   chroma_stft_mean  chroma_stft_var  rms_mean   rms_var  \\\n",
       "0          0.432707         0.087017  0.047977  0.000411   \n",
       "1          0.451825         0.085256  0.240985  0.008035   \n",
       "2          0.292264         0.085571  0.199328  0.005632   \n",
       "3          0.540349         0.059563  0.125761  0.000635   \n",
       "4          0.444012         0.085203  0.203773  0.006599   \n",
       "\n",
       "   spectral_centroid_mean  spectral_centroid_var  spectral_bandwidth_mean  \\\n",
       "0             2915.017702          465988.571671              2420.421212   \n",
       "1             3238.215472          635263.200965              2954.126414   \n",
       "2             1962.036801          261307.494531              2325.013206   \n",
       "3             2315.317248          115250.776839              2066.651952   \n",
       "4             2095.420824          430313.487168              2241.060906   \n",
       "\n",
       "   spectral_bandwidth_var  rolloff_mean   rolloff_var  ...  mfcc16_var  \\\n",
       "0            55397.978934   5864.933419  1.067012e+06  ...   52.428093   \n",
       "1           167148.237400   6701.364299  2.241874e+06  ...   47.259617   \n",
       "2           179382.875864   3820.419899  1.860261e+06  ...   72.924728   \n",
       "3            37095.019096   4615.982658  4.207177e+05  ...   21.919737   \n",
       "4           110796.012282   4581.850948  1.717499e+06  ...   76.894180   \n",
       "\n",
       "   mfcc17_mean  mfcc17_var  mfcc18_mean  mfcc18_var  mfcc19_mean  mfcc19_var  \\\n",
       "0    -6.002379   44.046604     2.347543   57.231190    -3.352306   68.406425   \n",
       "1    -2.177770   38.882034    -1.600560   51.832035    -0.616253   57.315872   \n",
       "2    -0.548955   78.905830    -0.568484   87.446632     0.643941   66.528664   \n",
       "3    -6.810860   24.919960     4.214549   15.420555    -3.401198   20.339085   \n",
       "4    -2.812528  101.614967     6.798242  107.964317    -5.803802  103.876694   \n",
       "\n",
       "   mfcc20_mean  mfcc20_var   label  \n",
       "0     2.508936   58.562813    jazz  \n",
       "1    -4.048588   53.083454     pop  \n",
       "2    -1.999727  107.257652     pop  \n",
       "3     1.762156   17.411707   metal  \n",
       "4    -3.767237   92.247749  hiphop  \n",
       "\n",
       "[5 rows x 58 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "14337cbc-f337-4757-b9c3-f79923892757",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'dataset' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[4], line 14\u001b[0m\n\u001b[1;32m      1\u001b[0m label_values \u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m      2\u001b[0m     \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mclassical\u001b[39m\u001b[38;5;124m'\u001b[39m: \u001b[38;5;241m0\u001b[39m, \n\u001b[1;32m      3\u001b[0m     \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mrock\u001b[39m\u001b[38;5;124m'\u001b[39m: \u001b[38;5;241m1\u001b[39m,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     11\u001b[0m     \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mhiphop\u001b[39m\u001b[38;5;124m'\u001b[39m: \u001b[38;5;241m9\u001b[39m\n\u001b[1;32m     12\u001b[0m }\n\u001b[0;32m---> 14\u001b[0m dataset\u001b[38;5;241m.\u001b[39mlabel \u001b[38;5;241m=\u001b[39m dataset\u001b[38;5;241m.\u001b[39mlabel\u001b[38;5;241m.\u001b[39mmap(label_values)\n",
      "\u001b[0;31mNameError\u001b[0m: name 'dataset' is not defined"
     ]
    }
   ],
   "source": [
    "label_values = {\n",
    "    'classical': 0, \n",
    "    'rock': 1,\n",
    "    'metal': 2,\n",
    "    'country': 3, \n",
    "    'jazz': 4, \n",
    "    'blues': 5, \n",
    "    'reggae': 6, \n",
    "    'disco': 7, \n",
    "    'pop': 8, \n",
    "    'hiphop': 9\n",
    "}\n",
    "\n",
    "dataset.label = dataset.label.map(label_values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "a070a213-355d-48c9-88c5-16c21fd14b01",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chroma_stft_mean</th>\n",
       "      <th>chroma_stft_var</th>\n",
       "      <th>rms_mean</th>\n",
       "      <th>rms_var</th>\n",
       "      <th>spectral_centroid_mean</th>\n",
       "      <th>spectral_centroid_var</th>\n",
       "      <th>spectral_bandwidth_mean</th>\n",
       "      <th>spectral_bandwidth_var</th>\n",
       "      <th>rolloff_mean</th>\n",
       "      <th>rolloff_var</th>\n",
       "      <th>...</th>\n",
       "      <th>mfcc16_var</th>\n",
       "      <th>mfcc17_mean</th>\n",
       "      <th>mfcc17_var</th>\n",
       "      <th>mfcc18_mean</th>\n",
       "      <th>mfcc18_var</th>\n",
       "      <th>mfcc19_mean</th>\n",
       "      <th>mfcc19_var</th>\n",
       "      <th>mfcc20_mean</th>\n",
       "      <th>mfcc20_var</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.432707</td>\n",
       "      <td>0.087017</td>\n",
       "      <td>0.047977</td>\n",
       "      <td>0.000411</td>\n",
       "      <td>2915.017702</td>\n",
       "      <td>465988.571671</td>\n",
       "      <td>2420.421212</td>\n",
       "      <td>55397.978934</td>\n",
       "      <td>5864.933419</td>\n",
       "      <td>1.067012e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>52.428093</td>\n",
       "      <td>-6.002379</td>\n",
       "      <td>44.046604</td>\n",
       "      <td>2.347543</td>\n",
       "      <td>57.231190</td>\n",
       "      <td>-3.352306</td>\n",
       "      <td>68.406425</td>\n",
       "      <td>2.508936</td>\n",
       "      <td>58.562813</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.451825</td>\n",
       "      <td>0.085256</td>\n",
       "      <td>0.240985</td>\n",
       "      <td>0.008035</td>\n",
       "      <td>3238.215472</td>\n",
       "      <td>635263.200965</td>\n",
       "      <td>2954.126414</td>\n",
       "      <td>167148.237400</td>\n",
       "      <td>6701.364299</td>\n",
       "      <td>2.241874e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>47.259617</td>\n",
       "      <td>-2.177770</td>\n",
       "      <td>38.882034</td>\n",
       "      <td>-1.600560</td>\n",
       "      <td>51.832035</td>\n",
       "      <td>-0.616253</td>\n",
       "      <td>57.315872</td>\n",
       "      <td>-4.048588</td>\n",
       "      <td>53.083454</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.292264</td>\n",
       "      <td>0.085571</td>\n",
       "      <td>0.199328</td>\n",
       "      <td>0.005632</td>\n",
       "      <td>1962.036801</td>\n",
       "      <td>261307.494531</td>\n",
       "      <td>2325.013206</td>\n",
       "      <td>179382.875864</td>\n",
       "      <td>3820.419899</td>\n",
       "      <td>1.860261e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>72.924728</td>\n",
       "      <td>-0.548955</td>\n",
       "      <td>78.905830</td>\n",
       "      <td>-0.568484</td>\n",
       "      <td>87.446632</td>\n",
       "      <td>0.643941</td>\n",
       "      <td>66.528664</td>\n",
       "      <td>-1.999727</td>\n",
       "      <td>107.257652</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.540349</td>\n",
       "      <td>0.059563</td>\n",
       "      <td>0.125761</td>\n",
       "      <td>0.000635</td>\n",
       "      <td>2315.317248</td>\n",
       "      <td>115250.776839</td>\n",
       "      <td>2066.651952</td>\n",
       "      <td>37095.019096</td>\n",
       "      <td>4615.982658</td>\n",
       "      <td>4.207177e+05</td>\n",
       "      <td>...</td>\n",
       "      <td>21.919737</td>\n",
       "      <td>-6.810860</td>\n",
       "      <td>24.919960</td>\n",
       "      <td>4.214549</td>\n",
       "      <td>15.420555</td>\n",
       "      <td>-3.401198</td>\n",
       "      <td>20.339085</td>\n",
       "      <td>1.762156</td>\n",
       "      <td>17.411707</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.444012</td>\n",
       "      <td>0.085203</td>\n",
       "      <td>0.203773</td>\n",
       "      <td>0.006599</td>\n",
       "      <td>2095.420824</td>\n",
       "      <td>430313.487168</td>\n",
       "      <td>2241.060906</td>\n",
       "      <td>110796.012282</td>\n",
       "      <td>4581.850948</td>\n",
       "      <td>1.717499e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>76.894180</td>\n",
       "      <td>-2.812528</td>\n",
       "      <td>101.614967</td>\n",
       "      <td>6.798242</td>\n",
       "      <td>107.964317</td>\n",
       "      <td>-5.803802</td>\n",
       "      <td>103.876694</td>\n",
       "      <td>-3.767237</td>\n",
       "      <td>92.247749</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 58 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   chroma_stft_mean  chroma_stft_var  rms_mean   rms_var  \\\n",
       "0          0.432707         0.087017  0.047977  0.000411   \n",
       "1          0.451825         0.085256  0.240985  0.008035   \n",
       "2          0.292264         0.085571  0.199328  0.005632   \n",
       "3          0.540349         0.059563  0.125761  0.000635   \n",
       "4          0.444012         0.085203  0.203773  0.006599   \n",
       "\n",
       "   spectral_centroid_mean  spectral_centroid_var  spectral_bandwidth_mean  \\\n",
       "0             2915.017702          465988.571671              2420.421212   \n",
       "1             3238.215472          635263.200965              2954.126414   \n",
       "2             1962.036801          261307.494531              2325.013206   \n",
       "3             2315.317248          115250.776839              2066.651952   \n",
       "4             2095.420824          430313.487168              2241.060906   \n",
       "\n",
       "   spectral_bandwidth_var  rolloff_mean   rolloff_var  ...  mfcc16_var  \\\n",
       "0            55397.978934   5864.933419  1.067012e+06  ...   52.428093   \n",
       "1           167148.237400   6701.364299  2.241874e+06  ...   47.259617   \n",
       "2           179382.875864   3820.419899  1.860261e+06  ...   72.924728   \n",
       "3            37095.019096   4615.982658  4.207177e+05  ...   21.919737   \n",
       "4           110796.012282   4581.850948  1.717499e+06  ...   76.894180   \n",
       "\n",
       "   mfcc17_mean  mfcc17_var  mfcc18_mean  mfcc18_var  mfcc19_mean  mfcc19_var  \\\n",
       "0    -6.002379   44.046604     2.347543   57.231190    -3.352306   68.406425   \n",
       "1    -2.177770   38.882034    -1.600560   51.832035    -0.616253   57.315872   \n",
       "2    -0.548955   78.905830    -0.568484   87.446632     0.643941   66.528664   \n",
       "3    -6.810860   24.919960     4.214549   15.420555    -3.401198   20.339085   \n",
       "4    -2.812528  101.614967     6.798242  107.964317    -5.803802  103.876694   \n",
       "\n",
       "   mfcc20_mean  mfcc20_var  label  \n",
       "0     2.508936   58.562813      4  \n",
       "1    -4.048588   53.083454      8  \n",
       "2    -1.999727  107.257652      8  \n",
       "3     1.762156   17.411707      2  \n",
       "4    -3.767237   92.247749      9  \n",
       "\n",
       "[5 rows x 58 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "1c6a7adf-35bd-462e-9b49-498b826a494d",
   "metadata": {},
   "outputs": [],
   "source": [
    "genres = [\n",
    "    'classical',\n",
    "    'rock',\n",
    "    'metal',\n",
    "    'country',\n",
    "    'jazz',\n",
    "    'blues',\n",
    "    'reggae',\n",
    "    'disco',\n",
    "    'pop',\n",
    "    'hiphop'\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "4140a9e5-1ebd-4034-bf0f-f031885668f2",
   "metadata": {},
   "outputs": [],
   "source": [
    "features = [\n",
    "        'chroma_stft_mean', 'chroma_stft_var', 'rms_mean',\n",
    "       'rms_var', 'spectral_centroid_mean', 'spectral_centroid_var',\n",
    "       'spectral_bandwidth_mean', 'spectral_bandwidth_var', 'rolloff_mean',\n",
    "       'rolloff_var', 'zero_crossing_rate_mean', 'zero_crossing_rate_var',\n",
    "       'harmony_mean', 'harmony_var', 'perceptr_mean', 'perceptr_var', 'tempo',\n",
    "       'mfcc1_mean', 'mfcc1_var', 'mfcc2_mean', 'mfcc2_var', 'mfcc3_mean',\n",
    "       'mfcc3_var', 'mfcc4_mean', 'mfcc4_var', 'mfcc5_mean', 'mfcc5_var',\n",
    "       'mfcc6_mean', 'mfcc6_var', 'mfcc7_mean', 'mfcc7_var', 'mfcc8_mean',\n",
    "       'mfcc8_var', 'mfcc9_mean', 'mfcc9_var', 'mfcc10_mean', 'mfcc10_var',\n",
    "       'mfcc11_mean', 'mfcc11_var', 'mfcc12_mean', 'mfcc12_var', 'mfcc13_mean',\n",
    "       'mfcc13_var', 'mfcc14_mean', 'mfcc14_var', 'mfcc15_mean', 'mfcc15_var',\n",
    "       'mfcc16_mean', 'mfcc16_var', 'mfcc17_mean', 'mfcc17_var', 'mfcc18_mean',\n",
    "       'mfcc18_var', 'mfcc19_mean', 'mfcc19_var', 'mfcc20_mean', 'mfcc20_var'\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "7e30a0ec-6b91-47e7-b2c0-077af843c3ea",
   "metadata": {},
   "outputs": [],
   "source": [
    "song = dataset.iloc[4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "76b8ce36-e05d-41a6-870e-f4ff62db2160",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'chroma_stft_mean': 0.4440117478370666,\n",
       " 'chroma_stft_var': 0.0852029994130134,\n",
       " 'rms_mean': 0.2037734985351562,\n",
       " 'rms_var': 0.00659936433658,\n",
       " 'spectral_centroid_mean': 2095.4208239067048,\n",
       " 'spectral_centroid_var': 430313.48716756655,\n",
       " 'spectral_bandwidth_mean': 2241.060906256248,\n",
       " 'spectral_bandwidth_var': 110796.01228164523,\n",
       " 'rolloff_mean': 4581.850948466502,\n",
       " 'rolloff_var': 1717499.435882924,\n",
       " 'zero_crossing_rate_mean': 0.0941514253431941,\n",
       " 'zero_crossing_rate_var': 0.003422177139843,\n",
       " 'harmony_mean': -3.053571708733216e-05,\n",
       " 'harmony_var': 0.0202102083712816,\n",
       " 'perceptr_mean': -0.001146224560216,\n",
       " 'perceptr_var': 0.0124355517327785,\n",
       " 'tempo': 135.99917763157896,\n",
       " 'mfcc1_mean': -74.18608856201172,\n",
       " 'mfcc1_var': 2630.19384765625,\n",
       " 'mfcc2_mean': 104.59842681884766,\n",
       " 'mfcc2_var': 672.80517578125,\n",
       " 'mfcc3_mean': -8.379661560058594,\n",
       " 'mfcc3_var': 544.7293090820312,\n",
       " 'mfcc4_mean': 49.65111541748047,\n",
       " 'mfcc4_var': 280.70770263671875,\n",
       " 'mfcc5_mean': -9.369983673095703,\n",
       " 'mfcc5_var': 164.64053344726562,\n",
       " 'mfcc6_mean': 21.44277572631836,\n",
       " 'mfcc6_var': 137.95318603515625,\n",
       " 'mfcc7_mean': -16.32986831665039,\n",
       " 'mfcc7_var': 144.6834259033203,\n",
       " 'mfcc8_mean': 18.780681610107425,\n",
       " 'mfcc8_var': 104.22476959228516,\n",
       " 'mfcc9_mean': -13.064760208129885,\n",
       " 'mfcc9_var': 81.15306854248047,\n",
       " 'mfcc10_mean': 18.465389251708984,\n",
       " 'mfcc10_var': 67.09021759033203,\n",
       " 'mfcc11_mean': -14.948745727539062,\n",
       " 'mfcc11_var': 63.98073196411133,\n",
       " 'mfcc12_mean': 6.881842613220215,\n",
       " 'mfcc12_var': 61.116844177246094,\n",
       " 'mfcc13_mean': -15.3265962600708,\n",
       " 'mfcc13_var': 50.56884002685547,\n",
       " 'mfcc14_mean': 4.77806282043457,\n",
       " 'mfcc14_var': 62.86275863647461,\n",
       " 'mfcc15_mean': -11.097589492797852,\n",
       " 'mfcc15_var': 52.935150146484375,\n",
       " 'mfcc16_mean': 4.736111164093018,\n",
       " 'mfcc16_var': 76.89418029785156,\n",
       " 'mfcc17_mean': -2.812528371810913,\n",
       " 'mfcc17_var': 101.6149673461914,\n",
       " 'mfcc18_mean': 6.798242092132568,\n",
       " 'mfcc18_var': 107.96431732177734,\n",
       " 'mfcc19_mean': -5.803801536560059,\n",
       " 'mfcc19_var': 103.87669372558594,\n",
       " 'mfcc20_mean': -3.767236709594727,\n",
       " 'mfcc20_var': 92.24774932861328,\n",
       " 'label': 9.0}"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "song.to_dict()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "15d41b49-7328-46d8-80f0-a24da81be79c",
   "metadata": {},
   "source": [
    "**Better start from here!**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "c0097df3-f04a-4fe8-a7f5-e32c64b7cf5d",
   "metadata": {},
   "outputs": [],
   "source": [
    "song = {\n",
    "    'chroma_stft_mean': [0.4440117478370666],\n",
    "    'chroma_stft_var': [0.0852029994130134],\n",
    "    'rms_mean': [0.2037734985351562],\n",
    "    'rms_var': [0.00659936433658],\n",
    "    'spectral_centroid_mean': [2095.4208239067048],\n",
    "    'spectral_centroid_var': [430313.48716756655],\n",
    "    'spectral_bandwidth_mean': [2241.060906256248],\n",
    "    'spectral_bandwidth_var': [110796.01228164523],\n",
    "    'rolloff_mean': [4581.850948466502],\n",
    "    'rolloff_var': [1717499.435882924],\n",
    "    'zero_crossing_rate_mean': [0.0941514253431941],\n",
    "    'zero_crossing_rate_var': [0.003422177139843],\n",
    "    'harmony_mean': [-3.053571708733216e-05],\n",
    "    'harmony_var': [0.0202102083712816],\n",
    "    'perceptr_mean': [-0.001146224560216],\n",
    "    'perceptr_var': [0.0124355517327785],\n",
    "    'tempo': [135.99917763157896],\n",
    "    'mfcc1_mean': [-74.18608856201172],\n",
    "    'mfcc1_var': [2630.19384765625],\n",
    "    'mfcc2_mean': [104.59842681884766],\n",
    "    'mfcc2_var': [672.80517578125],\n",
    "    'mfcc3_mean': [-8.379661560058594],\n",
    "    'mfcc3_var': [544.7293090820312],\n",
    "    'mfcc4_mean': [49.65111541748047],\n",
    "    'mfcc4_var': [280.70770263671875],\n",
    "    'mfcc5_mean': [-9.369983673095703],\n",
    "    'mfcc5_var': [164.64053344726562],\n",
    "    'mfcc6_mean': [21.44277572631836],\n",
    "    'mfcc6_var': [137.95318603515625],\n",
    "    'mfcc7_mean': [-16.32986831665039],\n",
    "    'mfcc7_var': [144.6834259033203],\n",
    "    'mfcc8_mean': [18.780681610107425],\n",
    "    'mfcc8_var': [104.22476959228516],\n",
    "    'mfcc9_mean': [-13.064760208129885],\n",
    "    'mfcc9_var': [81.15306854248047],\n",
    "    'mfcc10_mean': [18.465389251708984],\n",
    "    'mfcc10_var': [67.09021759033203],\n",
    "    'mfcc11_mean': [-14.948745727539062],\n",
    "    'mfcc11_var': [63.98073196411133],\n",
    "    'mfcc12_mean': [6.881842613220215],\n",
    "    'mfcc12_var': [61.116844177246094],\n",
    "    'mfcc13_mean': [-15.3265962600708],\n",
    "    'mfcc13_var': [50.56884002685547],\n",
    "    'mfcc14_mean': [4.77806282043457],\n",
    "    'mfcc14_var': [62.86275863647461],\n",
    "    'mfcc15_mean': [-11.097589492797852],\n",
    "    'mfcc15_var': [52.935150146484375],\n",
    "    'mfcc16_mean': [4.736111164093018],\n",
    "    'mfcc16_var': [76.89418029785156],\n",
    "    'mfcc17_mean': [-2.812528371810913],\n",
    "    'mfcc17_var': [101.6149673461914],\n",
    "    'mfcc18_mean': [6.798242092132568],\n",
    "    'mfcc18_var': [107.96431732177734],\n",
    "    'mfcc19_mean': [-5.803801536560059],\n",
    "    'mfcc19_var': [103.87669372558594],\n",
    "    'mfcc20_mean': [-3.767236709594727],\n",
    "    'mfcc20_var': [92.24774932861328]\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e98e7ef1-c7ee-49d9-b0ae-88d8a103bdd1",
   "metadata": {},
   "outputs": [],
   "source": [
    "#   'label': 9.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "28f81946-e90c-4965-8260-57aeadfd1b06",
   "metadata": {},
   "outputs": [],
   "source": [
    "song_df = pd.DataFrame(song)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "81b48455-c65f-4e26-8418-c6df2631db91",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chroma_stft_mean</th>\n",
       "      <th>chroma_stft_var</th>\n",
       "      <th>rms_mean</th>\n",
       "      <th>rms_var</th>\n",
       "      <th>spectral_centroid_mean</th>\n",
       "      <th>spectral_centroid_var</th>\n",
       "      <th>spectral_bandwidth_mean</th>\n",
       "      <th>spectral_bandwidth_var</th>\n",
       "      <th>rolloff_mean</th>\n",
       "      <th>rolloff_var</th>\n",
       "      <th>...</th>\n",
       "      <th>mfcc16_mean</th>\n",
       "      <th>mfcc16_var</th>\n",
       "      <th>mfcc17_mean</th>\n",
       "      <th>mfcc17_var</th>\n",
       "      <th>mfcc18_mean</th>\n",
       "      <th>mfcc18_var</th>\n",
       "      <th>mfcc19_mean</th>\n",
       "      <th>mfcc19_var</th>\n",
       "      <th>mfcc20_mean</th>\n",
       "      <th>mfcc20_var</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.444012</td>\n",
       "      <td>0.085203</td>\n",
       "      <td>0.203773</td>\n",
       "      <td>0.006599</td>\n",
       "      <td>2095.420824</td>\n",
       "      <td>430313.487168</td>\n",
       "      <td>2241.060906</td>\n",
       "      <td>110796.012282</td>\n",
       "      <td>4581.850948</td>\n",
       "      <td>1.717499e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>4.736111</td>\n",
       "      <td>76.89418</td>\n",
       "      <td>-2.812528</td>\n",
       "      <td>101.614967</td>\n",
       "      <td>6.798242</td>\n",
       "      <td>107.964317</td>\n",
       "      <td>-5.803802</td>\n",
       "      <td>103.876694</td>\n",
       "      <td>-3.767237</td>\n",
       "      <td>92.247749</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 57 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   chroma_stft_mean  chroma_stft_var  rms_mean   rms_var  \\\n",
       "0          0.444012         0.085203  0.203773  0.006599   \n",
       "\n",
       "   spectral_centroid_mean  spectral_centroid_var  spectral_bandwidth_mean  \\\n",
       "0             2095.420824          430313.487168              2241.060906   \n",
       "\n",
       "   spectral_bandwidth_var  rolloff_mean   rolloff_var  ...  mfcc16_mean  \\\n",
       "0           110796.012282   4581.850948  1.717499e+06  ...     4.736111   \n",
       "\n",
       "   mfcc16_var  mfcc17_mean  mfcc17_var  mfcc18_mean  mfcc18_var  mfcc19_mean  \\\n",
       "0    76.89418    -2.812528  101.614967     6.798242  107.964317    -5.803802   \n",
       "\n",
       "   mfcc19_var  mfcc20_mean  mfcc20_var  \n",
       "0  103.876694    -3.767237   92.247749  \n",
       "\n",
       "[1 rows x 57 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "song_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "ee5b7d1a-1b27-4e40-ae0d-6d8aae61e484",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-12-18 12:48:30.522955: E external/local_xla/xla/stream_executor/cuda/cuda_driver.cc:274] failed call to cuInit: CUDA_ERROR_UNKNOWN: unknown error\n",
      "2023-12-18 12:48:30.522971: I external/local_xla/xla/stream_executor/cuda/cuda_diagnostics.cc:129] retrieving CUDA diagnostic information for host: zaib\n",
      "2023-12-18 12:48:30.522974: I external/local_xla/xla/stream_executor/cuda/cuda_diagnostics.cc:136] hostname: zaib\n",
      "2023-12-18 12:48:30.523094: I external/local_xla/xla/stream_executor/cuda/cuda_diagnostics.cc:159] libcuda reported version is: 535.129.3\n",
      "2023-12-18 12:48:30.523103: I external/local_xla/xla/stream_executor/cuda/cuda_diagnostics.cc:163] kernel reported version is: 535.129.3\n",
      "2023-12-18 12:48:30.523104: I external/local_xla/xla/stream_executor/cuda/cuda_diagnostics.cc:241] kernel version seems to match DSO: 535.129.3\n"
     ]
    }
   ],
   "source": [
    "model = keras.models.load_model('mugen_model_v1_175_0.775.h5')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "e7fb05fe-beb3-4838-a41a-a2c16de08b7f",
   "metadata": {},
   "outputs": [],
   "source": [
    "scaler = load('scaler.joblib')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "a67435ad-75a1-4e7b-817d-b90dc8406d00",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.80306058, -0.15570111,  1.10559116,  0.93655303, -0.15369472,\n",
       "        -0.11116464, -0.01547439, -0.27911507, -0.00249689, -0.10263481,\n",
       "        -0.22186785,  0.13539316,  0.19517971,  0.65431588, -0.71008055,\n",
       "         1.02720524,  0.60200522,  0.70410317, -0.41004394,  0.16232736,\n",
       "        -0.08335441,  0.00821547,  0.26885273,  0.83739295,  0.532862  ,\n",
       "        -0.68446797, -0.0836993 ,  0.5947242 ,  0.18089452, -1.13806267,\n",
       "         0.5402677 ,  0.8477326 ,  0.38778695, -0.73264239, -0.17957941,\n",
       "         1.3638803 , -0.40411945, -1.30617196, -0.30395242,  0.37106547,\n",
       "        -0.23417114, -1.71787863, -0.52215585,  0.61539986, -0.05484645,\n",
       "        -1.49347647, -0.29566683,  0.77361665,  0.45334707,  0.22743311,\n",
       "         1.14307044,  1.62191167,  1.28215677, -0.9514257 ,  0.99618948,\n",
       "        -0.67206209,  0.48226681]])"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = scaler.transform(song_df)\n",
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "ba2d6d8d-221f-4a90-ae28-28624a641b32",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_reshaped = X.reshape(X.shape[0], 1, X.shape[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "09c5a0bf-a2f1-4a12-a93f-b92aff028f19",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 0s 235ms/step\n"
     ]
    }
   ],
   "source": [
    "preds = model.predict(X_reshaped)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "07a28ee1-1e41-4542-bbfe-4a513a66d9d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "genre_preds = dict(zip(genres, preds[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "0904fd94-1133-4453-a83c-1d13f083d2a0",
   "metadata": {},
   "outputs": [],
   "source": [
    "max_genre = max(genre_preds, key=genre_preds.get)\n",
    "max_value = genre_preds[max_genre]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "e24769e1-bf01-400f-b68c-1a3da11311fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('hiphop', 0.9396053)"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max_genre, max_value"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a6d27fa8-8e53-47e5-8277-3811e98411fb",
   "metadata": {},
   "source": [
    "**From TF to TFLite**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "10f46976-f0a4-4acb-9968-c37044c56a22",
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow.lite as tflite"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "192a4c64-7a0f-44a0-ab1b-0478b9b86654",
   "metadata": {},
   "outputs": [],
   "source": [
    "converter = tflite.TFLiteConverter.from_keras_model(model)\n",
    "\n",
    "converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS, tf.lite.OpsSet.SELECT_TF_OPS]\n",
    "converter._experimental_lower_tensor_list_ops = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "b415004a-63eb-4b0e-accc-f6b7e540fb90",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: /tmp/tmpre2kndqv/assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: /tmp/tmpre2kndqv/assets\n",
      "2023-12-18 12:48:50.653961: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:378] Ignored output_format.\n",
      "2023-12-18 12:48:50.653975: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:381] Ignored drop_control_dependency.\n",
      "2023-12-18 12:48:50.654309: I tensorflow/cc/saved_model/reader.cc:83] Reading SavedModel from: /tmp/tmpre2kndqv\n",
      "2023-12-18 12:48:50.659735: I tensorflow/cc/saved_model/reader.cc:51] Reading meta graph with tags { serve }\n",
      "2023-12-18 12:48:50.659746: I tensorflow/cc/saved_model/reader.cc:146] Reading SavedModel debug info (if present) from: /tmp/tmpre2kndqv\n",
      "2023-12-18 12:48:50.675207: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:388] MLIR V1 optimization pass is not enabled\n",
      "2023-12-18 12:48:50.681226: I tensorflow/cc/saved_model/loader.cc:233] Restoring SavedModel bundle.\n",
      "2023-12-18 12:48:50.741958: I tensorflow/cc/saved_model/loader.cc:217] Running initialization op on SavedModel bundle at path: /tmp/tmpre2kndqv\n",
      "2023-12-18 12:48:50.779187: I tensorflow/cc/saved_model/loader.cc:316] SavedModel load for tags { serve }; Status: success: OK. Took 124876 microseconds.\n",
      "2023-12-18 12:48:50.959163: I tensorflow/compiler/mlir/tensorflow/utils/dump_mlir_util.cc:269] disabling MLIR crash reproducer, set env var `MLIR_CRASH_REPRODUCER_DIRECTORY` to enable.\n",
      "2023-12-18 12:48:51.036866: E tensorflow/compiler/mlir/lite/stablehlo/transforms/op_stat_pass.cc:119] Unsupported data type.\n",
      "2023-12-18 12:48:51.036936: E tensorflow/compiler/mlir/lite/stablehlo/transforms/op_stat_pass.cc:119] Unsupported data type.\n",
      "2023-12-18 12:48:51.036945: E tensorflow/compiler/mlir/lite/stablehlo/transforms/op_stat_pass.cc:119] Unsupported data type.\n",
      "Summary on the non-converted ops:\n",
      "---------------------------------\n",
      " * Accepted dialects: tfl, builtin, func\n",
      " * Non-Converted Ops: 54, Total Ops 152, % non-converted = 35.53 %\n",
      " * 49 ARITH ops, 5 TF ops\n",
      "\n",
      "- arith.constant:   49 occurrences  (f32: 33, i32: 16)\n",
      "\n",
      "  (i1: 2, i32: 2)\n",
      "\n",
      "\n",
      "- tf.TensorListReserve:    1 occurrences  (: 1)\n",
      "- tf.TensorListSetItem:    2 occurrences  (: 2)\n",
      "- tf.TensorListStack:    2 occurrences  (f32: 2)\n",
      "  (f32: 10, i32: 4)\n",
      "  (f32: 4)\n",
      "  (f32: 1)\n",
      "  (f32: 1)\n",
      "  (f32: 19)\n",
      "  (f32: 2)\n",
      "  (i1: 2)\n",
      "  (f32: 6)\n",
      "  (f32: 10)\n",
      "\n",
      "  (i32: 1)\n",
      "  (f32: 1)\n",
      "  (i64: 4, i32: 1)\n",
      "  (f32: 1)\n",
      "  (f32: 2, i32: 1)\n",
      "  (f32: 4)\n",
      "  (f32: 1)\n",
      "  (i32: 2)\n",
      "\n",
      "2023-12-18 12:48:51.037910: W tensorflow/compiler/mlir/lite/flatbuffer_export.cc:2921] TFLite interpreter needs to link Flex delegate in order to run the model since it contains the following Select TFop(s):\n",
      "Flex ops: FlexTensorListReserve, FlexTensorListSetItem, FlexTensorListStack\n",
      "Details:\n",
      "\ttf.TensorListReserve(tensor<2xi32>, tensor<i32>) -> (tensor<!tf_type.variant<tensor<?x64xf32>>>) : {device = \"\"}\n",
      "\ttf.TensorListSetItem(tensor<!tf_type.variant<tensor<?x64xf32>>>, tensor<i32>, tensor<?x64xf32>) -> (tensor<!tf_type.variant<tensor<?x64xf32>>>) : {device = \"\", resize_if_index_out_of_bounds = false}\n",
      "\ttf.TensorListStack(tensor<!tf_type.variant<tensor<?x64xf32>>>, tensor<2xi32>) -> (tensor<1x?x64xf32>) : {device = \"\", num_elements = 1 : i64}\n",
      "See instructions: https://www.tensorflow.org/lite/guide/ops_select\n"
     ]
    }
   ],
   "source": [
    "tflite_model = converter.convert()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "c1c8c7d5-b513-4803-9e3f-76cc9cbf6ed5",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('mugen-model.tflite', 'wb') as f_out:\n",
    "    f_out.write(tflite_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a5caba0-0e11-488e-8c85-3aab872ba367",
   "metadata": {},
   "source": [
    "**predicting with TFLite**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "664120fb-cff9-4fa5-8083-5934e9e5c4d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import tflite_runtime.interpreter as tflite"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "0698d3fe-c850-45f2-a2a9-dc54a6258360",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Created TensorFlow Lite delegate for select TF ops.\n",
      "INFO: TfLiteFlexDelegate delegate: 3 nodes delegated out of 18 nodes with 2 partitions.\n",
      "\n",
      "INFO: Created TensorFlow Lite XNNPACK delegate for CPU.\n"
     ]
    }
   ],
   "source": [
    "interpreter = tflite.Interpreter(model_path='mugen-model.tflite')\n",
    "interpreter.allocate_tensors()\n",
    "\n",
    "input_index = interpreter.get_input_details()[0]['index']\n",
    "output_index = interpreter.get_output_details()[0]['index']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "6368571a-abf0-4556-9614-bd4bae9addfe",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_reshaped = X_reshaped.astype('float32')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "e811c6ef-d60d-4492-b256-68d90bf642be",
   "metadata": {},
   "outputs": [],
   "source": [
    "interpreter.set_tensor(input_index, X_reshaped)\n",
    "interpreter.invoke()\n",
    "preds = interpreter.get_tensor(output_index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "bda9af9f-663a-4948-a119-4facbf13466d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('hiphop', 0.9396052)"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "genre_preds = dict(zip(genres, preds[0]))\n",
    "\n",
    "max_genre = max(genre_preds, key=genre_preds.get)\n",
    "max_value = genre_preds[max_genre]\n",
    "\n",
    "max_genre, max_value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "6c1aef2c-ea88-462c-bfcb-dd66186d8f6c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[ 0.8030606 , -0.1557011 ,  1.1055912 ,  0.93655306,\n",
       "         -0.15369472, -0.11116464, -0.01547439, -0.27911508,\n",
       "         -0.00249689, -0.10263481, -0.22186784,  0.13539316,\n",
       "          0.19517972,  0.6543159 , -0.71008056,  1.0272052 ,\n",
       "          0.60200524,  0.7041032 , -0.41004395,  0.16232735,\n",
       "         -0.08335441,  0.00821547,  0.26885274,  0.8373929 ,\n",
       "          0.532862  , -0.684468  , -0.0836993 ,  0.5947242 ,\n",
       "          0.18089452, -1.1380627 ,  0.5402677 ,  0.8477326 ,\n",
       "          0.38778695, -0.7326424 , -0.17957942,  1.3638803 ,\n",
       "         -0.40411943, -1.306172  , -0.30395243,  0.37106547,\n",
       "         -0.23417114, -1.7178786 , -0.5221558 ,  0.61539984,\n",
       "         -0.05484645, -1.4934765 , -0.29566684,  0.7736167 ,\n",
       "          0.4533471 ,  0.22743312,  1.1430705 ,  1.6219116 ,\n",
       "          1.2821568 , -0.9514257 ,  0.9961895 , -0.6720621 ,\n",
       "          0.4822668 ]]], dtype=float32)"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_reshaped"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "5e18baae-96f8-4cab-ab81-5571778cce3e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def predict(X):\n",
    "    \n",
    "    preds = model.predict(X)\n",
    "    #float_predictions = preds[0].tolist()\n",
    "\n",
    "    genre_preds = dict(zip(genres, preds[0]))\n",
    "\n",
    "    max_genre = max(genre_preds, key=genre_preds.get)\n",
    "    max_value = genre_preds[max_genre]\n",
    "\n",
    "    return genre_preds, max_genre, max_value\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "9cbe76ab-f86c-472b-96b0-c1678afb1129",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 0s 12ms/step\n"
     ]
    }
   ],
   "source": [
    "genre_preds, max_genre, max_value = predict(X_reshaped)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "abca14f8-fd1e-4a44-b895-7c612c3ed7a6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'classical': 4.756844e-05,\n",
       " 'rock': 0.0011586339,\n",
       " 'metal': 0.006832264,\n",
       " 'country': 0.0015658727,\n",
       " 'jazz': 2.787578e-05,\n",
       " 'blues': 0.029967746,\n",
       " 'reggae': 0.0023837145,\n",
       " 'disco': 0.017146694,\n",
       " 'pop': 0.0012644121,\n",
       " 'hiphop': 0.9396053}"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "genre_preds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "60aad73f-0542-462d-8cc3-5f1132b1665d",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_array = np.array([[[ 0.8030606 , -0.1557011 ,  1.1055912 ,  0.93655306,\n",
    "         -0.15369472, -0.11116464, -0.01547439, -0.27911508,\n",
    "         -0.00249689, -0.10263481, -0.22186784,  0.13539316,\n",
    "          0.19517972,  0.6543159 , -0.71008056,  1.0272052 ,\n",
    "          0.60200524,  0.7041032 , -0.41004395,  0.16232735,\n",
    "         -0.08335441,  0.00821547,  0.26885274,  0.8373929 ,\n",
    "          0.532862  , -0.684468  , -0.0836993 ,  0.5947242 ,\n",
    "          0.18089452, -1.1380627 ,  0.5402677 ,  0.8477326 ,\n",
    "          0.38778695, -0.7326424 , -0.17957942,  1.3638803 ,\n",
    "         -0.40411943, -1.306172  , -0.30395243,  0.37106547,\n",
    "         -0.23417114, -1.7178786 , -0.5221558 ,  0.61539984,\n",
    "         -0.05484645, -1.4934765 , -0.29566684,  0.7736167 ,\n",
    "          0.4533471 ,  0.22743312,  1.1430705 ,  1.6219116 ,\n",
    "          1.2821568 , -0.9514257 ,  0.9961895 , -0.6720621 ,\n",
    "          0.4822668 ]]], dtype='float32')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "64362911-a13a-43fb-8e04-2fa4ff2f85d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "import json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "312cdaa2-d68e-4142-a19f-707d25a5090f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\"data\": [[[0.8030605912208557, -0.15570110082626343, 1.1055911779403687, 0.9365530610084534, -0.15369471907615662, -0.1111646369099617, -0.015474390238523483, -0.27911508083343506, -0.002496890025213361, -0.10263480991125107, -0.22186784446239471, 0.1353931576013565, 0.19517971575260162, 0.6543158888816833, -0.7100805640220642, 1.027205228805542, 0.6020052433013916, 0.7041031718254089, -0.41004395484924316, 0.1623273491859436, -0.0833544135093689, 0.008215470239520073, 0.26885274052619934, 0.8373929262161255, 0.5328620076179504, -0.6844679713249207, -0.0836993008852005, 0.594724178314209, 0.18089452385902405, -1.1380627155303955, 0.5402677059173584, 0.8477326035499573, 0.38778695464134216, -0.732642412185669, -0.17957942187786102, 1.3638802766799927, -0.40411943197250366, -1.3061720132827759, -0.3039524257183075, 0.3710654675960541, -0.23417113721370697, -1.7178785800933838, -0.5221558213233948, 0.6153998374938965, -0.05484645068645477, -1.4934765100479126, -0.2956668436527252, 0.7736166715621948, 0.4533470869064331, 0.22743311524391174, 1.1430704593658447, 1.621911644935608, 1.2821568250656128, -0.9514256715774536, 0.9961894750595093, -0.67206209897995, 0.4822668135166168]]]}\n"
     ]
    }
   ],
   "source": [
    "data_dict = {\"data\": data_array.tolist()}  # Convert the NumPy array to a nested list\n",
    "\n",
    "# Convert the dictionary to JSON format\n",
    "json_data = json.dumps(data_dict)\n",
    "\n",
    "print(json_data)"
   ]
  }
 ],
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