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    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "I music2emo 02-10 03:58:55.459 music2emo.py:280] audio file loaded and feature computation success : inference/input/test.mp3\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "🎵 **Music Emotion Recognition Results** 🎵\n",
      "--------------------------------------------------\n",
      "🎭 **Predicted Mood Tags:** ballad, calm, film, hopeful, inspiring, love, meditative, melancholic, relaxing, romantic, sad, soft\n",
      "💖 **Valence:** 5.42 (Scale: 1-9)\n",
      "⚡ **Arousal:** 4.16 (Scale: 1-9)\n",
      "--------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "from music2emo import Music2emo\n",
    "\n",
    "input_audio = \"inference/input/test.mp3\"\n",
    "\n",
    "music2emo = Music2emo()\n",
    "output_dic = music2emo.predict(input_audio)\n",
    "\n",
    "valence = output_dic[\"valence\"]\n",
    "arousal = output_dic[\"arousal\"]\n",
    "predicted_moods =output_dic[\"predicted_moods\"]\n",
    "\n",
    "print(\"\\n🎵 **Music Emotion Recognition Results** 🎵\")\n",
    "print(\"-\" * 50)\n",
    "print(f\"🎭 **Predicted Mood Tags:** {', '.join(predicted_moods) if predicted_moods else 'None'}\")\n",
    "print(f\"💖 **Valence:** {valence:.2f} (Scale: 1-9)\")\n",
    "print(f\"⚡ **Arousal:** {arousal:.2f} (Scale: 1-9)\")\n",
    "print(\"-\" * 50)\n",
    "\n"
   ]
  }
 ],
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