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The audio tagging and sound event detection models are trained from PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition: https://github.com/qiuqiangkong/audioset_tagging_cnn\n\n## Installation\nPyTorch\u003e=1.0 is required.\n```\n$ pip install panns-inference\n```\n\n## Usage\n```\n$ python3 example.py\n```\n\nFor example:\n\n```\nimport librosa\nimport panns_inference\nfrom panns_inference import AudioTagging, SoundEventDetection, labels\n\naudio_path = 'examples/R9_ZSCveAHg_7s.wav'\n(audio, _) = librosa.core.load(audio_path, sr=32000, mono=True)\naudio = audio[None, :]  # (batch_size, segment_samples)\n\nprint('------ Audio tagging ------')\nat = AudioTagging(checkpoint_path=None, device='cuda')\n(clipwise_output, embedding) = at.inference(audio)\n\nprint('------ Sound event detection ------')\nsed = SoundEventDetection(checkpoint_path=None, device='cuda')\nframewise_output = sed.inference(audio)\n```\n\n\n## Results\n\u003cpre\u003e\n------ Audio tagging ------\nCheckpoint path: /root/panns_data/Cnn14_mAP=0.431.pth\nGPU number: 1\nSpeech: 0.893\nTelephone bell ringing: 0.754\nInside, small room: 0.235\nTelephone: 0.183\nMusic: 0.092\nRingtone: 0.047\nInside, large room or hall: 0.028\nAlarm: 0.014\nAnimal: 0.009\nVehicle: 0.008\n------ Sound event detection ------\nCheckpoint path: /root/panns_data/Cnn14_mAP=0.431.pth\nGPU number: 1\nSave fig to results/sed_result.pdf\n\u003c/pre\u003e\n\nSound event detection plot:\n\u003cimg src=\"resources/sed_result.png\" width=\"600\"\u003e\n\n## Cite\n[1] Kong, Qiuqiang, Yin Cao, Turab Iqbal, Yuxuan Wang, Wenwu Wang, and Mark D. Plumbley. \"PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition.\" arXiv preprint arXiv:1912.10211 (2019).","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fqiuqiangkong%2Fpanns_inference","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fqiuqiangkong%2Fpanns_inference","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fqiuqiangkong%2Fpanns_inference/lists"}