o SQ8j@s6ddlZddlZddlZddlmZGdddZdS)N)dequec@sdeZdZdZejejeje ddddfde de fdd Z dd d Z dd dZdddZdS)VADz A model class for a voice activity detection (VAD) based on Silero's model: https://github.com/snakers4/silero-vad resourcesmodelszsilero_vad.onnx model_path n_threadscCsTt}||_||_tj||dgd|_tdd|_t d tj |_ | dS)zInitialize the VAD model object. Args: model_path (str): The path to the Silero VAD ONNX model. n_threads (int): The number of threads to use for the VAD model. CPUExecutionProvider) sess_options providers})maxleni>N)ortSessionOptionsinter_op_num_threadsintra_op_num_threadsInferenceSessionmodelrprediction_buffernparrayastypeint64 sample_rate reset_states)selfrrsessionOptionsrW/home/nk/hobo-godmode/plappi-mvp/.venv/lib/python3.10/site-packages/openwakeword/vad.py__init__<s  z VAD.__init__cCs@td|dfd|_td|dfd|_d|_d|_dS)N@float32r)rzerosr_h_c_last_sr_last_batch_size)r batch_sizerrrr\s zVAD.reset_statesc sfddtdjdD}g}|D]%}|d|j|j|jd}|jd|}|\}|_|_||ddqt |S)aI Get the VAD predictions for the input audio frame. Args: x (np.ndarray): The input audio, must be 16 khz and 16-bit PCM format. If longer than the input frame, will be split into chunks of length `frame_size` and the predictions for each chunk returned. Must be a length that is integer multiples of the `frame_size` argument. frame_size (int): The frame size in samples. The reccomended default is 480 samples (30 ms @ 16khz), but smaller and larger values can be used (though performance may decrease). Returns float: The average predicted score for the audio frame cs(g|]}||dtjqS)i)rrr").0i frame_sizexrr ts zVAD.predict..rN)inputhcsrN) rangeshaper$r%rrrunappendrmean) rr.r-chunksframe_predictionschunk ort_inputsort_outsoutrr,rpredictbs   z VAD.predictcCs|j|||dSr0)rr8r@)rr.r-rrr__call__sz VAD.__call__N)r)r))rA)__name__ __module__ __qualname____doc__ospathjoindirnameabspath__file__strintrrr@rBrrrrr6s" r) onnxruntimernumpyrrG collectionsrrrrrrs /