Method __call__

evaluation/evaluate_vggsound.py:48–114

r"""Evalute.

(
        self,
        pl_model: pl.LightningModule
    )

        self.audio_dir = 'evaluation/data/vggsound'

    def __call__(
        self,
        pl_model: pl.LightningModule
    ) -> Dict:
        r"""Evalute."""

        print(f'Evaluation on VGGSound+ with [text label] queries.')
        
        pl_model.eval()
        device = pl_model.device

        sisdrs_list = []
        sdris_list = []
        sisdris_list = []
        

        with torch.no_grad():
            for eval_data in tqdm(self.eval_list):

                # labels, source_path, mixture_path = eval_data
                file_id, mix_wav, s0_wav, s0_text, s1_wav, s1_text = eval_data

                labels = s0_text

                mixture_path = os.path.join(self.audio_dir, mix_wav)
                source_path = os.path.join(self.audio_dir, s0_wav)


                source, fs = librosa.load(source_path, sr=self.sampling_rate, mono=True)
                mixture, fs = librosa.load(mixture_path, sr=self.sampling_rate, mono=True)

                sdr_no_sep = calculate_sdr(ref=source, est=mixture)
                                
                text = [labels]
                conditions = pl_model.query_encoder.get_query_embed(
                    modality='text',
                    text=text,
                    device=device 
                )
                    
                input_dict = {
                    "mixture": torch.Tensor(mixture)[None, None, :].to(device),
                    "condition": conditions,
                }
                
                sep_segment = pl_model.ss_model(input_dict)["waveform"]
                    # sep_segment: (batch_size=1, channels_num=1, segment_samples)

                sep_segment = sep_segment.squeeze(0).squeeze(0).data.cpu().numpy()
                    # sep_segment: (segment_samples,)

                sdr = calculate_sdr(ref=source, est=sep_segment)
                sdri = sdr - sdr_no_sep

                sisdr_no_sep = calculate_sisdr(ref=source, est=mixture)
                sisdr = calculate_sisdr(ref=source, est=sep_segment)
                sisdri = sisdr - sisdr_no_sep