b82419f321b3b52841065e00d1f50945d7e8a2ee,nussl/separation/primitive/hpss.py,HPSS,run,#HPSS#,48

Before Change

        // make a mask and return
        harmonic_mask = np.array(harmonic_masks).transpose((1, 2, 0))
        percussive_mask = np.array(percussive_masks).transpose((1, 2, 0))
        both_masks = [harmonic_mask, percussive_mask]
        
        self.masks = []
        
        for mask in both_masks:
            if self.mask_type == self.BINARY_MASK:
                mask = np.round(mask)
                mask_object = masks.BinaryMask(mask)
            elif self.mask_type == self.SOFT_MASK:
                mask_object = masks.SoftMask(mask)
            else:
                raise ValueError("Unknown mask type {self.mask_type}!")
            self.masks.append(mask_object)
        self.result_masks = self.masks
        return self.masks
    
    def _compute_spectrograms(self):

After Change

            percussive_masks.append(percussive_mask)

        // make a mask and return
        harmonic_masks = np.stack(harmonic_masks, axis=-1)
        percussive_masks = np.stack(percussive_masks, axis=-1)

        _masks = np.stack([harmonic_masks, percussive_masks], axis=-1)
        
        self.result_masks = []
        
        for i in range(_masks.shape[-1]):
            mask_data = _masks[..., i]
            if self.mask_type == self.MASKS["binary"]:
                mask_data = _masks[..., i] == np.max(_masks, axis=-1)
            mask = self.mask_type(mask_data)
            self.result_masks.append(mask)

        return self.result_masks

Instances