Switched to using Sonogram.py

app.py

@@ -15,11 +15,7 @@ from pathlib import Path
 import streamlit as st
 import torch
 import pandas as pd
-from pyannote.audio import Pipeline
-from pyannote.audio.pipelines import SpeakerDiarization
-from pyannote.audio.models.segmentation import PyanNet
-from pyannote.audio import Inference
-from pyannote.pipeline.parameter import ParamDict
+from sonogram import Sonogram
 
 import sonogram_utility as su
 import utils
@@ -76,25 +72,7 @@ if ENABLE_DENOISE:
 else:
     dfModel = dfState = None
 
-# Load baseline model
-pipeline = Pipeline.from_pretrained("pyannote/speaker-diarization-3.1")
-
-# Generate replacement segmentation model
-newSpecs = pipeline._segmentation.model.specifications
-segModel = PyanNet.from_pretrained('20251208_Sonogram_Segmentation.ckpt')
-segModel.specifications = newSpecs
-segmentation_duration = segModel.specifications.duration
-
-# Update baseline with training
-pipeline._segmentation = Inference(
-    segModel,
-    duration=segmentation_duration,
-    step=pipeline.segmentation_step * segmentation_duration,
-    skip_aggregation=True,
-    batch_size=1,
-)
-
-pipeline.to(device)
+pipeline = Sonogram()
 
 # ---------------------------------------------------------------------------
 # Session state + global styles