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Improved error handling and tests for custom verifier model

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dscripka 2023-03-05 00:12:14 -05:00
parent 89b63051b6
commit 79bb73eb26
2 changed files with 22 additions and 0 deletions
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4
openwakeword/custom_verifier_model.py
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@ -151,6 +151,10 @@ def train_custom_verifier(
[get_reference_clip_features(i, oww, model_name, N=5)
for i in tqdm(positive_reference_clips, desc="Processing positive reference clips")]
)
if positive_features.shape[0] == 0:
raise ValueError("The positive features were created! Make sure that"
" the positive reference clips contain the appropriate audio"
" for the desired model")
# Get features from negative reference clips
negative_features = np.vstack(

18
tests/test_custom_verifier_model.py
View file

@ -32,6 +32,7 @@ import os
import numpy as np
import scipy.io.wavfile
import tempfile
import pytest
# Tests
@ -46,6 +47,15 @@ class TestModels:
reference_clips = [os.path.join("tests", "data", "hey_mycroft_test.wav")]
negative_clips = [os.path.join(tmp_dir, "negative_reference.wav")]
# Check for error message when no positive examples are found
with pytest.raises(ValueError):
openwakeword.train_custom_verifier(
positive_reference_clips=reference_clips,
negative_reference_clips=negative_clips,
output_path=os.path.join(tmp_dir, 'verifier_model.pkl'),
model_name="alexa"
)
# Train verifier model on the reference clips
openwakeword.train_custom_verifier(
positive_reference_clips=reference_clips,
@ -54,6 +64,14 @@ class TestModels:
model_name="hey_mycroft"
)
# Train verifier model on the reference clips, using full path of model file
openwakeword.train_custom_verifier(
positive_reference_clips=reference_clips,
negative_reference_clips=negative_clips,
output_path=os.path.join(tmp_dir, 'verifier_model.pkl'),
model_name=os.path.join("openwakeword", "resources", "models", "hey_mycroft_v0.1.onnx")
)
# Load model with verifier model
owwModel = openwakeword.Model(
wakeword_model_paths=[os.path.join("openwakeword", "resources", "models", "hey_mycroft_v0.1.onnx")],