mirror of
https://github.com/dscripka/openWakeWord.git
synced 2026-08-27 18:17:20 -04:00
95 lines
4.1 KiB
Python
95 lines
4.1 KiB
Python
# Copyright 2022 David Scripka. All rights reserved.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
# Copyright 2022 David Scripka. All rights reserved.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
|
|
|
|
# Imports
|
|
import openwakeword
|
|
import os
|
|
import numpy as np
|
|
import scipy.io.wavfile
|
|
import tempfile
|
|
import pytest
|
|
|
|
# Download models needed for tests
|
|
openwakeword.utils.download_models(model_names=["alexa_v0.1", "hey_mycroft_v0.1"])
|
|
|
|
|
|
# Tests
|
|
class TestModels:
|
|
def test_train_verifier_model(self):
|
|
with tempfile.TemporaryDirectory() as tmp_dir:
|
|
# Make random negative data for verifier model training
|
|
scipy.io.wavfile.write(os.path.join(tmp_dir, "negative_reference.wav"),
|
|
16000, np.random.randint(-1000, 1000, 16000*4).astype(np.int16))
|
|
|
|
# Load random clips
|
|
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,
|
|
negative_reference_clips=negative_clips,
|
|
output_path=os.path.join(tmp_dir, 'verifier_model.pkl'),
|
|
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.tflite")
|
|
)
|
|
|
|
with pytest.raises(ValueError):
|
|
# Load model with verifier model incorrectly to catch ValueError
|
|
owwModel = openwakeword.Model(
|
|
wakeword_models=[os.path.join("openwakeword", "resources",
|
|
"models", "hey_mycroft_v0.1.tflite")],
|
|
custom_verifier_models={"bad_key": os.path.join(tmp_dir, "verifier_model.pkl")},
|
|
custom_verifier_threshold=0.3,
|
|
)
|
|
|
|
# Load model with verifier model incorrectly to catch ValueError
|
|
owwModel = openwakeword.Model(
|
|
wakeword_models=[os.path.join("openwakeword", "resources", "models", "hey_mycroft_v0.1.tflite")],
|
|
custom_verifier_models={"hey_mycroft_v0.1": os.path.join(tmp_dir, "verifier_model.pkl")},
|
|
custom_verifier_threshold=0.3,
|
|
)
|
|
|
|
# Prediction on random data
|
|
owwModel.predict_clip(reference_clips[0])
|