124 lines
4.3 KiB
Python
124 lines
4.3 KiB
Python
#!/usr/bin/env python3
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# Copyright 2019 Mycroft AI Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import json
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from os.path import isfile, isdir
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from prettyparse import Usage
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from precise_lite.network_runner import Listener
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from precise_lite.params import inject_params
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from precise_lite.pocketsphinx.scripts.test import PocketsphinxTestScript
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from precise_lite.scripts.base_script import BaseScript
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from precise_lite.stats import Stats
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from precise_lite.train_data import TrainData
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class EvalScript(BaseScript):
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usage = Usage('''
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Evaluate a list of models on a dataset
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:-u --use-train
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Evaluate training data instead of test data
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:-t --threshold float 0.5
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Network output to be considered an activation
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:-pw --pocketsphinx-wake-word str -
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Optional wake word used to
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generate a Pocketsphinx data point
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:-pd --pocketsphinx-dict str -
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Optional word dictionary used to
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generate a Pocketsphinx data point
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Format = wake-word.yy-mm-dd.dict
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:-pf --pocketsphinx-folder str -
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Optional hmm folder used to
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generate a Pocketsphinx data point.
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:-pth --pocketsphinx-threshold float 1e-90
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Optional threshold used to
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generate a Pocketsphinx data point
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:-o --output str stats.json
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Output json file
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...
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''')
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usage.add_argument('models', nargs='*',
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help='List of model filenames in format: wake-word.yy-mm-dd.net')
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usage |= TrainData.usage
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def __init__(self, args):
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super().__init__(args)
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if not (
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bool(args.pocketsphinx_dict) ==
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bool(args.pocketsphinx_folder) ==
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bool(args.pocketsphinx_wake_word)
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):
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raise ValueError('Must pass all or no Pocketsphinx arguments')
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self.is_pocketsphinx = bool(args.pocketsphinx_dict)
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if self.is_pocketsphinx:
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if not isfile(args.pocketsphinx_dict):
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raise ValueError('No such file: ' + args.pocketsphinx_dict)
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if not isdir(args.pocketsphinx_folder):
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raise ValueError('No such folder: ' + args.pocketsphinx_folder)
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def run(self):
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args = self.args
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data = TrainData.from_both(args.tags_file, args.tags_folder, args.folder)
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data_files = data.train_files if args.use_train else data.test_files
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print('Data:', data)
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metrics = {}
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if self.is_pocketsphinx:
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script = PocketsphinxTestScript.create(
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key_phrase=args.pocketsphinx_wake_word, dict_file=args.pocketsphinx_dict,
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hmm_folder=args.pocketsphinx_folder, threshold=args.pocketsphinx_threshold
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)
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ww_files, nww_files = data_files
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script.run_test(ww_files, 'Wake Word', 1.0)
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script.run_test(nww_files, 'Not Wake Word', 0.0)
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stats = script.get_stats()
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metrics[args.pocketsphinx_dict] = stats.to_dict(args.threshold)
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for model_name in args.models:
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print('Calculating', model_name + '...')
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inject_params(model_name)
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train, test = data.load(args.use_train, not args.use_train)
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inputs, targets = train if args.use_train else test
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predictions = Listener.find_runner(model_name)(model_name).predict(inputs)
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stats = Stats(predictions, targets, sum(data_files, []))
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print('----', model_name, '----')
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print(stats.counts_str())
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print()
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print(stats.summary_str())
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print()
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metrics[model_name] = stats.to_dict(args.threshold)
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print('Writing to:', args.output)
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with open(args.output, 'w') as f:
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json.dump(metrics, f)
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main = EvalScript.run_main
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if __name__ == '__main__':
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main()
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