74 lines
2.4 KiB
Python
74 lines
2.4 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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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.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 TestScript(BaseScript):
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usage = Usage('''
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Test a model against a dataset
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:model str
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Either Keras (.net) or TensorFlow (.pb) model to test
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:-u --use-train
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Evaluate training data instead of test data
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:-nf --no-filenames
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Don't print out the names of files that failed
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:-t --threshold float 0.5
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Network output required to be considered an activation
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...
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''') | TrainData.usage
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def run(self):
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args = self.args
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inject_params(args.model)
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data = TrainData.from_both(args.tags_file, args.tags_folder, args.folder)
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train, test = data.load(args.use_train, not args.use_train, shuffle=False)
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inputs, targets = train if args.use_train else test
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filenames = sum(data.train_files if args.use_train else data.test_files, [])
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predictions = Listener.find_runner(args.model)(args.model).predict(inputs)
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stats = Stats(predictions, targets, filenames)
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print('Data:', data)
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if not args.no_filenames:
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fp_files = stats.calc_filenames(False, True, args.threshold)
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fn_files = stats.calc_filenames(False, False, args.threshold)
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print('=== False Positives ===')
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print('\n'.join(fp_files))
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print()
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print('=== False Negatives ===')
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print('\n'.join(fn_files))
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print()
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print(stats.counts_str(args.threshold))
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print()
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print(stats.summary_str(args.threshold))
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main = TestScript.run_main
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if __name__ == '__main__':
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main()
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