67 lines
2.9 KiB
Python
67 lines
2.9 KiB
Python
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
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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 os
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import argparse
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def parse_convergence_results(path, environment):
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whole_tumor = []
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tumor_core = []
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peritumoral_edema = []
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enhancing_tumor = []
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mean_dice = []
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logfiles = [f for f in os.listdir(path) if "log" in f and environment in f]
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if not logfiles:
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raise FileNotFoundError("No logfile found at {}".format(path))
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for logfile in logfiles:
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with open(os.path.join(path, logfile), "r") as f:
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content = f.readlines()
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if "TumorCore" not in content[-1]:
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print("Evaluation score not found. The file", logfile, "might be corrupted.")
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continue
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content = content[-1].split("()")[1]
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whole_tumor.append(float([val for val in content.split(" ")
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if "WholeTumor" in val][0].split()[-1]))
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tumor_core.append(float([val for val in content.split(" ")
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if "TumorCore" in val][0].split()[-1]))
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peritumoral_edema.append(float([val for val in content.split(" ")
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if "PeritumoralEdema" in val][0].split()[-1]))
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enhancing_tumor.append(float([val for val in content.split(" ")
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if "EnhancingTumor" in val][0].split()[-1]))
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mean_dice.append(float([val for val in content.split(" ")
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if "MeanDice" in val][0].split()[-1]))
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if whole_tumor:
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print("Evaluation average dice score:", sum(mean_dice) / len(mean_dice))
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print("Evaluation whole tumor dice score:", sum(whole_tumor) / len(whole_tumor))
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print("Evaluation tumor core dice score:", sum(tumor_core) / len(tumor_core))
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print("Evaluation peritumoral edema dice score:", sum(peritumoral_edema) / len(peritumoral_edema))
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print("Evaluation enhancing tumor dice score:", sum(enhancing_tumor) / len(enhancing_tumor))
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else:
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print("All logfiles were corrupted, no loss was obtained.")
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if __name__ == '__main__':
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parser = argparse.ArgumentParser()
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parser.add_argument('--model_dir',
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type=str,
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required=True)
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parser.add_argument('--env',
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type=str,
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required=True)
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args = parser.parse_args()
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parse_convergence_results(path=args.model_dir, environment=args.env)
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