44 lines
1.4 KiB
Python
Executable File
44 lines
1.4 KiB
Python
Executable File
#!/usr/bin/env python3
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import pandas as pd
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import numpy as np
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import sys
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from pprint import pprint
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from tabulate import tabulate
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def process_raw_line(line):
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fields = line.rstrip().split(' ')
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fields = [field.split(':')[-1] for field in fields]
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fields[5] = fields[5][1:-1]
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fields[0] = int(fields[0])
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fields[1:] = list(map(np.float, fields[1:]))
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return fields
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with open(sys.argv[1], 'r') as f:
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data = list(map(process_raw_line, f.readlines()))
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df = pd.DataFrame(data)
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df.columns = ['frame', 'Y', 'U', 'V', 'All', 'dB']
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df['inv'] = [1 - value for value in df['All']]
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print(f'Mean overall SSIM: {df["All"].mean()}')
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print(f'Median overall SSIM: {df["All"].median()}')
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print(f'Frame with worst SSIM: {df.idxmin()["All"]+1}')
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print(f'Frame with best SSIM: {df.idxmax()["All"]+1}')
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print(tabulate(
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[(key, value * 100) for key, value in [
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['best', df['All'].max()],
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[50, 1 - df['inv'].quantile(0.50)],
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[66.6, 1 - df['inv'].quantile(0.666)],
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[75, 1 - df['inv'].quantile(0.75)],
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[80, 1 - df['inv'].quantile(0.80)],
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[90, 1 - df['inv'].quantile(0.90)],
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[95, 1 - df['inv'].quantile(0.95)],
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[98, 1 - df['inv'].quantile(0.98)],
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[99, 1 - df['inv'].quantile(0.99)],
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[99.9, 1 - df['inv'].quantile(0.999)],
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[100, df['All'].min()]
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]],
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headers=['% Frames', '≥ SSIM']
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))
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