108 lines
2.6 KiB
Python
Executable File
108 lines
2.6 KiB
Python
Executable File
#!/usr/bin/env python3
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#
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# BSD 3-Clause License
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#
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# This file is part of the Basalt project.
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# https://gitlab.com/VladyslavUsenko/basalt.git
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#
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# Copyright (c) 2019-2021, Vladyslav Usenko and Nikolaus Demmel.
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# All rights reserved.
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#
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import os
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import sys
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import json
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datasets = ['Seq.', 'MH_01_easy', 'MH_02_easy', 'MH_03_medium', 'MH_04_difficult',
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'MH_05_difficult', 'V1_01_easy', 'V1_02_medium',
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'V1_03_difficult', 'V2_01_easy', 'V2_02_medium']
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# Other results.
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vio = {
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'ate' : ['VIO RMS ATE [m]'],
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'time' : ['VIO Time [s]'],
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'num_frames' : ['VIO Num. Frames']
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}
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mapping = {
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'ate' : ['MAP RMS ATE [m]'],
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'time' : ['MAP Time [s]'],
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'num_frames' : ['MAP Num. KFs']
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}
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pose_graph = {
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'ate' : ['PG RMS ATE [m]'],
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'time' : ['PG Time [s]'],
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'num_frames' : ['PG Num. KFs']
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}
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pure_ba = {
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'ate' : ['PG RMS ATE [m]'],
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'time' : ['PG Time [s]'],
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'num_frames' : ['PG Num. KFs']
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}
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out_dir = sys.argv[1]
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def load_data(x, prefix, key):
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fname = out_dir + '/' + prefix + '_' + key
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if os.path.isfile(fname):
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with open(fname, 'r') as f:
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j = json.load(f)
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res = round(j['rms_ate'], 3)
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x['ate'].append(float(res))
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x['time'].append(round(j['exec_time_ns']*1e-9, 3))
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x['num_frames'].append(j['num_frames'])
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else:
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x['ate'].append(float('Inf'))
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x['time'].append(float('Inf'))
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x['num_frames'].append(float('Inf'))
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for key in datasets[1:]:
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load_data(vio, 'vio', key)
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load_data(mapping, 'mapper', key)
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load_data(pose_graph, 'mapper_no_weights', key)
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load_data(pure_ba, 'mapper_no_factors', key)
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row_format ="{:>17}" + "{:>13}" * (len(datasets)-1)
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datasets_short = [x[:5] for x in datasets]
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print('\nVisual-Inertial Odometry')
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print(row_format.format(*datasets_short))
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print(row_format.format(*vio['ate']))
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#print(row_format.format(*vio['time']))
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print(row_format.format(*vio['num_frames']))
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print('\nVisual-Inertial Mapping')
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print(row_format.format(*datasets_short))
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print(row_format.format(*mapping['ate']))
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#print(row_format.format(*mapping['time']))
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print(row_format.format(*mapping['num_frames']))
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print('\nPose-Graph optimization (Identity weights for all factors)')
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print(row_format.format(*datasets_short))
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print(row_format.format(*pose_graph['ate']))
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#print(row_format.format(*pose_graph['time']))
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print(row_format.format(*pose_graph['num_frames']))
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print('\nPure BA optimization (no factors from the recovery used)')
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print(row_format.format(*datasets_short))
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print(row_format.format(*pure_ba['ate']))
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#print(row_format.format(*pure_ba['time']))
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print(row_format.format(*pure_ba['num_frames']))
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