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get_match.py
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get_match.py
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# Copyright 2021 Mobile Robotics Lab. at Skoltech
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import glob
import os
import pandas as pd
def main():
vid_1 = './output/2'
vid_2 = './output/1'
match(vid_1, vid_2)
def match(vid_1, vid_2):
out_images_1 = sorted(glob.glob(vid_1 + "/*"))
out_images_2 = sorted(glob.glob(vid_2 + "/*"))
image_timestamps_1 = (list(map(
lambda x: int(os.path.splitext(os.path.basename(x))[0]),
out_images_1)))
image_timestamps_2 = (list(map(
lambda x: int(os.path.splitext(os.path.basename(x))[0]),
out_images_2)))
THRESHOLD_NS = 100000
left = pd.DataFrame({'t': image_timestamps_1,
'left': image_timestamps_1}, dtype=int)
# TODO: change this quick hack to prevent pandas from
# converting ints to floats
right = pd.DataFrame({'t': image_timestamps_2,
'right_int': image_timestamps_2,
'right': list(map(str, image_timestamps_2))},
)
print(right.dtypes)
# align by nearest, because we need to account for frame drops
df = pd.merge_asof(left, right, on='t',
tolerance=THRESHOLD_NS,
allow_exact_matches=True,
direction='nearest')
df = df.dropna()
df = df.drop('t', axis='columns')
df = df.drop('right_int', axis='columns')
df = df.reset_index(drop=True)
print(df.head())
print(df.dtypes)
df.to_csv('./output/match.csv')
if __name__ == '__main__':
main()