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# Copyright 2022-present NAVER Corp.
# CC BY-NC-SA 4.0
# Available only for non-commercial use
from pdb import set_trace as bb
import os, os.path as osp
from tqdm import tqdm
import numpy as np
SEQUENCES = [ 'lakeside', 'sand_box', 'storage_room', 'storage_room_2', 'tunnel',
'delivery_area', 'electro', 'forest', 'playground', 'terrains']
RATES = [3, 5, 7, 9, 11, 13, 15]
def parse_args():
import argparse
parser = argparse.ArgumentParser('PUMP evaluation script for the ETH3D dataset')
parser.add_argument('--root', default='datasets/eth3d')
parser.add_argument('--output', default='results/eth3d')
parser.add_argument('--just-print', action='store_true', help='just print commands')
return parser.parse_args()
def main( args ):
run_pump(args) and run_eval(args)
def run_pump(args):
done = True
for img1, img2 in tqdm(list_eth3d_pairs()):
output_path = osp.join(args.output, img1, img2+'.corres')
if osp.isfile(output_path): continue
done = False
_exec(f'''python test_multiscale_recursive.py
--img1 {osp.join(args.root,img1)}
--img2 {osp.join(args.root,img2)}
--max-scale 1.5
--desc PUMP
--post-filter "densify=True,dense_side='right'"
--output {output_path}''')
return done
def run_eval( args ):
for rate in RATES:
mean_aepe_per_rate = 0
for seq in SEQUENCES:
pairs = np.load(osp.join(args.root, 'info_ETH3D_files', f'{seq}_every_5_rate_of_{rate}'), allow_pickle=True)
mean_aepe_per_seq = 0
for pair in pairs:
img1, img2 = pair['source_image'], pair['target_image']
Ys, Xs, Yt, Xt = [np.float32(pair[k]) for k in 'Ys Xs Yt Xt'.split()]
corres_path = osp.join(args.output, img1, img2+'.corres')
corres = np.load(corres_path, allow_pickle=True)['corres']
# extract estimated and target flow
W, H = np.int32(corres[-1, 2:4] + 1)
flow = (corres[:,0:2] - corres[:,2:4]).reshape(H, W, 2)
iYt, iXt = np.int32(np.round(Yt)), np.int32(np.round(Xt))
if 'correct way':
gt_targets = np.c_[Xs - Xt, Ys - Yt]
est_targets = flow[iYt, iXt]
elif 'GLU-Net way (somewhat inaccurate because of overlapping points in the mask)':
mask = np.zeros((H,W), dtype=bool)
mask[iYt, iXt] = True
gt_flow = np.full((H,W,2), np.nan, dtype=np.float32)
gt_flow[iYt, iXt, 0] = Xs - Xt
gt_flow[iYt, iXt, 1] = Ys - Yt
gt_targets = gt_flow[mask]
est_targets = flow[mask]
# compute end-point error
aepe = np.linalg.norm(est_targets - gt_targets, axis=-1).mean()
mean_aepe_per_seq += aepe
mean_aepe_per_seq /= len(pairs)
mean_aepe_per_rate += mean_aepe_per_seq
print(f'mean AEPE for {rate=} {seq=}:', mean_aepe_per_seq)
print(f'>> mean AEPE for {rate=}:', mean_aepe_per_rate / len(SEQUENCES))
def list_eth3d_pairs():
path = osp.join(args.root, 'info_ETH3D_files', 'list_pairs.txt')
try:
lines = open(path).read().splitlines()
except OSError:
lines = []
for seq in SEQUENCES:
for rate in RATES:
pairs = np.load(osp.join(args.root, 'info_ETH3D_files', f'{seq}_every_5_rate_of_{rate}'), allow_pickle=True)
for pair in pairs:
lines.append(pair['source_image'] + ' ' + pair['target_image'])
open(path, 'w').write('\n'.join(lines))
pairs = [line.split() for line in lines if line[0] != '#']
return pairs
def _exec(cmd):
# strip & remove \n
cmd = ' '.join(cmd.split())
if args.just_print:
print(cmd)
else:
os.system(cmd)
if __name__ == '__main__':
args = parse_args()
main( args )
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