def chunk_and_align_all(d):
print d['match_file']
rss1 = d['rss1']
rss2 = d['rss2']
pcd_dir1 = pjoin(dset_dir_from_rss(rss1), 'pcd_downsampled_normals')
pcd_dir2 = pjoin(dset_dir_from_rss(rss2), 'pcd_downsampled_normals')
# Read and save initial transform files
enu1 = get_enu0(d['gps_file1'], d['gps_file1'])
enu2 = get_enu0(d['gps_file2'], d['gps_file1'])
h5f = h5py.File(d['match_file'], 'r')
nn_matches = h5f['matches'][...]
nn_dict = dict(zip(nn_matches[:, 1], nn_matches[:, 0]))
h5f.close()
assert EXPORT_START == 0
start1 = nn_matches[0, 1] / EXPORT_STEP
args_all = list()
chunk_num = 0
for k in range(start1, nn_matches[-1, 1] / EXPORT_STEP - CHUNK_SIZE, REALIGN_EVERY):
#def chunk_and_align(start1, start2, enu1, enu2, rss1, rss2, pcd_dir1, pcd_dir2, chunk_num):
try:
k2 = get_closest_key_value(k * EXPORT_STEP, nn_dict, max_shift=10)
except:
# TODO Think this sometimes occurs near end of alignments
break
args_all.append((k, k2 / EXPORT_STEP, enu1, enu2, rss1, rss2, pcd_dir1, pcd_dir2, chunk_num))
chunk_num += 1
Parallel(n_jobs=NUM_CPUS)(delayed(chunk_and_align)(*args) for args in args_all)
# For debugging
'''
from os.path import join as pjoin
from pipeline_utils import dset_dir_from_rss, print_and_call
from pipeline_config import CAMERA, NUM_CPUS
from graphslam_config import MATCH_JSON_DATA, GRAPHSLAM_VIDEOS_DIR, GRAPHSLAM_MAPS_DIR,\
GRAPHSLAM_EVAL_DIR
from joblib import Parallel, delayed
def disp(s):
print s
if __name__ == '__main__':
cmds = list()
for match in MATCH_JSON_DATA:
video_file = pjoin(dset_dir_from_rss(match['rss1']), '_'.join(match['rss1'][1:]) + '%d.avi' % CAMERA)
fstem1 = '--'.join(match['rss1'])
fstem2 = '--'.join(match['rss2'])
outvideo = pjoin(GRAPHSLAM_VIDEOS_DIR, '+'.join((fstem1, fstem2)) + '.avi')
align_data = pjoin(GRAPHSLAM_MAPS_DIR, '+'.join((fstem1, fstem2)) + '.npz')
labels1 = pjoin(GRAPHSLAM_EVAL_DIR, fstem1 + '.h5')
labels2 = pjoin(GRAPHSLAM_EVAL_DIR, fstem2 + '.h5')
cmd = 'python project_map_on_video.py {vid} {align_data} {labels1} {labels2} {out} --cam {cam}'.format(
vid=video_file, align_data=align_data, out=outvideo,
labels1=labels1, labels2=labels2, cam=CAMERA)
cmds.append(cmd)
#print cmds
Parallel(n_jobs=NUM_CPUS-1)(delayed(print_and_call)(cmd) for cmd in cmds)
from os.path import join as pjoin
from pipeline_utils import dset_dir_from_rss, print_and_call
from pipeline_config import CAMERA, NUM_CPUS
from graphslam_config import MATCH_JSON_DATA, GRAPHSLAM_VIDEOS_DIR, GRAPHSLAM_MAPS_DIR,\
GRAPHSLAM_EVAL_DIR
from joblib import Parallel, delayed
def disp(s):
print s
if __name__ == '__main__':
cmds = list()
for match in MATCH_JSON_DATA:
video_file = pjoin(dset_dir_from_rss(match['rss1']),
'_'.join(match['rss1'][1:]) + '%d.avi' % CAMERA)
fstem1 = '--'.join(match['rss1'])
fstem2 = '--'.join(match['rss2'])
outvideo = pjoin(GRAPHSLAM_VIDEOS_DIR, '+'.join(
(fstem1, fstem2)) + '.avi')
align_data = pjoin(GRAPHSLAM_MAPS_DIR, '+'.join(
(fstem1, fstem2)) + '.npz')
labels1 = pjoin(GRAPHSLAM_EVAL_DIR, fstem1 + '.h5')
labels2 = pjoin(GRAPHSLAM_EVAL_DIR, fstem2 + '.h5')
cmd = 'python project_map_on_video.py {vid} {align_data} {labels1} {labels2} {out} --cam {cam}'.format(
vid=video_file,
align_data=align_data,
out=outvideo,
labels1=labels1,
labels2=labels2,
