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Fix Errors & Parameterize File Paths

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- Update gitignore to exclude vscode files
- Parameterize hardcoded file paths
- Comment out references to pgf image and latex dependency
- Allow pickle in numpy.load
- Add TODO comments for where settings need to be changed
- Explicitly set visualization to False
- Change pytorch device from cuda to cpu
This commit is contained in:
Sravan Balaji
2020-04-30 19:58:05 -04:00
parent d3d6d1cd82
commit 93ac62b154
4 changed files with 65 additions and 52 deletions
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3
.gitignore vendored
View File

@@ -1,3 +1,6 @@
# Ignore vscode settings
.vscode
# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]

53
poles/ncltpoles.py
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@@ -21,13 +21,17 @@ import particlefilter
import poles
import pynclt
import util
import sys
plt.rcParams['text.latex.preamble']=[r'\usepackage{lmodern}']
params = {'text.usetex': True,
'font.size': 16,
'font.family': 'lmodern',
'text.latex.unicode': True}
# plt.rcParams['text.latex.preamble']=[r'\usepackage{lmodern}']
# params = {'text.usetex': True,
# 'font.size': 16,
# 'font.family': 'lmodern',
# 'text.latex.unicode': True}
# TODO: UPDATE THIS!
localization_name_start = 'localization_3_6_7_2020-04'
mapextent = np.array([30.0, 30.0, 5.0])
mapsize = np.full(3, 0.2)
@@ -151,7 +155,7 @@ def save_global_map():
poleparams[ci, :-1], axis=0, weights=poleparams[ci, -1])])
scores.append(np.mean(poleparams[ci, -1]))
clustermeans = np.hstack([clustermeans, np.array(scores).reshape([-1, 1])])
globalmapfile = os.path.join('nclt', get_globalmapname() + '.npz')
globalmapfile = os.path.join(pynclt.resultdir, get_globalmapname() + '.npz')
np.savez(globalmapfile,
polemeans=clustermeans, mapfactors=mapfactors, mappos=globalmappos)
plot_global_map(globalmapfile)
@@ -161,12 +165,12 @@ def plot_global_map(globalmapfile):
data = np.load(globalmapfile)
x, y = data['polemeans'][:, :2].T
plt.clf()
plt.rcParams.update(params)
# plt.rcParams.update(params)
plt.scatter(x, y, s=1, c='b', marker='.')
plt.xlabel('x [m]')
plt.ylabel('y [m]')
plt.savefig(globalmapfile[:-4] + '.svg')
plt.savefig(globalmapfile[:-4] + '.pgf')
# plt.savefig(globalmapfile[:-4] + '.pgf')
print(data['mapfactors'])
@@ -222,7 +226,7 @@ def save_local_maps(sessionname, visualize=False):
def view_local_maps(sessionname):
sessiondir = os.path.join('nclt', sessionname)
sessiondir = os.path.join(pynclt.resultdir, sessionname)
session = pynclt.session(sessionname)
maps = np.load(os.path.join(sessiondir, get_localmapfile()))['maps']
for i, map in enumerate(maps):
@@ -254,14 +258,14 @@ def view_local_maps(sessionname):
def evaluate_matches():
mapdata = np.load(os.path.join('nclt', get_globalmapname() + '.npz'))
mapdata = np.load(os.path.join(pynclt.resultdir, get_globalmapname() + '.npz'))
polemap = mapdata['polemeans'][:, :2]
kdtree = scipy.spatial.cKDTree(polemap[:, :2], leafsize=10)
maxdist = 0.5
n_matches = np.zeros(len(pynclt.sessions))
n_all = np.zeros(len(pynclt.sessions))
for i, sessionname in enumerate(pynclt.sessions):
sessiondir = os.path.join('nclt', sessionname)
sessiondir = os.path.join(pynclt.resultdir, sessionname)
session = pynclt.session(sessionname)
maps = np.load(os.path.join(sessiondir, get_localmapfile()))['maps']
for map in maps:
@@ -285,11 +289,11 @@ def evaluate_matches():
def localize(sessionname, visualize=False):
print(sessionname)
mapdata = np.load(os.path.join('nclt', get_globalmapname() + '.npz'))
mapdata = np.load(os.path.join(pynclt.resultdir, get_globalmapname() + '.npz'))
polemap = mapdata['polemeans'][:, :2]
polevar = 1.50
session = pynclt.session(sessionname)
locdata = np.load(os.path.join(session.dir, get_localmapfile()))['maps']
locdata = np.load(os.path.join(session.dir, get_localmapfile()), allow_pickle=True)['maps']
polepos_m = []
polepos_w = []
for i in range(len(locdata)):
@@ -419,18 +423,18 @@ def plot_trajectories():
trajectorydir = os.path.join(
pynclt.resultdir, 'trajectories_est_{:.0f}_{:.0f}_{:.0f}'.format(
n_mapdetections, 10 * poles.minscore, poles.polesides[-1]))
pgfdir = os.path.join(trajectorydir, 'pgf')
# pgfdir = os.path.join(trajectorydir, 'pgf')
util.makedirs(trajectorydir)
util.makedirs(pgfdir)
mapdata = np.load(os.path.join('nclt', get_globalmapname() + '.npz'))
# util.makedirs(pgfdir)
mapdata = np.load(os.path.join(pynclt.resultdir, get_globalmapname() + '.npz'))
polemap = mapdata['polemeans']
plt.rcParams.update(params)
# plt.rcParams.update(params)
for sessionname in pynclt.sessions:
try:
session = pynclt.session(sessionname)
files = [file for file \
in os.listdir(os.path.join(pynclt.resultdir, sessionname)) \
if file.startswith('localization_3_6_7_2019-07')]
if file.startswith(localization_name_start)]
# if file.startswith(get_locfileprefix())]
for file in files:
T_w_r_est = np.load(os.path.join(
@@ -447,7 +451,7 @@ def plot_trajectories():
bottom=0.13, top=0.98, left=0.145, right=0.98)
filename = sessionname + file[18:-4]
plt.savefig(os.path.join(trajectorydir, filename + '.svg'))
plt.savefig(os.path.join(pgfdir, filename + '.pgf'))
# plt.savefig(os.path.join(pgfdir, filename + '.pgf'))
except:
pass
@@ -457,7 +461,7 @@ def evaluate():
for sessionname in pynclt.sessions:
files = [file for file \
in os.listdir(os.path.join(pynclt.resultdir, sessionname)) \
if file.startswith('localization_3_6_7_2019-07')]
if file.startswith(localization_name_start)]
# if file.startswith(get_locfileprefix())]
files.sort()
session = pynclt.session(sessionname)
@@ -497,7 +501,7 @@ def evaluate():
'angerror': angerror, 'angrmse': angrmse, 'T_gt_est': T_gt_est})
np.savez(os.path.join(pynclt.resultdir, get_evalfile()), stats=stats)
mapdata = np.load(os.path.join('nclt', get_globalmapname() + '.npz'))
mapdata = np.load(os.path.join(pynclt.resultdir, get_globalmapname() + '.npz'))
print('session \t f\te_pos \trmse_pos \te_ang \te_rmse')
row = '{session} \t{f} \t{poserror} \t{posrmse} \t{angerror} \t{angrmse}'
for i, stat in enumerate(stats):
@@ -514,8 +518,11 @@ if __name__ == '__main__':
poles.minscore = 0.6
poles.polesides = range(1, 7+1)
save_global_map()
session = '2012-01-08'
# TODO: Change this to the session you want to find trajectory for
session = '2012-01-15'
save_local_maps(session)
localize(session)
# Set visualization to False
localize(session, False)
plot_trajectories()
evaluate()

2
poles/poles.py
View File

@@ -7,7 +7,7 @@ import skimage.measure
import torch
device = torch.device('cuda')
device = torch.device('cpu')
polesides = range(1, 5+1)
minscore = 0.6
minheight = 1.0

59
poles/pynclt.py
View File

@@ -19,39 +19,42 @@ T_w_o[:3, :3] = [[0, 1, 0], [1, 0, 0], [0, 0, -1]]
T_o_w = util.invert_ht(T_w_o)
eulerdef = 'sxyz'
# TODO: Modify these for your workspace
csvdelimiter = ','
datadir = '/mnt/c/Users/SabrinaB/Desktop/nclt'
resultdir = 'nclt'
datadir = '/app/dataset/data/'
resultdir = '/app/dataset/nclt'
snapshotfile = 'snapshot.npz'
sessionfile = 'sessiondata.npz'
# TODO: Comment out the sessions you are not using
sessions = [
#'2012-01-08',
'2012-01-08',
'2012-01-15',
#'2012-01-22',
#'2012-02-02',
#'2012-02-04',
#'2012-02-05',
#'2012-02-12',
#'2012-02-18',
#'2012-02-19',
#'2012-03-17',
#'2012-03-25',
#'2012-03-31',
#'2012-04-29',
#'2012-05-11',
#'2012-05-26',
#'2012-06-15',
#'2012-08-04',
#'2012-08-20',
#'2012-09-28',
#'2012-10-28',
#'2012-11-04',
#'2012-11-16',
#'2012-11-17',
#'2012-12-01',
#'2013-01-10',
#'2013-02-23',
'2013-04-05']
'2012-01-22',
'2012-02-02',
'2012-02-04',
'2012-02-05',
'2012-02-12',
'2012-02-18',
'2012-02-19',
'2012-03-17',
'2012-03-25',
'2012-03-31',
'2012-04-29',
'2012-05-11',
'2012-05-26',
'2012-06-15',
'2012-08-04',
'2012-08-20',
'2012-09-28',
'2012-10-28',
'2012-11-04',
'2012-11-16',
'2012-11-17',
'2012-12-01',
'2013-01-10',
'2013-02-23',
'2013-04-05'
]
lat0 = np.radians(42.293227)