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RMSEacc_mul.py
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import datetime
import os, sys
lib_path = os.path.abspath(os.path.join('../..'))
sys.path.append(lib_path)
lib_path2 = '/test/flow_motion/unsupodo_refine2'
sys.path.append(lib_path2)
import multiprocessing
import os
import numpy as np
from tools.evatools.local2word import localsepara, get_world, gtget_world, localsepara_fast, relative_error
from tools.evatools.evaluation import evaluation, gtlocalevaluation
import pandas as pd
root = "/test/flow_motion/simple_flowuncer_seg/"
flagtime = datetime.datetime.strptime("2021-11-23 00-00-00", '%Y-%m-%d %H-%M-%S')
datasize = np.array([4541, 1101, 4661, 801, 271, 2761, 1101, 1101, 4071, 1591, 1201,
921, 1061, 3281, 631, 1091, 1731, 491, 1081, 4981, 831, 2721,
-1, -1, -1, -1, -1, -1, -1, -1,
3817, 6103, -1, 8278, 11424, 9248, 5351, 4705, 5233, -1,
6443, 20801, 4701, 11846, 16596, 7538, 14014, 5677, 10903, 9765, 9868, 41529], dtype=np.int)
def mul_process(timedir):
print(timedir)
filepath = os.path.join(root + "data/summary", timedir + ".xlsx")
localpath = os.path.join(root + "data/summarylocal", timedir + ".xlsx")
reader = None
print(filepath)
if os.path.exists(filepath):
writer = pd.ExcelWriter(filepath, mode="a", engine='openpyxl')
else:
data_df = pd.DataFrame()
writer = pd.ExcelWriter(filepath, mode="w")
data_df.to_excel(writer)
writer.save()
if os.path.exists(localpath):
writer_re = pd.ExcelWriter(localpath, mode="a", engine='openpyxl')
else:
data_df = pd.DataFrame()
writer_re = pd.ExcelWriter(localpath, mode="w")
data_df.to_excel(writer_re)
writer_re.save()
if "apollo"in timedir:
start = 1
elif "flow" in timedir:
start = 1
else:
start = 1
for e in range(0, 600, 1):
# for e in [42, 47]:
result = None
if os.path.exists(filepath):
if reader is None:
reader = pd.read_excel(filepath, sheet_name=None)
if str(e) in reader.keys():
continue
choose = ["test",""]
relaresult = None
for dir in choose:
eresult = None
dir = str(e) + dir
SQUE = localsepara_fast(root, timedir, dir)
if SQUE is None:
continue
print(dir)
totallen = 0.0
for sque in SQUE:
get_world(root, timedir, dir, int(sque))
trans, rota = evaluation(root, timedir, dir, int(sque))
relative = relative_error(root, timedir, dir, int(sque))
rota *= 100
if eresult is None:
eresult = np.array([sque, trans, rota, trans*datasize[sque], rota*datasize[sque]], dtype=np.float64).reshape(1, -1)
else:
temp = np.array([sque, trans, rota, trans * datasize[sque], rota * datasize[sque]], dtype=np.float64).reshape(1, -1)
eresult = np.concatenate((eresult, temp), axis=0)
totallen += datasize[sque]
if relaresult is None:
relaresult = relative
else:
relaresult = np.concatenate((relaresult, relative), axis=1)
averag = np.sum(eresult, axis=0).reshape(1, -1) / totallen
averag[:, 1] = averag[:, 3]
averag[:, 2] = averag[:, 4]
trueavg = np.mean(eresult, axis=0)
print(dir,"avgtran:",trueavg[1],"avgrota:",trueavg[2])
eresult = np.concatenate((eresult, averag), axis=0)
if result is None:
result = eresult
else:
result = np.concatenate((result, eresult), axis=0)
if SQUE is None:
continue
data = pd.DataFrame(result)
data_rae = pd.DataFrame(relaresult, index=["tmse", "trmse", "tmae", "tlen", "trate",
"rmse", "rrmse", "rmae", "rlen", "rrate"], columns=["x", "y", "z", "tlen"] * (relaresult.shape[1] // 4))
if os.path.exists(filepath):
writer = pd.ExcelWriter(filepath, mode="a", engine='openpyxl')
else:
writer = pd.ExcelWriter(filepath, mode="w")
data.to_excel(writer, str(e), float_format='%.5f', index=False, header=False)
writer.save()
if os.path.exists(localpath):
writer_re = pd.ExcelWriter(localpath, mode="a", engine='openpyxl')
else:
# writer_re = pd.ExcelWriter(localpath, mode="w")
data_df = pd.DataFrame()
writer_re = pd.ExcelWriter(localpath, mode="w")
data_df.to_excel(writer)
writer_re.save()
data_rae.to_excel(writer_re, str(e), float_format='%.5f', index=True, header=True)
writer_re.save()
writer.close()
writer_re.close()
if __name__ == '__main__':
dirpath = os.path.join(root, "result")
# dirpath = root
timelist = os.listdir(dirpath)
timelist = [
# "/experiment/kitti_ford_apollo/aloam/data"
"(2023-04-06 17-33-45)-(TITAN RTXx1)-19535-flow-full"
]
for timeflag in timelist:
# mul_process(timeflag)
p = multiprocessing.Process(target=mul_process, args=(timeflag,)) # 创建一个进程，args传参 必须是元组
p.start()