video-object-remover / SiamMask /utils /average_meter_helper.py
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# --------------------------------------------------------
# SiamMask
# Licensed under The MIT License
# Written by Qiang Wang (wangqiang2015 at ia.ac.cn)
# --------------------------------------------------------
import numpy as np
class Meter(object):
def __init__(self, name, val, avg):
self.name = name
self.val = val
self.avg = avg
def __repr__(self):
return "{name}: {val:.6f} ({avg:.6f})".format(
name=self.name, val=self.val, avg=self.avg
)
def __format__(self, *tuples, **kwargs):
return self.__repr__()
class AverageMeter(object):
"""Computes and stores the average and current value"""
def __init__(self):
self.reset()
def reset(self):
self.val = {}
self.sum = {}
self.count = {}
def update(self, batch=1, **kwargs):
val = {}
for k in kwargs:
val[k] = kwargs[k] / float(batch)
self.val.update(val)
for k in kwargs:
if k not in self.sum:
self.sum[k] = 0
self.count[k] = 0
self.sum[k] += kwargs[k]
self.count[k] += batch
def __repr__(self):
s = ''
for k in self.sum:
s += self.format_str(k)
return s
def format_str(self, attr):
return "{name}: {val:.6f} ({avg:.6f}) ".format(
name=attr,
val=float(self.val[attr]),
avg=float(self.sum[attr]) / self.count[attr])
def __getattr__(self, attr):
if attr in self.__dict__:
return super(AverageMeter, self).__getattr__(attr)
if attr not in self.sum:
# logger.warn("invalid key '{}'".format(attr))
print("invalid key '{}'".format(attr))
return Meter(attr, 0, 0)
return Meter(attr, self.val[attr], self.avg(attr))
def avg(self, attr):
return float(self.sum[attr]) / self.count[attr]
class IouMeter(object):
def __init__(self, thrs, sz):
self.sz = sz
self.iou = np.zeros((sz, len(thrs)), dtype=np.float32)
self.thrs = thrs
self.reset()
def reset(self):
self.iou.fill(0.)
self.n = 0
def add(self, output, target):
if self.n >= len(self.iou):
return
target, output = target.squeeze(), output.squeeze()
for i, thr in enumerate(self.thrs):
pred = output > thr
mask_sum = (pred == 1).astype(np.uint8) + (target > 0).astype(np.uint8)
intxn = np.sum(mask_sum == 2)
union = np.sum(mask_sum > 0)
if union > 0:
self.iou[self.n, i] = intxn / union
elif union == 0 and intxn == 0:
self.iou[self.n, i] = 1
self.n += 1
def value(self, s):
nb = max(int(np.sum(self.iou > 0)), 1)
iou = self.iou[:nb]
def is_number(s):
try:
float(s)
return True
except ValueError:
return False
if s == 'mean':
res = np.mean(iou, axis=0)
elif s == 'median':
res = np.median(iou, axis=0)
elif is_number(s):
res = np.sum(iou > float(s), axis=0) / float(nb)
return res
if __name__ == '__main__':
avg = AverageMeter()
avg.update(time=1.1, accuracy=.99)
avg.update(time=1.0, accuracy=.90)
print(avg)
print(avg.time)
print(avg.time.avg)
print(avg.time.val)
print(avg.SS)