def do_python_eval(self):
"""
python evaluation wrapper
:return: info_str
"""
info_str = ''
annopath = os.path.join(self.data_path, 'Annotations', '{0!s}.xml')
imageset_file = os.path.join(self.data_path, 'ImageSets',
self.image_set + '.txt')
annocache = os.path.join(self.cache_path,
self.name + '_annotations.pkl')
aps = []
# The PASCAL VOC metric changed in 2010
use_07_metric = True if self.year == 'SDS' or int(
self.year) < 2010 else False
print 'VOC07 metric? ' + ('Y' if use_07_metric else 'No')
info_str += 'VOC07 metric? ' + ('Y' if use_07_metric else 'No')
info_str += '\n'
for cls_ind, cls in enumerate(self.classes):
if cls == '__background__':
continue
filename = self.get_result_file_template().format(cls)
rec, prec, ap = voc_eval(filename,
annopath,
imageset_file,
cls,
annocache,
ovthresh=0.5,
use_07_metric=use_07_metric)
aps += [ap]
print('AP for {} = {:.4f}'.format(cls, ap))
info_str += 'AP for {} = {:.4f}\n'.format(cls, ap)
print('Mean [email protected] = {:.4f}'.format(np.mean(aps)))
info_str += 'Mean [email protected] = {:.4f}\n\n'.format(np.mean(aps))
# @0.7
aps = []
for cls_ind, cls in enumerate(self.classes):
if cls == '__background__':
continue
filename = self.get_result_file_template().format(cls)
rec, prec, ap = voc_eval(filename,
annopath,
imageset_file,
cls,
annocache,
ovthresh=0.7,
use_07_metric=use_07_metric)
aps += [ap]
print('AP for {} = {:.4f}'.format(cls, ap))
info_str += 'AP for {} = {:.4f}\n'.format(cls, ap)
print('Mean [email protected] = {:.4f}'.format(np.mean(aps)))
info_str += 'Mean [email protected] = {:.4f}'.format(np.mean(aps))
return info_str
def do_python_eval(self):
"""
python evaluation wrapper
:return: info_str
"""
info_str = ''
annopath = os.path.join(self.data_path, 'Annotations', '{0!s}.xml')
imageset_file = os.path.join(self.data_path, 'ImageSets', 'Main', self.image_set + '.txt')
annocache = os.path.join(self.cache_path, self.name + '_annotations.pkl')
aps = []
# The PASCAL VOC metric changed in 2010
use_07_metric = True if self.year == 'SDS' or int(self.year) < 2010 else False
print 'VOC07 metric? ' + ('Y' if use_07_metric else 'No')
info_str += 'VOC07 metric? ' + ('Y' if use_07_metric else 'No')
info_str += '\n'
for cls_ind, cls in enumerate(self.classes):
if cls == '__background__':
continue
filename = self.get_result_file_template().format(cls)
rec, prec, ap = voc_eval(filename, annopath, imageset_file, cls, annocache,
ovthresh=0.5, use_07_metric=use_07_metric)
aps += [ap]
print('AP for {} = {:.4f}'.format(cls, ap))
info_str += 'AP for {} = {:.4f}\n'.format(cls, ap)
print('Mean [email protected] = {:.4f}'.format(np.mean(aps)))
info_str += 'Mean [email protected] = {:.4f}\n\n'.format(np.mean(aps))
# @0.7
aps = []
for cls_ind, cls in enumerate(self.classes):
if cls == '__background__':
continue
filename = self.get_result_file_template().format(cls)
rec, prec, ap = voc_eval(filename, annopath, imageset_file, cls, annocache,
ovthresh=0.7, use_07_metric=use_07_metric)
aps += [ap]
print('AP for {} = {:.4f}'.format(cls, ap))
info_str += 'AP for {} = {:.4f}\n'.format(cls, ap)
print('Mean [email protected] = {:.4f}'.format(np.mean(aps)))
info_str += 'Mean [email protected] = {:.4f}'.format(np.mean(aps))
return info_str
def do_python_eval(self):
"""
python evaluation wrapper
:return: None
"""
annopath = os.path.join(self.data_path, 'Annotations', '{0!s}.xml')
imageset_file = os.path.join(self.data_path, 'ImageSets', 'Main',
self.image_set + '.txt')
annocache = os.path.join(self.cache_path,
self.name + '_annotations.pkl')
result_file = os.path.join(self.cache_path,
self.name + 'eval_result.txt')
result_cont = ''
recs = []
precs = []
aps = []
# The PASCAL VOC metric changed in 2010
use_07_metric = True if int(self.year) < 2010 else False
print 'VOC07 metric? ' + ('Y' if use_07_metric else 'No')
for cls_ind, cls in enumerate(self.classes):
if cls == '__background__':
continue
filename = self.get_result_file_template().format(cls)
rec, prec, ap = voc_eval(filename,
annopath,
imageset_file,
cls,
annocache,
ovthresh=0.5,
use_07_metric=use_07_metric)
#self.draw_roc_curve(cls, rec, prec, ap)
#recs += rec
#precs += prec
aps += [ap]
output = 'AP for {} = {:.4f}'.format(cls, ap)
print(output)
result_cont += output + '\n'
#self.draw_roc_curve("all", recs/float(self.num_classes-1), precs/float(self.num_classes-1), np.mean(aps))
output = 'Mean AP = {:.4f}'.format(np.mean(aps))
print(output)
result_cont += output + '\n'
with open(result_file, 'wt') as f:
f.write(result_cont)
os.system('mailx -s "gpu029 voc eval result" [email protected] < ' +
result_file)
def do_python_eval(self):
"""
python evaluation wrapper
:return: None
"""
annopath = os.path.join(self.data_path, 'Annotations', '{0!s}.xml')
imageset_file = os.path.join(self.data_path, 'ImageSets', 'Main',
self.image_set + '.txt')
annocache = os.path.join(self.cache_path,
self.name + '_annotations.pkl')
aps = []
ars = []
nobs = []
# The PASCAL VOC metric changed in 2010
use_07_metric = True if int(self.year) < 2010 else False
print('VOC07 metric? ' + ('Y' if use_07_metric else 'No'))
for cls_ind, cls in enumerate(self.classes):
if cls == '__background__':
continue
filename = self.get_result_file_template().format(cls)
rec, prec, ap, ar, npos = voc_eval(filename,
annopath,
imageset_file,
cls,
annocache,
ovthresh=0.5,
use_07_metric=use_07_metric)
aps += [ap]
ars += [ar]
nobs += [npos]
print('AP for {} = {:.4f}'.format(cls, ap))
print('Mean AP = {:.4f}'.format(np.mean(aps)))
draw_ap(aps,
ars,
nobs,
self.classes[1:],
range_name='all',
tag='map = {:.4f}'.format(np.mean(aps)))
def do_python_eval(self):
"""
python evaluation wrapper
:return: info_str
"""
result_out = True
result_thersh = 0.85
if result_out:
clas = dict()
f = io.open(self.data_path+'/food_info.txt','r',encoding='UTF-8')
lines = f.readlines()
for line in lines:
data = line.split(' ')
data.pop(1)
clas[int(line.split(' ')[1])] = data #clas[24] = [腐竹油菜 3.0 92.8 3.42 4.06 1.99 3.1]
f.close()
result_file = os.path.join(self.result_path, 'results', 'Food' + self.year, 'result_all.txt')
f = io.open(result_file,'w',encoding ='UTF-8' )
f2 = io.open(os.path.join(self.result_path, 'results', 'Food' + self.year, 'result_{}.txt'.format(result_thersh)),'w',encoding ='UTF-8')
info_str = ''
annopath = os.path.join(self.data_path, 'Annotations', '{0!s}.xml')
imageset_file = os.path.join(self.data_path, 'ImageSets', 'Main', self.image_set + '.txt')
annocache = os.path.join(self.cache_path, self.name + '_annotations.pkl')
# The PASCAL VOC metric changed in 2010
use_07_metric = True if self.year == 'SDS' or int(self.year) < 2010 else False
print 'VOC07 metric? ' + ('Y' if use_07_metric else 'No')
info_str += 'VOC07 metric? ' + ('Y' if use_07_metric else 'No')
info_str += '\n'
#kinds = ['all', 'small', 'medium', 'large']
kinds = ['all']
Maps = []
for ovthresh in np.arange(0.5, 1.0,0.05):
for k in kinds:
info_str += 'MAP@{} - ({})\n'.format(ovthresh, k)
aps = []
for cls_ind, cls in enumerate(self.classes):
if cls == '__background__':
continue
filename = self.get_result_file_template().format(cls)
rec, prec, ap = voc_eval(filename, annopath, imageset_file, cls, annocache,
ovthresh=ovthresh, use_07_metric=use_07_metric)
aps += [ap]
if result_out:
f.write(clas[int(cls)][0] +' {} = {:.4f}\n'.format(cls, ap))
if ap<float(result_thersh):
f2.write(clas[int(cls)][0] +' {} = {:.4f}\n'.format(cls, ap))
#print(clas[int(cls)][0] +' {} = {:.4f}'.format(cls, ap))
info_str += 'AP for {} = {:.4f}\n'.format(cls, ap)
Maps +=[np.mean(aps)]
print('Mean AP@{:.2f} = {:.4f}'.format(ovthresh, np.mean(aps)))
info_str += 'Mean AP@{:.2f} = {:.4f}\n\n'.format(ovthresh, np.mean(aps))
if result_out:
f.close()
f2.close()
print('{:.4f}'.format( np.mean(Maps)))
info_str+='All Map {:.4f}'.format( np.mean(Maps))
return info_str
