Can I know about the rank1 precision of the code?(such as on market1501)

[cysu]

Can I know about the rank1 precision of the code?(such as on market1501)

[zydou]

open-reid/reid/evaluators.py

Lines 82 to 98 in 3293ca7

	mAP = mean_ap(distmat, query_ids, gallery_ids, query_cams, gallery_cams)
	print('Mean AP: {:4.1%}'.format(mAP))
	# Compute all kinds of CMC scores
	cmc_configs = {
	'allshots': dict(separate_camera_set=False,
	single_gallery_shot=False,
	first_match_break=False),
	'cuhk03': dict(separate_camera_set=True,
	single_gallery_shot=True,
	first_match_break=False),
	'market1501': dict(separate_camera_set=False,
	single_gallery_shot=False,
	first_match_break=True)}
	cmc_scores = {name: cmc(distmat, query_ids, gallery_ids,
	query_cams, gallery_cams, **params)
	for name, params in cmc_configs.items()}

[YunpengZhai]

@zydou thanks, but what I want to know is the result of evaluation. what precision can it get? thanks!

[zydou]

Calculate mAP:

open-reid/reid/evaluation_metrics/ranking.py

Lines 82 to 83 in 3293ca7

	def mean_ap(distmat, query_ids=None, gallery_ids=None,
	query_cams=None, gallery_cams=None):

Calculate CMC:

open-reid/reid/evaluation_metrics/ranking.py

Lines 18 to 22 in 3293ca7

	def cmc(distmat, query_ids=None, gallery_ids=None,
	query_cams=None, gallery_cams=None, topk=100,
	separate_camera_set=False,
	single_gallery_shot=False,
	first_match_break=False):

[Cysu]

Thank you @zydou for the answer!

Please feel free to reopen the issue if there are any further problems, @YunpengZhai