def rank(dist):
r = cmc(dist, queryset.ids, testset.ids, queryset.cameras, testset.cameras,
separate_camera_set=False,
single_gallery_shot=False,
first_match_break=True)
m_ap = mean_ap(dist, queryset.ids, testset.ids, queryset.cameras, testset.cameras)
return r, m_ap
def rank(dist):
r = cmc(dist, self.queryset.ids, self.testset.ids, self.queryset.cameras, self.testset.cameras,
self.queryset.clothes, self.testset.clothes,
separate_camera_set=False,
single_gallery_shot=False,
first_match_break=True,
cloth_changing_settings=False)
m_ap = mean_ap(
dist, self.queryset.ids, self.testset.ids, self.queryset.cameras, self.testset.cameras,
self.queryset.clothes, self.testset.clothes,
cloth_changing_settings=False)
return r, m_ap
def evaluate(self):
self.model.eval()
print('extract features, this may take a few minutes')
qf = extract_feature(self.model, tqdm(self.query_loader)).numpy()
gf = extract_feature(self.model, tqdm(self.test_loader)).numpy()
######################### re rank##########################
q_g_dist = np.dot(qf, np.transpose(gf))
q_q_dist = np.dot(qf, np.transpose(qf))
g_g_dist = np.dot(gf, np.transpose(gf))
dist = re_ranking(q_g_dist, q_q_dist, g_g_dist)
queryset = self.queryset
testset = self.testset
m_ap = mean_ap(dist, queryset, testset)
print('[With Re-Ranking] mAP: {:.4f}'.format(m_ap))
#########################no re rank##########################
dist = cdist(qf, gf)
m_ap = mean_ap(dist, queryset, testset)
print('[Without Re-Ranking] mAP: {:.4f}'.format(m_ap))
