def test(self):
epoch = self.scheduler.last_epoch + 1
lr = self.scheduler.get_lr()[0]
self.model.eval()
qf = self.extract_feature(self.query_loader).numpy()
gf = self.extract_feature(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)
r = cmc(dist, self.queryset.ids, self.testset.ids, self.queryset.cameras, self.testset.cameras,
separate_camera_set=True,
single_gallery_shot=False,
first_match_break=True)
m_ap = mean_ap(dist, self.queryset.ids, self.testset.ids, self.queryset.cameras, self.testset.cameras)
print('epoch:{:d} lr:{:.6f} [ re_rank] mAP: {:.4f} rank1: {:.4f} rank3: {:.4f} rank5: {:.4f} rank10: {:.4f}'
.format(epoch, lr, m_ap, r[0], r[2], r[4], r[9]))
#########################no re rank##########################
dist = cdist(qf, gf)
r = cmc(dist, self.queryset.ids, self.testset.ids, self.queryset.cameras, self.testset.cameras,
separate_camera_set=True,
single_gallery_shot=False,
first_match_break=True)
m_ap = mean_ap(dist, self.queryset.ids, self.testset.ids, self.queryset.cameras, self.testset.cameras)
print('epoch:{:d} lr:{:.6f} [no re_rank] mAP: {:.4f} rank1: {:.4f} rank3: {:.4f} rank5: {:.4f} rank10: {:.4f}'
.format(epoch, lr, m_ap, r[0], r[2], r[4],r[9]))
qf = self.extract_feature(self.query_loader1).numpy()
gf = self.extract_feature(self.test_loader1).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)
r = cmc(dist, self.queryset1.ids, self.testset1.ids, self.queryset1.cameras, self.testset1.cameras,
separate_camera_set=True,
single_gallery_shot=False,
first_match_break=True)
m_ap = mean_ap(dist, self.queryset1.ids, self.testset1.ids, self.queryset1.cameras, self.testset1.cameras)
print('epoch:{:d} lr:{:.6f} [ re_rank] mAP: {:.4f} rank1: {:.4f} rank3: {:.4f} rank5: {:.4f} rank10: {:.4f}'
.format(epoch, lr, m_ap, r[0], r[2], r[4], r[9]))
#########################no re rank##########################
dist = cdist(qf, gf)
r = cmc(dist, self.queryset1.ids, self.testset1.ids, self.queryset1.cameras, self.testset1.cameras,
separate_camera_set=True,
single_gallery_shot=False,
first_match_break=True)
m_ap = mean_ap(dist, self.queryset1.ids, self.testset1.ids, self.queryset1.cameras, self.testset1.cameras)
print('epoch:{:d} lr:{:.6f} [no re_rank] mAP: {:.4f} rank1: {:.4f} rank3: {:.4f} rank5: {:.4f} rank10: {:.4f}'
.format(epoch, lr, m_ap, r[0], r[2], r[4], r[9]))
def test(self):
epoch = self.scheduler.last_epoch + 1
self.ckpt.write_log('\n[INFO] Test:')
self.model.eval()
self.ckpt.add_log(torch.zeros(1, 5))
qf = self.extract_feature(self.query_loader).numpy()
gf = self.extract_feature(self.test_loader).numpy()
if self.args.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)
else:
dist = cdist(qf, gf)
r = cmc(dist,
self.queryset.ids,
self.testset.ids,
self.queryset.cameras,
self.testset.cameras,
separate_camera_set=False,
single_gallery_shot=False,
first_match_break=True)
m_ap = mean_ap(dist, self.queryset.ids, self.testset.ids,
self.queryset.cameras, self.testset.cameras)
self.ckpt.log[-1, 0] = m_ap
self.ckpt.log[-1, 1] = r[0]
self.ckpt.log[-1, 2] = r[2]
self.ckpt.log[-1, 3] = r[4]
self.ckpt.log[-1, 4] = r[9]
best = self.ckpt.log.max(0)
self.ckpt.write_log(
'[INFO] mAP: {:.4f} rank1: {:.4f} rank3: {:.4f} rank5: {:.4f} rank10: {:.4f} (Best: {:.4f} @epoch {})'
.format(m_ap, r[0], r[2], r[4], r[9], best[0][0],
(best[1][0] + 1) * self.args.test_every))
if not self.args.test_only:
self.ckpt.save(self,
epoch,
is_best=((best[1][0] + 1) *
self.args.test_every == epoch))