test_roidb = roidb_read['test_roidb']
N_train = len(train_roidb)
N_test = len(test_roidb)
saver = tf.train.Saver()
with tf.Session() as sess:
init = tf.global_variables_initializer()
sess.run(init)
saver.restore(sess, model_path)
pred_roidb = []
for roidb_id in range(N_test):
if (roidb_id + 1) % 10 == 0:
print(roidb_id + 1)
roidb_use = test_roidb[roidb_id]
if len(roidb_use['rela_gt']) == 0:
pred_roidb.append({})
continue
pred_rela, pred_rela_score = vnet.test_predicate(sess, roidb_use)
pred_roidb_temp = {
'pred_rela': pred_rela,
'pred_rela_score': pred_rela_score,
'sub_box_dete': roidb_use['sub_box_gt'],
'obj_box_dete': roidb_use['obj_box_gt'],
'sub_dete': roidb_use['sub_gt'],
'obj_dete': roidb_use['obj_gt']
}
pred_roidb.append(pred_roidb_temp)
roidb = {}
roidb['pred_roidb'] = pred_roidb
np.savez(save_path, roidb=roidb)
saver = tf.train.Saver()
with tf.Session() as sess:
init = tf.global_variables_initializer()
sess.run(init)
saver.restore(sess, model_path)
pred_roidb = []
sub_roidb = []
obj_roidb = []
for roidb_id in range(N_test):
if (roidb_id+1)%10 == 0:
print(roidb_id + 1)
roidb_use = test_roidb[roidb_id]
if len(roidb_use['rela_gt']) == 0:
pred_roidb.append({})
continue
pred_rela, pred_rela_score, pred_sub , pred_obj = vnet.test_predicate(sess, roidb_use)
pred_roidb_temp = {'pred_rela': pred_rela, 'pred_rela_score': pred_rela_score,
'sub_box_dete': roidb_use['sub_box_gt'], 'obj_box_dete': roidb_use['obj_box_gt'],
'sub_dete': roidb_use['sub_gt'], 'obj_dete': roidb_use['obj_gt'] ,
'original_pred': roidb_use['rela_gt']}
pred_roidb.append(pred_roidb_temp)
sub_roidb.append(pred_sub)
obj_roidb.append(pred_obj)
roidb = {}
roidb['pred_roidb'] = pred_roidb
roidb['subVec'] = sub_roidb
roidb['objVec'] = obj_roidb
np.savez(save_path, roidb=roidb)