ensemble_4s.py

import argparse
import pickle

import numpy as np
from tqdm import tqdm

parser = argparse.ArgumentParser()
parser.add_argument('--datasets', default='ntu/xsub', choices={'ntu/xsub', 'ntu/xview'},
                    help='the work folder for storing results')
parser.add_argument('--alpha', default=1, help='weighted summation')
arg = parser.parse_args()

dataset = arg.datasets
label = open('./data/' + dataset + '/val_label.pkl', 'rb')
label = np.array(pickle.load(label))
r1 = open('./work_dir/' + dataset + '/agcn_test_forward/epoch1_test_score.pkl', 'rb')
r1 = list(pickle.load(r1).items())
r2 = open('./work_dir/' + dataset + '/agcn_test_reverse/epoch1_test_score.pkl', 'rb')
r2 = list(pickle.load(r2).items())
r3 = open('./work_dir/' + dataset + '/agcn_test_forward_bone/epoch1_test_score.pkl', 'rb')
r3 = list(pickle.load(r3).items())
r4 = open('./work_dir/' + dataset + '/agcn_test_reverse_bone/epoch1_test_score.pkl', 'rb')
r4 = list(pickle.load(r4).items())
right_num = total_num = right_num_5 = 0
for i in tqdm(range(len(label[0]))):
    _, l = label[:, i]
    _, r11 = r1[i]
    _, r22 = r2[i]
    _, r33 = r3[i]
    _, r44 = r4[i]
    # r = r11 + r33 * arg.alpha
    # r = r11 + r22 * arg.alpha + r33 * arg.alpha
    r = r11 * 1 + r22 * 1 + r33 * 1 + r44 * 1
    rank_5 = r.argsort()[-5:]
    right_num_5 += int(int(l) in rank_5)
    r = np.argmax(r)
    right_num += int(r == int(l))
    total_num += 1
acc = right_num / total_num
acc5 = right_num_5 / total_num
print(acc, acc5)