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ensemble.py
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# import argparse
# import pickle
# import os
# import numpy as np
# from tqdm import tqdm
# if __name__ == "__main__":
# parser = argparse.ArgumentParser()
# parser.add_argument('--dataset',
# required=True,
# choices={'ntu/xsub', 'ntu/xview', 'ntu120/xsub', 'ntu120/xset', 'NW-UCLA'},
# help='the work folder for storing results')
# parser.add_argument('--alpha',
# default=1,
# help='weighted summation',
# type=float)
# parser.add_argument('--joint-dir',
# help='Directory containing "epoch1_test_score.pkl" for joint eval results')
# parser.add_argument('--bone-dir',
# help='Directory containing "epoch1_test_score.pkl" for bone eval results')
# parser.add_argument('--joint-motion-dir', default=None)
# parser.add_argument('--bone-motion-dir', default=None)
# arg = parser.parse_args()
# dataset = arg.dataset
# if 'UCLA' in arg.dataset:
# label = []
# with open('./data/' + 'NW-UCLA/' + '/val_label.pkl', 'rb') as f:
# data_info = pickle.load(f)
# for index in range(len(data_info)):
# info = data_info[index]
# label.append(int(info['label']) - 1)
# elif 'ntu120' in arg.dataset:
# if 'xsub' in arg.dataset:
# npz_data = np.load('./data/' + 'ntu120/' + 'NTU120_CSub.npz')
# label = np.where(npz_data['y_test'] > 0)[1]
# elif 'xset' in arg.dataset:
# npz_data = np.load('./data/' + 'ntu120/' + 'NTU120_CSet.npz')
# label = np.where(npz_data['y_test'] > 0)[1]
# elif 'ntu' in arg.dataset:
# if 'xsub' in arg.dataset:
# npz_data = np.load('./data/' + 'ntu/' + 'NTU60_CS.npz')
# label = np.where(npz_data['y_test'] > 0)[1]
# elif 'xview' in arg.dataset:
# npz_data = np.load('./data/' + 'ntu/' + 'NTU60_CV.npz')
# label = np.where(npz_data['y_test'] > 0)[1]
# else:
# raise NotImplementedError
# with open(os.path.join(arg.joint_dir, 'epoch1_test_score.pkl'), 'rb') as r1:
# r1 = list(pickle.load(r1).items())
# with open(os.path.join(arg.bone_dir, 'epoch1_test_score.pkl'), 'rb') as r2:
# r2 = list(pickle.load(r2).items())
# if arg.joint_motion_dir is not None:
# with open(os.path.join(arg.joint_motion_dir, 'epoch1_test_score.pkl'), 'rb') as r3:
# r3 = list(pickle.load(r3).items())
# if arg.bone_motion_dir is not None:
# with open(os.path.join(arg.bone_motion_dir, 'epoch1_test_score.pkl'), 'rb') as r4:
# r4 = list(pickle.load(r4).items())
# right_num = total_num = right_num_5 = 0
# if arg.joint_motion_dir is not None and arg.bone_motion_dir is not None:
# arg.alpha = [0.6, 0.6, 0.4, 0.4]
# for i in tqdm(range(len(label))):
# l = label[i]
# _, r11 = r1[i]
# _, r22 = r2[i]
# _, r33 = r3[i]
# _, r44 = r4[i]
# r = r11 * arg.alpha[0] + r22 * arg.alpha[1] + r33 * arg.alpha[2] + r44 * arg.alpha[3]
# 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
# elif arg.joint_motion_dir is not None and arg.bone_motion_dir is None:
# arg.alpha = [0.6, 0.6, 0.4]
# for i in tqdm(range(len(label))):
# l = label[:, i]
# _, r11 = r1[i]
# _, r22 = r2[i]
# _, r33 = r3[i]
# r = r11 * arg.alpha[0] + r22 * arg.alpha[1] + r33 * arg.alpha[2]
# 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
# else:
# for i in tqdm(range(len(label))):
# l = label[i]
# _, r11 = r1[i]
# _, r22 = r2[i]
# r = r11 + r22 * arg.alpha
# 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('Top1 Acc: {:.4f}%'.format(acc * 100))
# print('Top5 Acc: {:.4f}%'.format(acc5 * 100))
import argparse
import pickle
import numpy as np
from tqdm import tqdm
def ensemble(ds, items):
if 'ntu120' in ds:
num_class=120
if 'xsub' in ds:
npz_data = np.load('./data/ntu120/NTU120_CSub.npz')
label = np.where(npz_data['y_test'] > 0)[1]
elif 'xset' in ds:
npz_data = np.load('./data/ntu120/NTU120_CSet.npz')
label = np.where(npz_data['y_test'] > 0)[1]
elif 'ntu' in ds:
num_class=60
if 'xsub' in ds:
npz_data = np.load('./data/ntu/NTU60_CS.npz')
label = np.where(npz_data['y_test'] > 0)[1]
elif 'xview' in ds:
npz_data = np.load('./data/ntu/NTU60_CV.npz')
label = np.where(npz_data['y_test'] > 0)[1]
elif 'UCLA' in ds:
num_class=10
# npz_data = np.load('./data/ntu/NTU60_CS.npz')
# label = np.where(npz_data['y_test'] > 0)[1]
with open('data/NW-UCLA/val_label.pkl', 'rb') as f:
d = pickle.load(f)
label = []
for item in d:
label.append(int(item['label']) - 1)
else:
raise NotImplementedError
ckpt_dirs, alphas = list(zip(*items))
ckpts = []
for ckpt_dir in ckpt_dirs:
with open(ckpt_dir, 'rb') as f:
ckpts.append(list(pickle.load(f).items()))
right_num = total_num = right_num_5 = 0
for i in tqdm(range(len(label))):
l = label[i]
r = np.zeros(num_class)
for alpha, ckpt in zip(alphas, ckpts):
_, r11 = ckpt[i]
r += r11 * alpha
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('Top1 Acc: {:.4f}%'.format(acc * 100))
print('Top5 Acc: {:.4f}%'.format(acc5 * 100))
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--dataset',
required=True,
choices={'ntu/xsub', 'ntu/xview', 'ntu120/xsub', 'ntu120/xset', 'NW-UCLA'},
help='the work folder for storing results')
parser.add_argument('--position_ckpts', nargs='+',
help='Directory containing "epoch1_test_score.pkl" for position eval results')
parser.add_argument('--motion_ckpts', nargs='+',
help='Directory containing "epoch1_test_score.pkl" for motion eval results')
arg = parser.parse_args()
item = []
for ckpt in arg.position_ckpts:
# item.append((ckpt, 1.5))
item.append((ckpt, 0.6))
for ckpt in arg.motion_ckpts:
# item.append((ckpt, 1))
item.append((ckpt, 0.4))
ensemble(arg.dataset, item)