text stringlengths 1 93.6k |
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print("test time: %0.4fs" % (end - start))
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# <FILESEP>
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import os
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import numpy as np
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import torch
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from options.test_options import TestOptions
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from data.data_loader import TestInputFetcher
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from model import create_model
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from processor import Processor
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from utils.logger import Logger
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f = open('contents.txt', 'r')
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contents = [line.strip() for line in f.readlines()]
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f = open('styles.txt', 'r')
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styles = [line.strip() for line in f.readlines()]
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output_dir = 'output/'
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src_file = os.path.join(output_dir, 'walking_neutral.bvh')
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ref_file = os.path.join(output_dir, 'jumping_old.bvh')
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if __name__ == '__main__':
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test_options = TestOptions()
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opt = test_options.parse()
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print('Start test on cuda:%s' % opt.gpu_ids)
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fetcher = TestInputFetcher(opt)
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# create model, trainer, logger
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model = create_model(opt)
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tester = Processor(opt)
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logger = Logger(opt)
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if opt.load_latest:
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model.load_networks()
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opt.load_iter = model.get_current_iter()
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else:
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model.load_networks(opt.load_iter)
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print('Parameters/Optimizers are loaded from the iteration %d' % opt.load_iter)
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cls_name = os.path.split(src_file)[1][:-4]
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src_con = contents.index(cls_name.split('_')[0])
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src_sty = styles.index(cls_name.split('_')[1])
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cls_name = os.path.split(ref_file)[1][:-4]
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ref_con = contents.index(cls_name.split('_')[0])
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ref_sty = styles.index(cls_name.split('_')[1])
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inputs = {}
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src_input = fetcher.get_data(src_file, sty=src_sty, con=src_con, type='src')
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ref_input = fetcher.get_data(ref_file, sty=ref_sty, con=ref_con, start=0, end=64, type='ref')
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latent_input = fetcher.get_latent()
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inputs.update(src_input)
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inputs.update(ref_input)
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inputs.update(latent_input)
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# stylize with a reference motion
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output_ref = tester.test(model, inputs, alter='ref')
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# stylize with a random noise
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output_latent = tester.test(model, inputs, alter='latent')
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output_ref_file = os.path.join(output_dir, 'output_ref.bvh')
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output_latent_file = os.path.join(output_dir, 'output_latent.bvh')
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logger.save_output(output_ref, inputs['x_real']['traj'], inputs['x_real']['feet'][0].cpu().numpy(), filename=output_ref_file, fs_fix=True)
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logger.save_output(output_latent, inputs['x_real']['traj'], inputs['x_real']['feet'][0].cpu().numpy(), filename=output_latent_file, fs_fix=True)
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# <FILESEP>
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# -*- coding: utf-8 -*-
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######################
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# Author : 高明飞
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# Data : 2016-07-21
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# Brief : 用于获取浙大考试中心网站新通知的爬虫
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######################
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import requests, time, re, logging, sqlite3
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from bs4 import BeautifulSoup
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import WebsiteBase
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class ZJU_KSZX(WebsiteBase.WebsiteBase):
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def __init__(self, AgentID):
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super().__init__('浙大考试中心', 'ZJU_KSZX', AgentID, False, ['全国计算机等级考试'], 7)
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# Return number of pages
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def GetPageRange(self):
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return range(1)
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# Use requests to get the main page, return response
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def GetMainPage(self, page):
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return requests.get('http://kszx.zju.edu.cn/Default.aspx', timeout=21)
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# Return soup
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def GetEnclose(self, soup):
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return soup.find('div', id='main')
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