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test_stage1.py
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test_stage1.py
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import os
import numpy as np
import torch
import torch.nn as nn
from torch.utils.data import DataLoader
from tqdm import tqdm
import logging
from model.ANFL import MEFARG
from dataset import *
from utils import *
from conf import get_config,set_logger,set_outdir,set_env
def get_dataloader(conf):
print('==> Preparing data...')
testset = HybridDataset(conf.dataset_path, phase='test', transform=image_eval(crop_size=conf.crop_size),
stage=1)
test_loader = DataLoader(testset, batch_size=conf.batch_size, shuffle=False, num_workers=conf.num_workers)
return test_loader, len(testset)
# Test
def test(net,test_loader):
net.eval()
statistics_list = None
for batch_idx, (inputs, targets) in enumerate(tqdm(test_loader)):
with torch.no_grad():
targets = targets.float()
if torch.cuda.is_available():
inputs, targets = inputs.cuda(), targets.cuda()
outputs = net(inputs)
update_list = statistics(outputs, targets.detach(), 0.5)
statistics_list = update_statistics_list(statistics_list, update_list)
mean_f1_score, f1_score_list = calc_f1_score(statistics_list)
mean_acc, acc_list = calc_acc(statistics_list)
return mean_f1_score, f1_score_list, mean_acc, acc_list
def main(conf):
dataset_info = hybrid_infolist
# data
test_loader, test_data_num = get_dataloader(conf)
logging.info("[ test_data_num: {} ]".format( test_data_num))
net = MEFARG(num_main_classes=conf.num_main_classes, num_sub_classes=conf.num_sub_classes, backbone=conf.arc, neighbor_num=conf.neighbor_num, metric=conf.metric)
# resume
if conf.resume != '':
logging.info("Resume form | {} ]".format(conf.resume))
net = load_state_dict(net, conf.resume)
# if torch.cuda.is_available():
# net = nn.DataParallel(net).cuda()
if torch.cuda.is_available():
net = net.cuda()
#test
test_mean_f1_score, test_f1_score, test_mean_acc, test_acc = test(net, test_loader)
# log
infostr = {'test_mean_f1_score {:.2f} test_mean_acc {:.2f}' .format(100.* test_mean_f1_score, 100.* test_mean_acc)}
logging.info(infostr)
infostr = {'F1-score-list:'}
logging.info(infostr)
infostr = dataset_info(test_f1_score)
logging.info(infostr)
infostr = {'Acc-list:'}
logging.info(infostr)
infostr = dataset_info(test_acc)
logging.info(infostr)
# ---------------------------------------------------------------------------------
if __name__=="__main__":
conf = get_config()
conf.evaluate = True
set_env(conf)
# generate outdir name
set_outdir(conf)
# Set the logger
set_logger(conf)
main(conf)