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demo..py
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demo..py
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import utils.gpu as gpu
from modelR.GGHL import GGHL
from tensorboardX import SummaryWriter
from evalR.evaluator_demo import Evaluator
import argparse
import os
import config.config as cfg
import time
import logging
from utils.utils_coco import *
from utils.log import Logger
from torch.cuda import amp
class Tester(object):
def __init__(self, weight_path=None, gpu_id=0, visiual=None, eval=False):
self.img_size = cfg.TEST["TEST_IMG_SIZE"]
self.__num_class = cfg.DATA["NUM"]
self.__conf_threshold = cfg.TEST["CONF_THRESH"]
self.__nms_threshold = cfg.TEST["NMS_THRESH"]
self.__device = gpu.select_device(gpu_id, force_cpu=False)
self.__multi_scale_test = cfg.TEST["MULTI_SCALE_TEST"]
self.__flip_test = cfg.TEST["FLIP_TEST"]
self.__classes = cfg.DATA["CLASSES"]
self.__visiual = visiual
self.__eval = eval
self.__model = GGHL().eval().to(self.__device) # Single GPU
self.__load_model_weights(weight_path)
def __load_model_weights(self, weight_path):
print("loading weight file from : {}".format(weight_path))
weight = os.path.join(weight_path)
chkpt = torch.load(weight, map_location=self.__device)
self.__model.load_state_dict(chkpt) #['model']
del chkpt
def test(self):
img_id = '100000003' #要测试的图像id
with torch.no_grad():
Evaluator(self.__model).Test_single_img(img_id)
if __name__ == "__main__":
global logger
parser = argparse.ArgumentParser()
parser.add_argument('--weight_path', type=str, default='weight/HRSC_50epoch.pt', help='weight file path')
parser.add_argument('--log_val_path', type=str, default='log/', help='weight file path')
parser.add_argument('--visiual', type=str, default=None, help='test data path or None')
parser.add_argument('--eval', action='store_true', default=True, help='eval flag')
parser.add_argument('--gpu_id', type=int, default=0, help='gpu id')
parser.add_argument('--log_path', type=str, default='log/', help='log path')
opt = parser.parse_args()
writer = SummaryWriter(logdir=opt.log_path + '/event')
logger = Logger(log_file_name=opt.log_val_path + '/log_test.txt', log_level=logging.DEBUG,
logger_name='GGHL').get_log()
Tester(weight_path=opt.weight_path, gpu_id=opt.gpu_id, eval=opt.eval, visiual=opt.visiual).test()