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test_geodino.py
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test_geodino.py
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import os
import sys
import argparse
import logging
import random
import torch
import gorilla
import numpy as np
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
sys.path.append(os.path.join(BASE_DIR, 'provider'))
sys.path.append(os.path.join(BASE_DIR, 'model'))
sys.path.append(os.path.join(BASE_DIR, 'utils'))
sys.path.append(os.path.join(BASE_DIR, 'lib', 'sphericalmap_utils'))
sys.path.append(os.path.join(BASE_DIR, 'lib', 'pointnet2'))
from solver_category import test_func, get_logger
from dataset_category import TestDataset, TrainingDataset
from evaluation_utils import evaluate
def get_parser():
parser = argparse.ArgumentParser(
description="VI-Net")
# pretrain
parser.add_argument("--gpus",
type=str,
default="0",
help="gpu num")
parser.add_argument("--config",
type=str,
default="config/base.yaml",
help="path to config file")
parser.add_argument("--dataset",
type=str,
default="REAL275",
help="[REAL275 | CAMERA25]")
parser.add_argument("--test_epoch",
type=int,
default=0,
help="test epoch")
args_cfg = parser.parse_args()
return args_cfg
def init():
args = get_parser()
cfg = gorilla.Config.fromfile(args.config)
cfg.dataset = args.dataset
cfg.gpus = args.gpus
cfg.test_epoch = args.test_epoch
cfg.log_dir = os.path.join('log', args.dataset)
cfg.save_path = os.path.join(cfg.log_dir, 'results')
if not os.path.isdir(cfg.save_path):
os.makedirs(cfg.save_path)
logger = get_logger(
level_print=logging.INFO, level_save=logging.WARNING, path_file=cfg.log_dir+"/test_logger.log")
gorilla.utils.set_cuda_visible_devices(gpu_ids=cfg.gpus)
return logger, cfg
if __name__ == "__main__":
logger, cfg = init()
logger.warning(
"************************ Start Logging ************************")
logger.info(cfg)
logger.info("using gpu: {}".format(cfg.gpus))
random.seed(cfg.rd_seed)
torch.manual_seed(cfg.rd_seed)
torch.cuda.manual_seed(cfg.rd_seed)
torch.cuda.manual_seed_all(cfg.rd_seed)
# model
logger.info("=> loading model ...")
from PN2 import Net
ts_model = Net(cfg.n_cls)
from VI_Net_geodino import Net
r_model = Net(cfg.resolution, cfg.ds_rate)
if len(cfg.gpus)>1:
ts_model = torch.nn.DataParallel(ts_model, range(len(cfg.gpus.split(","))))
r_model = torch.nn.DataParallel(r_model, range(len(cfg.gpus.split(","))))
# sim_model = torch.nn.DataParallel(sim_model, range(len(cfg.gpus.split(","))))
ts_model = ts_model.cuda()
r_model = r_model.cuda()
# sim_model= sim_model.cuda()
checkpoint = os.path.join(cfg.log_dir, 'PN2', 'epoch_' + str(0) + '.pth')
logger.info("=> loading PN2 checkpoint from path: {} ...".format(checkpoint))
gorilla.solver.load_checkpoint(model=ts_model, filename=checkpoint)
checkpoint = os.path.join(cfg.log_dir, 'VI_Net_geodino', 'epoch_' + str(cfg.test_epoch) + '.pth')
logger.info("=> loading VI-Net checkpoint from path: {} ...".format(checkpoint))
gorilla.solver.load_checkpoint(model=r_model, filename=checkpoint)
# checkpoint = os.path.join(cfg.log_dir, 'SIM_Net', 'epoch_' + str(10) + '.pth')
# logger.info("=> loading SIM-Net checkpoint from path: {} ...".format(checkpoint))
# gorilla.solver.load_checkpoint(model=sim_model, filename=checkpoint)
#feature_file = os.path.join(BASE_DIR, cfg.feature.feature_path, cfg.feature.ref_feature_file)#.replace('.','_' + str(cfg.test_epoch) + '.'))
#with open(feature_file, 'rb') as f:
# ref_feature= np.load(f, allow_pickle=True)
#ref_feature = torch.FloatTensor(ref_feature)
# train_dataset = TrainingDataset(
# cfg.train_dataset,
# cfg.dataset,
# 'r',
# resolution = cfg.resolution,
# ds_rate = cfg.ds_rate,
# num_img_per_epoch=cfg.num_mini_batch_per_epoch*cfg.train_dataloader.bs,
# )
# # data loader
# train_dataloder = torch.utils.data.DataLoader(
# train_dataset,
# batch_size=cfg.train_dataloader.bs,
# num_workers=int(cfg.train_dataloader.num_workers),
# shuffle=cfg.train_dataloader.shuffle,
# sampler=None,
# drop_last=cfg.train_dataloader.drop_last,
# pin_memory=cfg.train_dataloader.pin_memory
# )
dataset = TestDataset(cfg.test, cfg.dataset, cfg.resolution, cfg.ds_rate)
dataloder = torch.utils.data.DataLoader(
dataset,
batch_size=1,
num_workers=0,
shuffle=False,
drop_last=False
)
save_path = cfg.save_path + '/VI_Net_geodino/epoch_' + str(cfg.test_epoch)
if not os.path.isdir(save_path):
os.makedirs(save_path)
test_func(ts_model, r_model, dataloder, save_path)
evaluate(save_path, logger)