test_produce_maps.py

import os
os.environ["CUDA_VISIBLE_DEVICES"] = ""
import torch
import torch.nn.functional as F
import sys
import torch.nn as nn
import numpy as np
import argparse
import cv2
from Models.model_multi import TMSOD
from Models.data_multi import test_dataset
import time
from Models.data_multi import get_loader

parser = argparse.ArgumentParser()
parser.add_argument('--testsize', type=int, default=384, help='testing size')
parser.add_argument('--test_path', type=str, default='', help='test dataset path')
opt = parser.parse_args()
dataset_path = opt.test_path
model = TMSOD()
model.cuda()
model.load_state_dict({k.replace('module.',''):v for k,v in torch.load('.pth', map_location='cuda:0').items()})
model.eval()
test_datasets = []#'NLPR', 'STERE1000', 'SIP', 'NJUD', 'NLPR', 'DUT-RGBD', 'SSD', 'DUTS-TE', 'HKU-IS' ...

for dataset in test_datasets:
    save_path = './test_maps/' + dataset + '/'
    if not os.path.exists(save_path):
        os.makedirs(save_path)
    image_root = dataset_path + dataset + '/test_data/test_images/'#'/RGB/'
    gt_root = dataset_path + dataset + '/test_data/test_masks/'#'/GT/'
    depth_root = dataset_path + dataset + '/test_data/test_depth/'#'/RGB/'
    test_loader = test_dataset(image_root, gt_root, depth_root, opt.testsize)
    img_num = len(test_loader)
    time_s = time.time()
    for i in range(test_loader.size):
        image, gt, depth, name, image_for_post = test_loader.load_data()
        gt = np.asarray(gt, np.float32)
        gt /= (gt.max() + 1e-8)
        image = image.cuda()
        depth = depth.cuda()
        pre_res = model(image, depth)
        res = pre_res
        res = F.upsample(res, size=gt.shape, mode='bilinear', align_corners=False)
        res = res.sigmoid().data.cpu().numpy().squeeze()
        res = (res - res.min()) / (res.max() - res.min() + 1e-8)
        print('save img to: ', save_path + name.split('/')[-1])
        cv2.imwrite(save_path + name.split('/')[-1], res * 255)
    time_e = time.time()
    print('speed: %f FPS' % (img_num / (time_e - time_s)))
    print('Test Done!')