def pred_image(data_root, results_dir):
opt = TestOptions().parse() # get training options
opt = make_val_opt(opt)
opt.phase = 'test'
opt.dataset_mode = 'changedetection'
opt.n_class = 2
opt.SA_mode = 'PAM'
opt.arch = 'mynet3'
opt.model = 'CDFA'
opt.epoch = 'pam'
opt.num_test = np.inf
opt.name = 'pam'
opt.dataroot = data_root
opt.results_dir = results_dir
val(opt)
if i % 5 == 0: # save images to an HTML file
print('processing (%04d)-th image... %s' % (i, img_path))
save_visuals(visuals,save_path,img_path[0])
score = running_metrics.get_scores()
print_current_acc(log_name, opt.epoch, score)
if __name__ == '__main__':
opt = TestOptions().parse() # get training options
opt = make_val_opt(opt)
opt.phase = 'val'
opt.dataroot = 'path-to-LEVIR-CD-test'
opt.dataset_mode = 'changedetection'
opt.n_class = 2
opt.SA_mode = 'PAM'
opt.arch = 'mynet3'
opt.model = 'CDFA'
opt.name = 'pam'
opt.results_dir = './results/'
opt.epoch = '78_F1_1_0.88780'
opt.num_test = np.inf
val(opt)
