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)