Function do_eval

eval_existingOnes.py:16–91

(opt)

def do_eval(opt):
    # evaluation for whole dataset
    # dataset first in evaluation
    for _data_name in opt.data_lst.split('+'):
        pred_data_dir =  sorted(glob(os.path.join(opt.pred_root, opt.model_lst[0], _data_name)))
        if not pred_data_dir:
            print('Skip dataset {}.'.format(_data_name))
            continue
        gt_src = os.path.join(opt.gt_root, _data_name)
        gt_paths = sorted(glob(os.path.join(gt_src, 'gt', '*')))
        print('#' * 20, _data_name, '#' * 20)
        filename = os.path.join(opt.save_dir, '{}_eval.txt'.format(_data_name))
        tb = pt.PrettyTable()
        tb.vertical_char = '&'
        if config.task == 'DIS5K':
            tb.field_names = ["Dataset", "Method", "maxFm", "wFmeasure", 'MAE', "Smeasure", "meanEm", "HCE", "maxEm", "meanFm", "adpEm", "adpFm"]
        elif config.task == 'COD':
            tb.field_names = ["Dataset", "Method", "Smeasure", "wFmeasure", "meanFm", "maxFm", "meanEm", "maxEm", 'MAE', "adpEm", "adpFm", "HCE"]
        elif config.task == 'HRSOD':
            tb.field_names = ["Dataset", "Method", "Smeasure", "maxFm", "meanEm", 'MAE', "maxEm", "meanFm", "wFmeasure", "adpEm", "adpFm", "HCE"]
        elif config.task == 'DIS5K+HRSOD+HRS10K':
            tb.field_names = ["Dataset", "Method", "maxFm", "wFmeasure", 'MAE', "Smeasure", "meanEm", "HCE", "maxEm", "meanFm", "adpEm", "adpFm"]
        elif config.task == 'P3M-10k':
            tb.field_names = ["Dataset", "Method", "Smeasure", "maxFm", "meanEm", 'MAE', "maxEm", "meanFm", "wFmeasure", "adpEm", "adpFm", "HCE"]
        else:
            tb.field_names = ["Dataset", "Method", "Smeasure", 'MAE', "maxEm", "meanEm", "maxFm", "meanFm", "wFmeasure", "adpEm", "adpFm", "HCE"]
        for _model_name in opt.model_lst[:]:
            print('\t', 'Evaluating model: {}...'.format(_model_name))
            pred_paths = [p.replace(opt.gt_root, os.path.join(opt.pred_root, _model_name)).replace('/gt/', '/') for p in gt_paths]
            # print(pred_paths[:1], gt_paths[:1])
            em, sm, fm, mae, wfm, hce = evaluator(
                gt_paths=gt_paths,
                pred_paths=pred_paths,
                metrics=opt.metrics.split('+'),
                verbose=config.verbose_eval
            )
            if config.task == 'DIS5K':
                scores = [
                    fm['curve'].max().round(3), wfm.round(3), mae.round(3), sm.round(3), em['curve'].mean().round(3), int(hce.round()), 
                    em['curve'].max().round(3), fm['curve'].mean().round(3), em['adp'].round(3), fm['adp'].round(3),
                ]
            elif config.task == 'COD':
                scores = [
                    sm.round(3), wfm.round(3), fm['curve'].mean().round(3), fm['curve'].max().round(3), em['curve'].mean().round(3), em['curve'].max().round(3), mae.round(3),
                    em['adp'].round(3), fm['adp'].round(3), int(hce.round()),
                ]
            elif config.task == 'HRSOD':
                scores = [
                    sm.round(3), fm['curve'].max().round(3), em['curve'].mean().round(3), mae.round(3),
                    em['curve'].max().round(3), fm['curve'].mean().round(3), wfm.round(3), em['adp'].round(3), fm['adp'].round(3), int(hce.round()),
                ]
            elif config.task == 'DIS5K+HRSOD+HRS10K':
                scores = [
                    fm['curve'].max().round(3), wfm.round(3), mae.round(3), sm.round(3), em['curve'].mean().round(3), int(hce.round()), 
                    em['curve'].max().round(3), fm['curve'].mean().round(3), em['adp'].round(3), fm['adp'].round(3),
                ]
            elif config.task == 'P3M-10k':
                scores = [