Bug in semantic segmentation metric

[xianyu-wang]

Checklist

• [X] I have searched for similar issues.
• [X] I have tested with the latest development wheel.
• [X] I have checked the release documentation and the latest documentation (for master branch).

Describe the issue

I found in semseg_metric.py. the function 'acc()' calculate the mean per-class acc at the end, not overall accuracy as the document describes.

In semantic_segmentation.py, it uses this same value for both 'mean acc' and 'overall acc'

Steps to reproduce the bug

'semantic_segmentation.py' 
Line 638-641:
        for key, val in acc_dicts[-1].items():
            writer.add_scalar("{}/ Overall".format(key), val, epoch)
        for key, val in iou_dicts[-1].items():
            writer.add_scalar("{}/ Overall".format(key), val, epoch)

Line 645-646:
        log.info(f"Mean acc train: {acc_dicts[-1]['Training accuracy']:.3f} "
                 f" eval: {acc_dicts[-1]['Validation accuracy']:.3f}")

'semseg_metric.py' 
Line 54:
        accs.append(np.nanmean(accs))

Error message

No response

Expected behavior

No response

Open3D, Python and System information

- Operating system: Ubuntu 18.04
- Python version: Python 3.8
- Open3D version: 0.14.1+caa3ae0a5
- System type: x86
- Is this remote workstation?: yes
- How did you install Open3D?: build from source

Additional information

No response