mmsegmentation/docs/en/user_guides/visualization.md

Visualization

MMSegmentation provides segmentation visualization hook, used to visualize validation and testing process prediction results.

Usage

Users can modify default_hooks at each schedule_x.py config file.

For exsample, In _base_/schedules/schedule_20k.py, modify the SegVisualizationHook configuration, set draw to True to enable the storage of network inference results, interval indicates the sampling interval of the prediction results, and when set to 1, each inference result of the network will be saved. interval is set to 50 by default:

default_hooks = dict(
    timer=dict(type='IterTimerHook'),
    logger=dict(type='LoggerHook', interval=50, log_metric_by_epoch=False),
    param_scheduler=dict(type='ParamSchedulerHook'),
    checkpoint=dict(type='CheckpointHook', by_epoch=False, interval=2000),
    sampler_seed=dict(type='DistSamplerSeedHook'),
    visualization=dict(type='SegVisualizationHook', draw=True, interval=1))

vis_backends = [dict(type='LocalVisBackend'),
                dict(type='TensorboardVisBackend')]
visualizer = dict(
    type='SegLocalVisualizer', vis_backends=vis_backends, name='visualizer')

View visualization results in a local folder or use tensorboard.

Find the vis_data path of work_dir after starting training or testing, for example, the vis_data path of a particular test is as follows:

work_dirs/test_visual/20220810_115248/vis_data

The stored results of the local visualization are kept in vis_image under vis_data, while the tensorboard visualization results are executed with the following command:

tensorboard --logdir work_dirs/test_visual/20220810_115248/vis_data