mmagic.visualization.vis_backend
¶
Module Contents¶
Classes¶
MMagic visualization backend class. It can write image, config, scalars, |
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Tensorboard visualization backend class. |
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Visualization backend for Pavi. |
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Wandb visualization backend for MMagic. |
- class mmagic.visualization.vis_backend.VisBackend(save_dir: str, img_save_dir: str = 'vis_image', config_save_file: str = 'config.py', scalar_save_file: str = 'scalars.json', ceph_path: Optional[str] = None, delete_local_image: bool = True)[source]¶
Bases:
mmengine.visualization.BaseVisBackend
MMagic visualization backend class. It can write image, config, scalars, etc. to the local hard disk and ceph path. You can get the drawing backend through the experiment property for custom drawing.
Examples
>>> from mmagic.visualization import VisBackend >>> import numpy as np >>> vis_backend = VisBackend(save_dir='temp_dir', >>> ceph_path='s3://temp-bucket') >>> img = np.random.randint(0, 256, size=(10, 10, 3)) >>> vis_backend.add_image('img', img) >>> vis_backend.add_scalar('mAP', 0.6) >>> vis_backend.add_scalars({'loss': [1, 2, 3], 'acc': 0.8}) >>> cfg = Config(dict(a=1, b=dict(b1=[0, 1]))) >>> vis_backend.add_config(cfg)
- Parameters
save_dir (str) – The root directory to save the files produced by the visualizer.
img_save_dir (str) – The directory to save images. Default to ‘vis_image’.
config_save_file (str) – The file name to save config. Default to ‘config.py’.
scalar_save_file (str) – The file name to save scalar values. Default to ‘scalars.json’.
ceph_path (Optional[str]) – The remote path of Ceph cloud storage. Defaults to None.
delete_local (bool) – Whether delete local after uploading to ceph or not. If
ceph_path
is None, this will be ignored. Defaults to True.
- property experiment: VisBackend[source]¶
Return the experiment object associated with this visualization backend.
- add_config(config: mmengine.config.Config, **kwargs) None [source]¶
Record the config to disk.
- Parameters
config (Config) – The Config object
- add_image(name: str, image: numpy.array, step: int = 0, **kwargs) None [source]¶
Record the image to disk.
- Parameters
name (str) – The image identifier.
image (np.ndarray) – The image to be saved. The format should be RGB. Default to None.
step (int) – Global step value to record. Default to 0.
- add_scalar(name: str, value: Union[int, float, torch.Tensor, numpy.ndarray], step: int = 0, **kwargs) None [source]¶
Record the scalar data to disk.
- Parameters
name (str) – The scalar identifier.
value (int, float, torch.Tensor, np.ndarray) – Value to save.
step (int) – Global step value to record. Default to 0.
- add_scalars(scalar_dict: dict, step: int = 0, file_path: Optional[str] = None, **kwargs) None [source]¶
Record the scalars to disk.
The scalar dict will be written to the default and specified files if
file_path
is specified.- Parameters
scalar_dict (dict) – Key-value pair storing the tag and corresponding values. The value must be dumped into json format.
step (int) – Global step value to record. Default to 0.
file_path (str, optional) – The scalar’s data will be saved to the
file_path
file at the same time if thefile_path
parameter is specified. Default to None.
- class mmagic.visualization.vis_backend.TensorboardVisBackend(save_dir: str)[source]¶
Bases:
mmengine.visualization.TensorboardVisBackend
Tensorboard visualization backend class.
It can write images, config, scalars, etc. to a tensorboard file.
Examples
>>> from mmengine.visualization import TensorboardVisBackend >>> import numpy as np >>> vis_backend = TensorboardVisBackend(save_dir='temp_dir') >>> img = np.random.randint(0, 256, size=(10, 10, 3)) >>> vis_backend.add_image('img', img) >>> vis_backend.add_scaler('mAP', 0.6) >>> vis_backend.add_scalars({'loss': 0.1,'acc':0.8}) >>> cfg = Config(dict(a=1, b=dict(b1=[0, 1]))) >>> vis_backend.add_config(cfg)
- Parameters
save_dir (str) – The root directory to save the files produced by the backend.
- add_image(name: str, image: numpy.array, step: int = 0, **kwargs)[source]¶
Record the image to Tensorboard. Additional support upload gif files.
- Parameters
name (str) – The image identifier.
image (np.ndarray) – The image to be saved. The format should be RGB.
step (int) – Useless parameter. Wandb does not need this parameter. Default to 0.
- class mmagic.visualization.vis_backend.PaviVisBackend(save_dir: str, exp_name: Optional[str] = None, labels: Optional[str] = None, project: Optional[str] = None, model: Optional[str] = None, description: Optional[str] = None)[source]¶
Bases:
mmengine.visualization.BaseVisBackend
Visualization backend for Pavi.
- property experiment: VisBackend[source]¶
Return the experiment object associated with this visualization backend.
- add_image(name: str, image: numpy.array, step: int = 0, **kwargs) None [source]¶
Record the image to Pavi.
- Parameters
name (str) – The image identifier.
image (np.ndarray) – The image to be saved. The format should be RGB. Default to None.
step (int) – Global step value to record. Default to 0.
- add_scalar(name: str, value: Union[int, float, torch.Tensor, numpy.ndarray], step: int = 0, **kwargs) None [source]¶
Record the scalar data to Pavi.
- Parameters
name (str) – The scalar identifier.
value (int, float, torch.Tensor, np.ndarray) – Value to save.
step (int) – Global step value to record. Default to 0.
- add_scalars(scalar_dict: dict, step: int = 0, file_path: Optional[str] = None, **kwargs) None [source]¶
Record the scalars to Pavi.
The scalar dict will be written to the default and specified files if
file_path
is specified.- Parameters
scalar_dict (dict) – Key-value pair storing the tag and corresponding values. The value must be dumped into json format.
step (int) – Global step value to record. Default to 0.
file_path (str, optional) – The scalar’s data will be saved to the
file_path
file at the same time if thefile_path
parameter is specified. Default to None.
- class mmagic.visualization.vis_backend.WandbVisBackend(save_dir: str, init_kwargs: Optional[dict] = None, define_metric_cfg: Union[dict, list, None] = None, commit: Optional[bool] = True, log_code_name: Optional[str] = None, watch_kwargs: Optional[dict] = None)[source]¶
Bases:
mmengine.visualization.WandbVisBackend
Wandb visualization backend for MMagic.
- add_image(name: str, image: numpy.array, step: int = 0, **kwargs)[source]¶
Record the image to wandb. Additional support upload gif files.
- Parameters
name (str) – The image identifier.
image (np.ndarray) – The image to be saved. The format should be RGB.
step (int) – Useless parameter. Wandb does not need this parameter. Default to 0.