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[Docs] Fix docstring format and rescale the image (#802)
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Zaida Zhou
GitHub
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@ -57,7 +57,9 @@ data
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The initialization process of the `BaseDataset` is shown as follows:
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<div align="center">
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<img src="https://user-images.githubusercontent.com/26813582/201585974-1360e2b5-f95f-4273-8cbf-6024e33204ab.png" height="500"/>
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</div>
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1. `load metainfo`: Obtain the meta information of the dataset. The meta information can be obtained from three sources with the priority from high to low:
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@ -57,7 +57,9 @@ data
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数据集基类的初始化流程如下图所示：
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<div align="center">
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<img src="https://user-images.githubusercontent.com/26813582/201585974-1360e2b5-f95f-4273-8cbf-6024e33204ab.png" height="500"/>
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</div>
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1. `load metainfo`：获取数据集的元信息，元信息有三种来源，优先级从高到低为：
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@ -138,19 +138,19 @@ class Visualizer(ManagerMixin):
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>>> # inherit
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>>> class DetLocalVisualizer(Visualizer):
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>>> def add_datasample(self,
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>>> name,
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>>> image: np.ndarray,
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>>> gt_sample:
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>>> Optional['BaseDataElement'] = None,
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>>> pred_sample:
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>>> Optional['BaseDataElement'] = None,
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>>> draw_gt: bool = True,
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>>> draw_pred: bool = True,
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>>> show: bool = False,
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>>> wait_time: int = 0,
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>>> step: int = 0) -> None:
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>>> pass
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>>> def add_datasample(self,
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>>> name,
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>>> image: np.ndarray,
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>>> gt_sample:
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>>> Optional['BaseDataElement'] = None,
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>>> pred_sample:
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>>> Optional['BaseDataElement'] = None,
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>>> draw_gt: bool = True,
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>>> draw_pred: bool = True,
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>>> show: bool = False,
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>>> wait_time: int = 0,
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>>> step: int = 0) -> None:
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>>> pass
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"""
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def __init__(
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@ -375,9 +375,9 @@ class Visualizer(ManagerMixin):
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for more details. Defaults to 'g.
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marker (str, optional): The marker style.
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See :mod:`matplotlib.markers` for more information about
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marker styles. Default to None.
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marker styles. Defaults to None.
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sizes (Optional[Union[np.ndarray, torch.Tensor]]): The marker size.
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Default to None.
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Defaults to None.
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"""
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check_type('positions', positions, (np.ndarray, torch.Tensor))
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positions = tensor2ndarray(positions)
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@ -443,7 +443,7 @@ class Visualizer(ManagerMixin):
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just single value. If ``font_families`` is single value, all
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the texts will have the same font family.
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font_familiy can be 'serif', 'sans-serif', 'cursive', 'fantasy'
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or 'monospace'. Defaults to 'sans-serif'.
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or 'monospace'. Defaults to 'sans-serif'.
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bboxes (Union[dict, List[dict]], optional): The bounding box of the
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texts. If bboxes is None, there are no bounding box around
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texts. ``bboxes`` can have the same length with texts or
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@ -689,7 +689,7 @@ class Visualizer(ManagerMixin):
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If ``line_widths`` is single value, all the lines will
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have the same linewidth. Defaults to 2.
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face_colors (Union[str, tuple, List[str], List[tuple]]):
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The face colors. Default to None.
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The face colors. Defaults to None.
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alpha (Union[int, float]): The transparency of bboxes.
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Defaults to 0.8.
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"""
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@ -734,7 +734,7 @@ class Visualizer(ManagerMixin):
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"""Draw single or multiple bboxes.
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Args:
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polygons (Union[Union[np.ndarray, torch.Tensor],
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polygons (Union[Union[np.ndarray, torch.Tensor],\
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List[Union[np.ndarray, torch.Tensor]]]): The polygons to draw
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with the format of (x1,y1,x2,y2,...,xn,yn).
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edge_colors (Union[str, tuple, List[str], List[tuple]]): The
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@ -756,7 +756,7 @@ class Visualizer(ManagerMixin):
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If ``line_widths`` is single value, all the lines will
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have the same linewidth. Defaults to 2.
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face_colors (Union[str, tuple, List[str], List[tuple]]):
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The face colors. Default to None.
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The face colors. Defaults to None.
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alpha (Union[int, float]): The transparency of polygons.
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Defaults to 0.8.
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"""
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@ -871,28 +871,28 @@ class Visualizer(ManagerMixin):
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"""Draw featmap.
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- If `overlaid_image` is not None, the final output image will be the
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weighted sum of img and featmap.
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weighted sum of img and featmap.
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- If `resize_shape` is specified, `featmap` and `overlaid_image`
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are interpolated.
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are interpolated.
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- If `resize_shape` is None and `overlaid_image` is not None,
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the feature map will be interpolated to the spatial size of the image
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in the case where the spatial dimensions of `overlaid_image` and
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`featmap` are different.
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the feature map will be interpolated to the spatial size of the image
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in the case where the spatial dimensions of `overlaid_image` and
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`featmap` are different.
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- If `channel_reduction` is "squeeze_mean" and "select_max",
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it will compress featmap to single channel image and weighted
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sum to `overlaid_image`.
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it will compress featmap to single channel image and weighted
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sum to `overlaid_image`.
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- if `channel_reduction` is None
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- If topk <= 0, featmap is assert to be one or three
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channel and treated as image and will be weighted sum
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to ``overlaid_image``.
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channel and treated as image and will be weighted sum
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to ``overlaid_image``.
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- If topk > 0, it will select topk channel to show by the sum of
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each channel. At the same time, you can specify the `arrangement`
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to set the window layout.
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each channel. At the same time, you can specify the `arrangement`
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to set the window layout.
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Args:
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featmap (torch.Tensor): The featmap to draw which format is
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