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minor change

pull/1801/head
xiexinch 2022-07-05 20:43:33 +08:00
parent d54f80c649
commit 761e1a9983
3 changed files with 11 additions and 11 deletions
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2
mmseg/datasets/isprs.py
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@ -7,7 +7,7 @@ from .custom import CustomDataset
class ISPRSDataset(CustomDataset): class ISPRSDataset(CustomDataset):
"""ISPRS dataset. """ISPRS dataset.
In segmentation map annotation for LoveDA, 0 is the ignore index. In segmentation map annotation for ISPRS, 0 is the ignore index.
``reduce_zero_label`` should be set to True. The ``img_suffix`` and ``reduce_zero_label`` should be set to True. The ``img_suffix`` and
``seg_map_suffix`` are both fixed to '.png'. ``seg_map_suffix`` are both fixed to '.png'.
""" """

18
mmseg/metrics/iou_metric.py
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@ -129,7 +129,7 @@ class IoUMetric(BaseMetric):
@staticmethod @staticmethod
def intersect_and_union(pred_label: torch.tensor, label: torch.tensor, def intersect_and_union(pred_label: torch.tensor, label: torch.tensor,
num_classes: int, ignore_index: int): num_classes: int, ignore_index: int):
"""Calculate intersection and Union. """Calculate Intersection and Union.
Args: Args:
pred_label (torch.tensor): Prediction segmentation map pred_label (torch.tensor): Prediction segmentation map
@ -175,22 +175,22 @@ class IoUMetric(BaseMetric):
beta: int = 1): beta: int = 1):
"""Calculate evaluation metrics """Calculate evaluation metrics
Args: Args:
total_area_intersect (ndarray): The intersection of prediction and total_area_intersect (np.ndarray): The intersection of prediction
ground truth histogram on all classes. and ground truth histogram on all classes.
total_area_union (ndarray): The union of prediction and ground total_area_union (np.ndarray): The union of prediction and ground
truth histogram on all classes. truth histogram on all classes.
total_area_pred_label (ndarray): The prediction histogram on all total_area_pred_label (np.ndarray): The prediction histogram on
classes.
total_area_label (ndarray): The ground truth histogram on
all classes. all classes.
metrics (list[str] | str): Metrics to be evaluated, 'mIoU' and total_area_label (np.ndarray): The ground truth histogram on
all classes.
metrics (List[str] | str): Metrics to be evaluated, 'mIoU' and
'mDice'. 'mDice'.
nan_to_num (int, optional): If specified, NaN values will be nan_to_num (int, optional): If specified, NaN values will be
replaced by the numbers defined by the user. Default: None. replaced by the numbers defined by the user. Default: None.
beta (int): Determines the weight of recall in the combined score. beta (int): Determines the weight of recall in the combined score.
Default: 1. Default: 1.
Returns: Returns:
Dict[str, ndarray]: per category evaluation metrics, Dict[str, np.ndarray]: per category evaluation metrics,
shape (num_classes, ). shape (num_classes, ).
""" """

2
mmseg/models/segmentors/encoder_decoder.py
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@ -44,7 +44,7 @@ class EncoderDecoder(BaseSegmentor):
whole_inference()/slide_inference(): encoder_decoder() whole_inference()/slide_inference(): encoder_decoder()
encoder_decoder(): extract_feat() -> decode_head.predict() encoder_decoder(): extract_feat() -> decode_head.predict()
4 The ``_forward`` method is used to output the tensor by running the model, 3. The ``_forward`` method is used to output the tensor by running the model,
which includes two steps: (1) Extracts features to obtain the feature maps which includes two steps: (1) Extracts features to obtain the feature maps
(2)Call the decode head forward function to forward decode head model. (2)Call the decode head forward function to forward decode head model.