Comments (3)
Hi @monjoybme , do you mean the figure bellow?
If yes, I advice you at first do some preprocessing so that the labels between automated segmentations and manual segmentations are the same for the same objects.
For instance,
# exchange the label_1 and label_4 for the numpy array `auto_seg`
auto_seg[auto_seg==4]==999
auto_seg[auto_seg==1]==4
auto_seg[auto_seg==999]==1
from segmentation_metrics.
@Jingnan-Jia Yes, correct. Can you share full code?
from segmentation_metrics.
Solved this problem. Happy to create a pull request if you are interested.
from segmentation_metrics.
Related Issues (19)
- URGENT: Great package, your myutil.py script not included in pip/git version HOT 1
- Import error HOT 6
- Adding TP TN FP FN HOT 5
- "Scan files are None, please check the data directory" HOT 4
- Open-source collaboration
- Unit of Volume Similarity HOT 4
- Type error issue when using this package with Pytest HOT 1
- Logging issues HOT 1
- Add .png suffix HOT 4
- Adding .dcm contour data HOT 1
- Computing values on ground truth does not give perfect scores HOT 8
- Evaluation metric 3D or 2D based segmentation HOT 1
- what will be the input labels for the function of 'get_metrics_dict_all_labels'? HOT 2
- Potential Documentation Optimization HOT 1
- AttributeError: module 'numpy' has no attribute 'Array' HOT 1
- Volume similarity has the wrong sign HOT 3
- Check msd computation HOT 2
- TypeError: 'type' object is not subscriptable, line 144 HOT 2
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from segmentation_metrics.