Prefer user instances when calling Labels.numpy()
#996
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@@ Coverage Diff @@
## develop #996 +/- ##
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- Coverage 66.75% 66.75% -0.01%
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Files 127 127
Lines 21469 21474 +5
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+ Hits 14332 14334 +2
- Misses 7137 7140 +3
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talmo
approved these changes
Oct 19, 2022
| @@ -2447,21 +2467,20 @@ def numpy( | |||
| tracks = np.full((n_frames, n_tracks, n_nodes, 2), np.nan, dtype="float32") | |||
| for lf in lfs: | |||
| i = lf.frame_idx - first_frame | |||
| lf_insts: Union[List[Instance], List[PredictedInstance]] = ( | |||
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List[Union[Instance, PredictedInstance]] for mixed lists?
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If a labeled frame has ANY user instances in the frame, then we ONLY use the user instances (the frame is already completely labeled). The lists are never mixed.
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Description
In #772, we added a feature where analysis files prefer user-instances over predicted. This PR extends this preference when calling
Labels.numpy(). If no user instances are found in the frame, then the predicted instances are used. However, if there are user instances in the frame, then we return the user instances.Types of changes
Does this address any currently open issues?
[list open issues here]
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