Bump to 0.0.11 #66
Bump to 0.0.11 #66
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WalkthroughThis update primarily focuses on enhancing the functionality of label conversion to raw arrays and loading predictions from an SLP file. It also includes a minor version bump for the package. Changes
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Review Status
Actionable comments generated: 1
Files selected for processing (2)
- README.md (1 hunks)
- sleap_io/init.py (1 hunks)
Files skipped from review due to trivial changes (1)
- sleap_io/init.py
Additional comments (Suppressed): 1
README.md (1)
- 62-64: Ensure that the existing code for creating labels from raw data is compatible with the newly introduced functionalities for converting labels into raw arrays and loading predictions from an SLP file.
| ### Convert labels to raw arrays | ||
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| ```py | ||
| import sleap_io as sio | ||
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| labels = sio.load_slp("tests/data/slp/centered_pair_predictions.slp") | ||
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| # Convert predictions to point coordinates in a single array. | ||
| trx = labels.numpy() | ||
| n_frames, n_tracks, n_nodes, xy = trx.shape | ||
| assert xy == 2 | ||
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| # Convert to array with confidence scores appended. | ||
| trx_with_scores = labels.numpy(return_confidence=True) | ||
| n_frames, n_tracks, n_nodes, xy_score = trx.shape | ||
| assert xy_score == 3 | ||
| ``` |
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The new functionality to convert labels into raw arrays and load predictions from an SLP file is well implemented. However, there's a minor issue in line 58 where trx.shape should be replaced with trx_with_scores.shape to correctly reflect the shape of the array with confidence scores appended.
- n_frames, n_tracks, n_nodes, xy_score = trx.shape
+ n_frames, n_tracks, n_nodes, xy_score = trx_with_scores.shape 
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