8000 Fix path resolution in training & inference by talmo · Pull Request #643 · talmolab/sleap · GitHub
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Fix path resolution in training & inference #643

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Merged
merged 4 commits into from
Feb 9, 2022
Merged

Fix path resolution in training & inference #643

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14ce6bd
Update the labels and filename used in the learning dialog every time.
talmo Feb 9, 2022
e31336f
Use default load_file behavior when no search paths specified
talmo Feb 9, 2022
2717c9b
Use high level load_file in inference
talmo Feb 9, 2022
d10c1b6
Use sleap.load_file in more places
talmo Feb 9, 2022
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6 changes: 6 additions & 0 deletions sleap/gui/app.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1588,6 +1588,7 @@ def _show_learning_dialog(self, mode: str):
return

if self._child_windows.get(mode, None) is None:
# Re-use existing dialog widget.
self._child_windows[mode] = LearningDialog(
mode,
self.state["filename"],
Expand All @@ -1596,6 +1597,11 @@ def _show_learning_dialog(self, mode: str):
self._child_windows[mode]._handle_learning_finished.connect(
self._handle_learning_finished
)
else:
# Update da 8000 ta in existing dialog widget.
self._child_windows[mode].labels = self.labels
self._child_windows[mode].labels_filename = self.state["filename"]
self._child_windows[mode].skeleton = self.labels.skeleton

self._child_windows[mode].update_file_lists()

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2 changes: 1 addition & 1 deletion sleap/nn/data/providers.py
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Expand Up @@ -87,7 +87,7 @@ def from_filename(
Returns:
A `LabelsReader` instance that can create a dataset for pipelining.
"""
labels = sleap.Labels.load_file(filename)
labels = sleap.load_file(filename)
if user_instances:
return cls.from_user_instances(labels)
else:
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2 changes: 1 addition & 1 deletion sleap/nn/inference.py
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Expand Up @@ -2947,7 +2947,7 @@ def _make_provider_from_cli(args: argparse.Namespace) -> Tuple[Provider, str]:
)

if data_path.endswith(".slp"):
labels = sleap.Labels.load_file(data_path)
labels = sleap.load_file(data_path)

if args.only_labeled_frames:
provider = LabelsReader.from_user_labeled_frames(labels)
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11 changes: 7 additions & 4 deletions sleap/nn/training.py
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Expand Up @@ -157,7 +157,7 @@ def from_labels(
"""Create data readers from sleap.Labels datasets as data providers."""
if isinstance(training, str):
logger.info(f"Loading training labels from: {training}")
training = sleap.Labels.load_file(training, video_search=video_search_paths)
training = sleap.load_file(training, video_search=video_search_paths)

if labels_config is not None and labels_config.split_by_inds:
# First try to split by indices if specified in config.
Expand Down Expand Up @@ -192,7 +192,7 @@ def from_labels(
# If validation is still a path, load it.
logger.info(f"Loading validation labels from: {validation}")
validation = sleap.Labels.load_file(
validation, video_search=video_search_paths
validation, search_paths=video_search_paths
)
elif isinstance(validation, float):
logger.info(
Expand All @@ -217,7 +217,7 @@ def from_labels(
if isinstance(test, str):
# If test is still a path, load it.
logger.info(f"Loading test labels from: {test}")
test = sleap.Labels.load_file(test, video_search=video_search_paths)
test = sleap.load_file(test, search_paths=video_search_paths)

test_reader = None
if test is not None:
Expand Down Expand Up @@ -1568,6 +1568,9 @@ def main():
job_config.outputs.save_visualizations |= args.save_viz
if args.labels_path == "":
args.labels_path = None
args.video_paths = args.video_paths.split(",")
if len(args.video_paths) == 0:
args.video_paths = None

logger.info("Versions:")
sleap.versions()
Expand Down Expand Up @@ -1613,7 +1616,7 @@ def main():
training_labels=args.labels_path,
validation_labels=args.val_labels,
test_labels=args.test_labels,
video_search_paths=args.video_paths.split(","),
video_search_paths=args.video_paths,
)
trainer.train()

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