Run pre-commit on all files

Author: lochhh

.gitignore

@@ -83,4 +83,4 @@ venv/
 **/_version.py
 
 # uv
-uv.lock
+uv.lock

MANIFEST.in

@@ -6,3 +6,4 @@ recursive-exclude * __pycache__
 recursive-exclude * *.py[co]
 recursive-exclude docs *
 recursive-exclude tests *
+recursive-exclude examples *

notebook_annotations_to_coco.py examples/notebook_annotations_to_coco.pynotebook_annotations_to_coco.py renamed to examples/notebook_annotations_to_coco.py

@@ -3,15 +3,18 @@
 # Notes
 # - all projects I tried are with a single video
 # - in LP example project: no video directory
-# - sleap-io assumes frame paths have minimally: labeled-data/<video-name>/<img-name>.<ext>
-#   <img-name> must contain the (sequence of) digits representing the frame index
-#   if <img-name> is alphanumerical, the last sequence of digits is assumed to be the frame index
+# - sleap-io assumes frame paths have minimally:
+#   labeled-data/<video-name>/<img-name>.<ext>
+# - <img-name> must contain the (sequence of) digits representing
+#   the frame index
+# - if <img-name> is alphanumerical, the last sequence of digits is assumed to
+#   be the frame index
 # - when loading DLC files with sleap-io: the frames need to exist
 
 # %%
 from pathlib import Path
 
-from poseinterface.io import format_dlc_annotations_file
+from poseinterface.io import annotations_to_coco
 
 # %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 # Input data: DLC project with a single video
@@ -24,7 +27,7 @@
     / "DLC-openfield-Pranav-2018-10-30"
     / "labeled-data"
     / "m4s1"
-    / Path("CollectedData_Pranav.csv")
+    / "CollectedData_Pranav.csv"
 )
 
 # Output path
@@ -37,8 +40,6 @@
 # %%%%%%%%%%%%
 # Export as COCO
 
-out_json = format_dlc_annotations_file(
-    dlc_annotations_files_csv, out_coco_json
-)
+out_json = annotations_to_coco(dlc_annotations_files_csv, out_coco_json)
 
 # %%

poseinterface/io.py

@@ -1,19 +1,23 @@
 from pathlib import Path
+
 import sleap_io as sio
 from sleap_io.io import dlc
 
-
 _EMPTY_LABELS_ERROR_MSG = {
-    "default": ("No annotations could be extracted from the input file."
-            "Please check that the input file contains labeled frames."),
+    "default": (
+        "No annotations could be extracted from the input file."
+        "Please check that the input file contains labeled frames."
+    ),
     "dlc": (
         "Ensure that the paths to the labelled frames are in the "
         "standard DLC project format: "
         "labeled-data / <video-name> / "
         "<filename-with-frame-number>.<extension>"
         "and that the frames files exist."
-    )
+    ),
 }
+
+
 def annotations_to_coco(
     input_path: Path,
     output_json_path: Path,
@@ -22,45 +26,46 @@ def annotations_to_coco(
     coco_visibility_encoding: str = "ternary",
 ) -> Path:
     """Export annotations file to COCO format.
-    
+
     Parameters
-    ---------- 
+    ----------
     input_path : pathlib.Path
         Path to the input annotations file.
     output_json_path : pathlib.Path
         Path to save the output COCO JSON file.
     coco_image_filenames : str | list[str] | None, optional
-        Optional image filenames to use in the COCO JSON. If provided, 
-        must be a single string (for single-frame videos) or a list of 
-        strings matching the number of labeled frames. If None (default), 
+        Optional image filenames to use in the COCO JSON. If provided,
+        must be a single string (for single-frame videos) or a list of
+        strings matching the number of labeled frames. If None (default),
         generates filenames from video filenames and frame indices.
     coco_visibility_encoding : str, optional
         Encoding scheme for keypoint visibility in the COCO JSON file.
         Options are "ternary" (0: not labeled, 1: labeled but not visible,
         2: labeled and visible) or "binary" (0: not visible, 1: visible).
         Default is "ternary".
-    
+
     Returns
     -------
     pathlib.Path
         Path to the saved COCO JSON file.
-    
+
     Notes
     -----
     The format of the input annotations file is automatically inferred based
-    on its extension. See :func:`sleap_io.io.main.load_file` for supported formats.
+    on its extension. See :func:`sleap_io.io.main.load_file` for supported
+    formats.
     """
     labels = sio.load_file(input_path)
     # Check if labels object is empty
     if len(labels.labeled_frames) == 0:
         error_msg = _EMPTY_LABELS_ERROR_MSG["default"]
         if dlc.is_dlc_file(input_path):
             error_msg += _EMPTY_LABELS_ERROR_MSG["dlc"]
-        raise ValueError(error_msg)    
+        raise ValueError(error_msg)
     sio.save_coco(
         labels,
         output_json_path,
         image_filenames=coco_image_filenames,
-        visibility_encoding=coco_visibility_encoding
+        visibility_encoding=coco_visibility_encoding,
     )
     return output_json_path