diff --git a/docs/source/_static/DLC_to_poseinterface_worklow.svg b/docs/source/_static/DLC_to_poseinterface_worklow.svg
new file mode 100644
index 0000000..11d9af8
--- /dev/null
+++ b/docs/source/_static/DLC_to_poseinterface_worklow.svg
@@ -0,0 +1,5 @@
+
+
+DLC project benchmark project {DLCProjectName}/ └── labeled-data/ ├── videos/ ├── {VideoName}.mp4 └── {VideoName}/ ├── CollectedData_{Name}.csv ├── img{index}.png ├── img{index}.png ├── {VideoName}{model}.csv └── {VideoName}{model}.h5 poseinterface_benchmarks/ └── Train/ └── {BenchmarkProjectName}/ ├── Frames/ ├── sub-{ID}_ses-{ID}_cam-{ID}_frame-{index}.png ├── sub-{ID}_ses-{ID}_cam-{ID}_frame-{index}.png ├── ... └── sub-{ID}_ses-{ID}_cam-{ID}_framelabels.json ├── sub-{ID}_ses-{ID}_cam-{ID}.mp4 └── sub-{ID}_ses-{ID}/ ├── sub-{ID}_ses-{ID}_cam-{ID}_start-{index}_dur-{N}.mp4 ├── sub-{ID}_ses-{ID}_cam-{ID}_start-{index}_dur-{N}_cliplabels.json └── ... └── ... annotations_to_poseinterface frames_to_poseinterface video_to_poseinterface predictions_to_poseinterface ├── sub-{ID}_ses-{ID}_cam-{ID}_videolabels.json extract_clip exctract_clip 1. Convert project run once per session 2. Extract clips can be run many times per session └── Clips/ ,.``
-# instead of the required
-# ``labeled-data//.``.
-# We fixed this by replacing the commas with slashes in the csv file.
-
-source_labels_dir = (
- source_project_dir / "labeled-data" / source_video_name.replace(".mp4", "")
-)
-source_annotations_path = source_labels_dir / "CollectedData_Loukia.csv"
-
-# Create Frames directory inside the session directory
-target_frames_dir = target_session_dir / "Frames"
-target_frames_dir.mkdir(parents=True, exist_ok=True)
-
-# %%
-# Convert DLC annotations to COCO format
-# --------------------------------------
-# Here we use the :func:`annotations_to_poseinterface`
-# function from `poseinterface.io`
-# which wraps around `sleap_io` functionality to perform the conversion.
-
-output_annotations_path = annotations_to_poseinterface(
- input_path=source_annotations_path,
- output_dir=target_frames_dir,
- sub_id=subject_id,
- ses_id=session_id,
- cam_id=view_id,
-)
-print(f"Saved COCO annotations to: {output_annotations_path}")
-
-# %%
-# Copy labeled frames to target directory
-# ---------------------------------------
-# Copy the frames used for labeling and rename them to follow
-# the naming convention:
-# ``sub-{subjectID}_ses-{SessionID}_view-{ViewID}_frame-{FrameID}.png``
-
-for source_frame_path in source_labels_dir.glob("*.png"):
- # Extract frame number from original filename, e.g. "img0042.png" -> "0042"
- frame_number = source_frame_path.stem.replace("img", "")
- target_frame_path = (
- target_frames_dir / f"{video_id}_frame-{frame_number}.png"
- )
- if not target_frame_path.exists():
- shutil.copy2(source_frame_path, target_frame_path)
-
-print(f"Copied labeled frames to: {target_frames_dir}")
-
-# %%
diff --git a/examples/convert_dlc_to_benchmark.py b/examples/convert_dlc_to_benchmark.py
new file mode 100644
index 0000000..92fd996
--- /dev/null
+++ b/examples/convert_dlc_to_benchmark.py
@@ -0,0 +1,356 @@
+"""Convert DeepLabCut project to benchmark dataset
+==================================================
+
+Create a ``poseinterface`` benchmark dataset from a DeepLabCut (DLC) project.
+"""
+
+# sphinx_gallery_thumbnail_path = '_static/project_icon.png'
+
+# %%
+# Imports
+# -------
+import json
+import shutil
+import tempfile
+from datetime import datetime, timezone
+from pathlib import Path
+
+import poseinterface
+from poseinterface.clips import extract_clip
+from poseinterface.io import (
+ annotations_to_poseinterface,
+ frames_to_poseinterface,
+ predictions_to_poseinterface,
+ video_to_poseinterface,
+)
+from poseinterface.utils import tree
+
+# %%
+# Overview
+# --------
+# We'll handle the conversion in two steps:
+#
+# 1. **Convert:** DLC project files (videos, frame annotations, and
+# keypoint predictions) are restructured into the
+# :ref:`poseinterface benchmark layout `.
+# 2. **Extract clips:** Short video clips and their labels are extracted
+# from the converted videos and their corresponding keypoint
+# predictions, ready for expert review.
+#
+# .. figure:: /_static/DLC_to_poseinterface_worklow.svg
+# :alt: Workflow diagram showing how a DLC project is converted
+# to a poseinterface benchmark dataset
+# :align: center
+#
+# High-level overview of the two-step conversion workflow.
+
+# %%
+# Source DLC project
+# ------------------
+# We work with a dataset from the
+# `Sainsbury Wellcome Centre (SWC) `_.
+#
+# .. note::
+#
+# This example runs against a lightweight fixture shipped with the
+# repository (under ``tests/data/``). This fixture contains only a subset
+# of the original DLC project, and is intended for testing and demonstration
+# purposes.
+#
+# Replace ``source_project_dir`` and ``benchmark_base_dir`` with the paths
+# to your DLC project and benchmark dataset directories, respectively. Keep
+# in mind that your project will contain more files than are shown here.
+
+
+source_project_dir = (
+ Path(".").resolve().parent
+ / "tests"
+ / "data"
+ / "dlc"
+ / "MouseTopDown-Loukia-2022-09-13"
+)
+print(tree(source_project_dir, level=1, exclude_hidden=True))
+
+# For this example we use a temporary directory, cleaned up at the end.
+benchmark_base_dir = Path(tempfile.mkdtemp(prefix="poseinterface-benchmark-"))
+print(f"\nBenchmark dataset will be saved to: {benchmark_base_dir}")
+
+# %%
+# The two source project sub-directories we care about are:
+#
+# - ``videos/``: the session videos and their corresponding prediction files.
+# - ``labeled-data/``: sampled frames and their keypoint annotations.
+#
+# Let's peek inside each.
+
+print(tree(source_project_dir / "videos", level=1, exclude_hidden=True))
+
+# %%
+# In ``videos/``, each video (ending in ``converted.mp4``) has a companion .csv
+# prediction file.
+
+print(tree(source_project_dir / "labeled-data", level=2, exclude_hidden=True))
+
+# %%
+# In ``labeled-data/``, the sub-directories mirror the video names (without
+# .mp4) and contain the sampled frame images (.png) and their annotations
+# (.csv). In real projects you may also find predictions and annotations in
+# .h5 format, as well as filtered prediction files.
+
+# %%
+# Define sessions to convert
+# ---------------------------
+# We select two sessions from the DLC project and assign each to either
+# the ``Train`` or ``Test`` split of the
+# :ref:`benchmark dataset `.
+# You may expand this list with more sessions, but ensure that each session
+# belongs to exactly one split, and that the same subject doesn't appear in
+# both splits (to avoid data leakage).
+# All videos use the same top-down camera view (``cam-topdown``).
+
+sessions = [
+ {
+ "split": "Train",
+ "source_video": "M727755_EPM_20200317_170544999-converted.mp4",
+ "sub_id": "M727755",
+ "ses_id": "20200317",
+ "cam_id": "topdown",
+ },
+ {
+ "split": "Test",
+ "source_video": "M708154_EPM_20200317_185651629-converted.mp4",
+ "sub_id": "M708154",
+ "ses_id": "20200317",
+ "cam_id": "topdown",
+ },
+]
+
+project_name = "SWC-plusmaze"
+
+# %%
+# Convert to benchmark format
+# ----------------------------
+# For each session we:
+#
+# 1. copy (and re-encode, if necessary) the session video;
+# 2. convert DLC keypoint annotations to COCO JSON, as well as copy and
+# rename the corresponding frame images;
+# 3. convert DLC keypoint predictions to COCO JSON.
+
+for session in sessions:
+ split = session["split"]
+ ids = {k: session[k] for k in ["sub_id", "ses_id", "cam_id"]}
+ sub_ses_prefix = f"sub-{ids['sub_id']}_ses-{ids['ses_id']}"
+ sub_ses_cam_prefix = f"{sub_ses_prefix}_cam-{ids['cam_id']}"
+ source_video_path = source_project_dir / "videos" / session["source_video"]
+ source_frames_dir = (
+ source_project_dir / "labeled-data" / source_video_path.stem
+ )
+ target_session_dir = (
+ benchmark_base_dir / split / project_name / sub_ses_prefix
+ )
+ target_frames_dir = target_session_dir / "Frames"
+ target_frames_dir.mkdir(parents=True, exist_ok=True)
+
+ print(f"Converting session: {split}/{project_name}/{sub_ses_prefix}")
+ # Copy the session video, re-encoding to H.264/yuv420p if necessary
+ video_to_poseinterface(
+ input_video=source_video_path,
+ output_video_dir=target_session_dir,
+ **ids,
+ )
+ print(f"\tvideo: {source_video_path.name} -> {sub_ses_cam_prefix}.mp4")
+
+ # Convert DLC annotations to COCO frame labels JSON, then copy the
+ # corresponding frame images with standardised poseinterface filenames.
+ # In real projects there may be multiple annotation CSVs (e.g. for
+ # different labelers); adjust the glob pattern to select the right one.
+ source_annotations_path = next(
+ source_frames_dir.glob("CollectedData_*.csv"),
+ None,
+ )
+ if source_annotations_path is None:
+ print(
+ f"\tNo CollectedData CSV found in {source_frames_dir}."
+ " Skipping annotations-to-poseinterface conversion."
+ )
+ else:
+ framelabels_path = annotations_to_poseinterface(
+ input_path=source_annotations_path,
+ output_dir=target_frames_dir,
+ format="frame",
+ **ids,
+ )
+ frames_to_poseinterface(
+ input_dir=source_frames_dir,
+ output_dir=target_frames_dir,
+ framelabels_path=framelabels_path,
+ )
+ print(
+ f"\tannotations (+ frame images): {source_annotations_path.name} "
+ f"-> {framelabels_path.name}"
+ )
+
+ # Convert DLC predictions to COCO video labels JSON for clip extraction.
+ # In real projects there may be multiple prediction CSVs (e.g. filtered
+ # versions); adjust the glob pattern to select the right one.
+ source_predictions_path = next(
+ (source_project_dir / "videos").glob(f"{source_video_path.stem}*.csv"),
+ None,
+ )
+ if source_predictions_path is None:
+ print(
+ f"\tNo prediction CSV found for {source_video_path.stem!r} in "
+ f"{source_project_dir / 'videos'}. Skipping predictions-to-"
+ "poseinterface conversion."
+ )
+ else:
+ predictions_to_poseinterface(
+ input_path=source_predictions_path,
+ video_path=source_video_path,
+ output_dir=target_session_dir,
+ **ids,
+ )
+ print(
+ f"\tpredictions: {source_predictions_path.name} -> "
+ f"{sub_ses_cam_prefix}_videolabels.json"
+ )
+ print("Done.\n")
+
+# %%
+# The resulting benchmark dataset:
+
+print(tree(benchmark_base_dir, level=5))
+
+# %%
+# .. note::
+#
+# Frame labels (``framelabels.json``) are generated for both splits, but in
+# the **published** dataset the ``Test`` split intentionally omits them for
+# evaluation. See the
+# :ref:`folder structure specification` for
+# details.
+#
+# The ``videolabels.json`` files generated alongside each session video are
+# intermediate artifacts used for clip extraction in the next section, and
+# will not be included in the published dataset.
+
+
+# %%
+# Extract clips
+# -------------
+# Clips (short video segments) can be extracted from the converted session
+# videos. When the ``videolabels.json`` files are present, the corresponding
+# clip label files (``cliplabels.json``) are generated automatically during
+# clip extraction.
+# These clip label files should then be proof-read and corrected by
+# experts before being included in the benchmark dataset.
+#
+# First, we specify the clip-extraction parameters. This step can be repeated
+# with different parameters to incrementally expand the clip set.
+
+duration = 5 # in frames
+start_frames = [25, 50, 75]
+print(f"Extracting {duration}-frame clips starting at frames: {start_frames}")
+
+# %%
+# We loop over all sessions and extract clips at each start frame.
+# The resulting video clips and their ``cliplabels.json`` files are saved
+# in a ``Clips/`` subdirectory within each session folder.
+
+for session in sessions:
+ sub_ses_prefix = f"sub-{session['sub_id']}_ses-{session['ses_id']}"
+ sub_ses_cam_prefix = f"{sub_ses_prefix}_cam-{session['cam_id']}"
+ session_dir = (
+ benchmark_base_dir / session["split"] / project_name / sub_ses_prefix
+ )
+
+ for start_frame in start_frames:
+ clip_path, _ = extract_clip(
+ video_path=session_dir / f"{sub_ses_cam_prefix}.mp4",
+ start_frame=start_frame,
+ duration=duration,
+ )
+ print(f"Extracted clip: {clip_path.stem}")
+
+
+# %%
+# The resulting benchmark dataset, including the extracted clips and their
+# corresponding labels:
+
+print(tree(benchmark_base_dir, level=5))
+
+
+# %%
+# .. note::
+#
+# In the published dataset, the ``Train`` split includes all
+# ``cliplabels.json`` files. The ``Test`` split omits all
+# ``cliplabels.json`` files and instead provides only clip start labels
+# (``startlabels.json``), derived from each clip's first frame,
+# to support point-tracker evaluation.
+# The ``videolabels.json`` files generated in the previous section are
+# intermediate artifacts used for clip extraction, and are never shared.
+# See the :ref:`folder structure specification` for details.
+
+
+# %%
+# Record provenance (optional)
+# ----------------------------
+# This step is optional and can be safely skipped, but it is highly recommended
+# when converting real data, for book-keeping and reproducibility purposes.
+#
+# We save a copy of this script alongside a JSON sidecar with the
+# ``poseinterface`` version (including git commit, via ``setuptools_scm``)
+# and a UTC timestamp. Both files are written to a top-level
+# ``.provenance/`` folder, named by project, so multiple projects under the
+# same ``benchmark_base_dir`` stay distinct.
+
+# sphinx_gallery_capture_repr = ()
+provenance_dir = benchmark_base_dir / ".provenance"
+provenance_dir.mkdir(parents=True, exist_ok=True)
+
+# ``__file__`` is set when running this script directly with Python, but not
+# when sphinx-gallery executes it during the docs build, guard accordingly.
+script_path_str = globals().get("__file__")
+if script_path_str:
+ shutil.copy(Path(script_path_str), provenance_dir / f"{project_name}.py")
+
+(provenance_dir / f"{project_name}.json").write_text(
+ json.dumps(
+ {
+ "poseinterface_version": poseinterface.__version__,
+ "converted_at": datetime.now(timezone.utc).isoformat(),
+ "source_project_dir": str(source_project_dir),
+ },
+ indent=2,
+ )
+)
+
+# %%
+# Clean up
+# --------
+# Since this example writes to a temporary directory, we remove it at the end.
+#
+# .. warning::
+#
+# Only run this cell when ``benchmark_base_dir`` points to a temporary
+# location. The guard below refuses to delete anything outside the system
+# temp directory, so it is safe to leave in place when you adapt this
+# example to a real benchmark dataset path.
+
+system_tempdir = Path(tempfile.gettempdir()).resolve()
+target = benchmark_base_dir.resolve()
+if target.is_relative_to(system_tempdir) and target != system_tempdir:
+ shutil.rmtree(target)
+ print(f"Removed temporary benchmark directory: {target}")
+else:
+ print(
+ f"Refusing to remove {target}: not inside system temp dir "
+ f"({system_tempdir}). Delete manually if you really want to."
+ )
diff --git a/poseinterface/io.py b/poseinterface/io.py
index 4a6b798..bbabfa8 100644
--- a/poseinterface/io.py
+++ b/poseinterface/io.py
@@ -5,6 +5,7 @@
import logging
import re
import shutil
+import warnings
from pathlib import Path
from typing import Literal, TypeAlias
@@ -466,6 +467,69 @@ def _reencode_video(
return reencoded_video_path
+def frames_to_poseinterface(
+ input_dir: Path,
+ output_dir: Path,
+ framelabels_path: Path,
+) -> None:
+ """Copy and rename frame images to match filenames in COCO JSON.
+
+ Source frames are matched to target names by frame number: the
+ first group of digits in each source filename is compared against
+ the ``frame-`` field in the COCO ``file_name`` entries.
+
+ Parameters
+ ----------
+ input_dir
+ Directory containing the source frame images (e.g. DLC
+ ``labeled-data//`` folder).
+ output_dir
+ Directory to copy the renamed frames into.
+ framelabels_path
+ Path to a COCO JSON file whose ``images`` entries provide
+ the target filenames.
+
+ Raises
+ ------
+ FileNotFoundError
+ If a source frame cannot be found for a frame number
+ listed in the COCO JSON.
+ """
+ # Build a map from frame number to source image path
+ source_frame_map: dict[int, Path] = {}
+ for ext in ("*.jpg", "*.jpeg", "*.png"):
+ for img_path in input_dir.glob(ext):
+ match = re.search(r"(\d+)", img_path.stem)
+ if match:
+ source_frame_map[int(match.group(1))] = img_path
+
+ if not source_frame_map:
+ raise FileNotFoundError(f"No image files found in {input_dir}")
+
+ with open(framelabels_path) as f:
+ coco_data = json.load(f)
+
+ missing_frames = []
+ for img in coco_data["images"]:
+ target_filename = img["file_name"]
+ frame_number = _extract_frame_number(target_filename)
+ if frame_number not in source_frame_map:
+ missing_frames.append(target_filename)
+ continue
+ target_path = output_dir / target_filename
+ if not target_path.exists():
+ shutil.copy2(source_frame_map[frame_number], target_path)
+
+ if missing_frames:
+ missing = "\n".join(f" {f}" for f in missing_frames)
+ warnings.warn(
+ f"{len(missing_frames)} frame(s) not found in {input_dir} "
+ f"and were skipped:\n{missing}",
+ UserWarning,
+ stacklevel=2,
+ )
+
+
def predictions_to_poseinterface(
input_path: Path | str,
video_path: Path | str,
diff --git a/poseinterface/utils.py b/poseinterface/utils.py
new file mode 100644
index 0000000..b95bd40
--- /dev/null
+++ b/poseinterface/utils.py
@@ -0,0 +1,97 @@
+"""General utility functions for ``poseinterface``."""
+
+from collections.abc import Iterator
+from itertools import islice
+from pathlib import Path
+
+
+def tree(
+ dir_path: Path,
+ *,
+ level: int = -1,
+ limit_to_directories: bool = False,
+ exclude_hidden: bool = False,
+ length_limit: int = 1000,
+) -> str:
+ """Return a visual tree structure of a directory as a string.
+
+ Parameters
+ ----------
+ dir_path
+ Path to the root directory.
+ level
+ Maximum depth to display. ``-1`` means no limit. Default is ``-1``.
+ limit_to_directories
+ If ``True``, only directories are shown. Default is ``False``.
+ exclude_hidden
+ If ``True``, files and directories starting with ``.`` are excluded.
+ Default is ``False``.
+ length_limit
+ Maximum number of lines to include before truncating.
+ Default is ``1000``.
+
+ Returns
+ -------
+ str
+ Tree representation of the directory structure, including a
+ summary line with the count of directories and files.
+
+ Notes
+ -----
+ Based on https://stackoverflow.com/a/59109706 by Aaron Hall, modified
+ by community (see post 'Timeline' for change history).
+ Retrieved 2026-03-27. License: CC BY-SA 4.0.
+
+ Examples
+ --------
+ >>> from pathlib import Path
+ >>> from poseinterface.utils import tree
+ >>> print(tree(Path(".")))
+ """
+ space = " "
+ branch = "│ "
+ tee = "├── "
+ last = "└── "
+
+ dir_path = Path(dir_path)
+ files = 0
+ directories = 0
+
+ def _inner(
+ dir_path: Path, prefix: str = "", level: int = -1
+ ) -> Iterator[str]:
+ nonlocal files, directories
+ if not level:
+ return
+ contents = [
+ d
+ for d in sorted(dir_path.iterdir(), key=lambda d: d.name)
+ if not (exclude_hidden and d.name.startswith("."))
+ ]
+ if limit_to_directories:
+ contents = [d for d in contents if d.is_dir()]
+ last_index = len(contents) - 1
+ for index, path in enumerate(contents):
+ pointer = last if index == last_index else tee
+ if path.is_dir():
+ yield prefix + pointer + path.name + "/"
+ directories += 1
+ extension = branch if pointer == tee else space
+ yield from _inner(
+ path, prefix=prefix + extension, level=level - 1
+ )
+ elif not limit_to_directories:
+ yield prefix + pointer + path.name
+ files += 1
+
+ lines: list[str] = [dir_path.name + "/"]
+ iterator = _inner(dir_path, level=level)
+ for line in islice(iterator, length_limit):
+ lines.append(line)
+ if next(iterator, None):
+ lines.append(f"... length_limit, {length_limit}, reached, counted:")
+ summary = f"\n{directories} directories"
+ if files:
+ summary += f", {files} files"
+ lines.append(summary)
+ return "\n".join(lines)
diff --git a/pyproject.toml b/pyproject.toml
index 919595f..0f9bf3e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -12,8 +12,8 @@ dynamic = ["version"]
dependencies = [
"jupyter>=1.1.1",
+ "movement>=0.16.0",
"sleap-io>=0.6.4",
- "movement"
]
license = {text = "BSD-3-Clause"}
@@ -50,6 +50,7 @@ dev = [
]
docs = [
"linkify-it-py",
+ "matplotlib",
"myst-parser",
"nbsphinx",
"pydata-sphinx-theme",
@@ -140,6 +141,6 @@ commands =
[tool.codespell]
-skip = '.git'
+skip = '.git,*.svg'
check-hidden = true
ignore-words-list = 'reencode'
diff --git a/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/labeled-data/M708154_EPM_20200317_185651629-converted/CollectedData_Loukia.csv b/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/labeled-data/M708154_EPM_20200317_185651629-converted/CollectedData_Loukia.csv
new file mode 100644
index 0000000..a56ee6a
--- /dev/null
+++ b/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/labeled-data/M708154_EPM_20200317_185651629-converted/CollectedData_Loukia.csv
@@ -0,0 +1,6 @@
+scorer,,,Loukia,Loukia,Loukia,Loukia,Loukia,Loukia,Loukia,Loukia
+bodyparts,,,snout,snout,left_ear,left_ear,right_ear,right_ear,tailbase,tailbase
+coords,,,x,y,x,y,x,y,x,y
+labeled-data,M708154_EPM_20200317_185651629-converted,img01841.png,10.0,20.0,15.0,25.0,20.0,30.0,25.0,35.0
+labeled-data,M708154_EPM_20200317_185651629-converted,img08489.png,10.0,20.0,15.0,25.0,20.0,30.0,25.0,35.0
+labeled-data,M708154_EPM_20200317_185651629-converted,img09286.png,10.0,20.0,15.0,25.0,20.0,30.0,25.0,35.0
diff --git a/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/labeled-data/M708154_EPM_20200317_185651629-converted/img01841.png b/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/labeled-data/M708154_EPM_20200317_185651629-converted/img01841.png
new file mode 100644
index 0000000..5e3a5ea
Binary files /dev/null and b/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/labeled-data/M708154_EPM_20200317_185651629-converted/img01841.png differ
diff --git a/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/labeled-data/M708154_EPM_20200317_185651629-converted/img08489.png b/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/labeled-data/M708154_EPM_20200317_185651629-converted/img08489.png
new file mode 100644
index 0000000..27aa6d1
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diff --git a/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/labeled-data/M727755_EPM_20200317_170544999-converted/CollectedData_Loukia.csv b/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/labeled-data/M727755_EPM_20200317_170544999-converted/CollectedData_Loukia.csv
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index 0000000..cb02a32
--- /dev/null
+++ b/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/labeled-data/M727755_EPM_20200317_170544999-converted/CollectedData_Loukia.csv
@@ -0,0 +1,6 @@
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+labeled-data,M727755_EPM_20200317_170544999-converted,img05794.png,10.0,20.0,15.0,25.0,20.0,30.0,25.0,35.0
diff --git a/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/labeled-data/M727755_EPM_20200317_170544999-converted/img00114.png b/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/labeled-data/M727755_EPM_20200317_170544999-converted/img00114.png
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diff --git a/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/videos/M708154_EPM_20200317_185651629-converted.mp4 b/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/videos/M708154_EPM_20200317_185651629-converted.mp4
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diff --git a/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/videos/M708154_EPM_20200317_185651629-convertedDLC_resnet50_MouseTopDownSep13shuffle1_340000.csv b/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/videos/M708154_EPM_20200317_185651629-convertedDLC_resnet50_MouseTopDownSep13shuffle1_340000.csv
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index 0000000..2d33d03
--- /dev/null
+++ b/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/videos/M708154_EPM_20200317_185651629-convertedDLC_resnet50_MouseTopDownSep13shuffle1_340000.csv
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diff --git a/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/videos/M727755_EPM_20200317_170544999-converted.mp4 b/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/videos/M727755_EPM_20200317_170544999-converted.mp4
new file mode 100644
index 0000000..a6025ef
Binary files /dev/null and b/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/videos/M727755_EPM_20200317_170544999-converted.mp4 differ
diff --git a/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/videos/M727755_EPM_20200317_170544999-convertedDLC_resnet50_MouseTopDownSep13shuffle1_340000.csv b/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/videos/M727755_EPM_20200317_170544999-convertedDLC_resnet50_MouseTopDownSep13shuffle1_340000.csv
new file mode 100644
index 0000000..bc4c002
--- /dev/null
+++ b/tests/data/dlc/MouseTopDown-Loukia-2022-09-13/videos/M727755_EPM_20200317_170544999-convertedDLC_resnet50_MouseTopDownSep13shuffle1_340000.csv
@@ -0,0 +1,103 @@
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diff --git a/tests/test_unit/test_io.py b/tests/test_unit/test_io.py
index 4a342a7..7268085 100644
--- a/tests/test_unit/test_io.py
+++ b/tests/test_unit/test_io.py
@@ -23,6 +23,7 @@
_reencode_video,
_update_image_ids,
annotations_to_poseinterface,
+ frames_to_poseinterface,
predictions_to_poseinterface,
video_to_poseinterface,
)
@@ -439,6 +440,106 @@ def test_pad_integers_to_same_width():
assert _pad_integers_to_same_width(input) == expected
+# ---------- Frames to poseinterface ----------------
+
+
+@pytest.fixture
+def frames_coco_json(tmp_path):
+ """Create a minimal COCO JSON with 3 image entries."""
+ data = {
+ "images": [
+ {"id": 100, "file_name": "sub-A_ses-1_cam-top_frame-0100.png"},
+ {"id": 200, "file_name": "sub-A_ses-1_cam-top_frame-0200.png"},
+ {"id": 350, "file_name": "sub-A_ses-1_cam-top_frame-0350.png"},
+ ],
+ "annotations": [],
+ "categories": [],
+ }
+ path = tmp_path / "framelabels.json"
+ path.write_text(json.dumps(data))
+ return path
+
+
+@pytest.fixture
+def frames_source_dir(tmp_path):
+ """Create a source directory with DLC-style frame images."""
+ src = tmp_path / "source_frames"
+ src.mkdir()
+ for name in ["img0100.png", "img0200.png", "img0350.png"]:
+ (src / name).write_bytes(b"fake png")
+ return src
+
+
+@pytest.fixture
+def frames_target_dir(tmp_path):
+ """Create an empty target directory."""
+ tgt = tmp_path / "target_frames"
+ tgt.mkdir()
+ return tgt
+
+
+def test_frames_to_poseinterface_copies_and_renames(
+ frames_source_dir, frames_target_dir, frames_coco_json
+):
+ """Test that frames are copied with standardised names."""
+ frames_to_poseinterface(
+ frames_source_dir, frames_target_dir, frames_coco_json
+ )
+
+ expected_names = {
+ "sub-A_ses-1_cam-top_frame-0100.png",
+ "sub-A_ses-1_cam-top_frame-0200.png",
+ "sub-A_ses-1_cam-top_frame-0350.png",
+ }
+ actual_names = {f.name for f in frames_target_dir.glob("*.png")}
+ assert actual_names == expected_names
+
+
+def test_frames_to_poseinterface_skips_existing(
+ frames_source_dir, frames_target_dir, frames_coco_json
+):
+ """Test that existing target files are not overwritten."""
+ existing = frames_target_dir / "sub-A_ses-1_cam-top_frame-0100.png"
+ existing.write_bytes(b"do not overwrite")
+
+ frames_to_poseinterface(
+ frames_source_dir, frames_target_dir, frames_coco_json
+ )
+
+ assert existing.read_bytes() == b"do not overwrite"
+
+
+def test_frames_to_poseinterface_raises_for_missing_source(
+ frames_target_dir, frames_coco_json, tmp_path
+):
+ """Test FileNotFoundError when source frame is missing."""
+ empty_src = tmp_path / "empty_source"
+ empty_src.mkdir()
+
+ with pytest.raises(FileNotFoundError, match="No image files found"):
+ frames_to_poseinterface(empty_src, frames_target_dir, frames_coco_json)
+
+
+def test_frames_to_poseinterface_warns_for_partial_match(
+ frames_source_dir, frames_target_dir, frames_coco_json
+):
+ """Test that a warning is emitted when some frames are missing."""
+ # Remove one source image so it can't be matched
+ (frames_source_dir / "img0200.png").unlink()
+
+ with pytest.warns(UserWarning, match="1 frame.*not found.*skipped"):
+ frames_to_poseinterface(
+ frames_source_dir, frames_target_dir, frames_coco_json
+ )
+
+ # The two matched frames should still be copied
+ actual_names = {f.name for f in frames_target_dir.glob("*.png")}
+ assert actual_names == {
+ "sub-A_ses-1_cam-top_frame-0100.png",
+ "sub-A_ses-1_cam-top_frame-0350.png",
+ }
+
+
# ---------- Video to poseinterface ----------------
diff --git a/tests/test_unit/test_utils.py b/tests/test_unit/test_utils.py
new file mode 100644
index 0000000..58d0dda
--- /dev/null
+++ b/tests/test_unit/test_utils.py
@@ -0,0 +1,94 @@
+import pytest
+
+from poseinterface.utils import tree
+
+
+class TestTree:
+ """Tests for the tree function that generates
+ a string representation of a directory structure."""
+
+ def test_empty_directory(self, tmp_path):
+ """Test tree of an empty directory."""
+ result = tree(tmp_path)
+ assert result.startswith(tmp_path.name + "/")
+ assert "0 directories" in result
+
+ def test_files_and_directories(self, tmp_path):
+ """Test tree with a mix of files and directories."""
+ (tmp_path / "a_dir").mkdir()
+ (tmp_path / "b_file.txt").touch()
+
+ result = tree(tmp_path)
+ assert "a_dir/" in result
+ assert "b_file.txt" in result
+ assert "b_file.txt/" not in result
+ assert "1 directories" in result
+ assert "1 files" in result
+
+ def test_level_limits_depth(self, tmp_path):
+ """Test that level limits the depth of the tree."""
+ (tmp_path / "a" / "b" / "c").mkdir(parents=True)
+
+ result_shallow = tree(tmp_path, level=1)
+ result_deep = tree(tmp_path, level=3)
+
+ # level=1 shows "a/" but not "b/"
+ assert "a/" in result_shallow
+ assert "b/" not in result_shallow
+ # level=3 shows all
+ assert "c/" in result_deep
+
+ @pytest.mark.parametrize(
+ "tree_kwargs, expected_present, expected_absent",
+ [
+ (
+ {"limit_to_directories": True},
+ ["subdir/", ".hidden_dir/"],
+ ["visible.txt", ".hidden_file"],
+ ),
+ (
+ {"exclude_hidden": True},
+ ["subdir/", "visible.txt"],
+ [".hidden_dir", ".hidden_file"],
+ ),
+ ],
+ )
+ def test_filtering_options(
+ self, tmp_path, tree_kwargs, expected_present, expected_absent
+ ):
+ """Test that filtering options include/exclude entries."""
+ (tmp_path / "subdir").mkdir()
+ (tmp_path / "visible.txt").touch()
+ (tmp_path / ".hidden_dir").mkdir()
+ (tmp_path / ".hidden_file").touch()
+
+ result = tree(tmp_path, **tree_kwargs)
+ for name in expected_present:
+ assert name in result
+ for name in expected_absent:
+ assert name not in result
+
+ def test_length_limit(self, tmp_path):
+ """Test that output is truncated at length_limit."""
+ for i in range(20):
+ (tmp_path / f"file_{i:02d}.txt").touch()
+
+ result = tree(tmp_path, length_limit=5)
+ assert "length_limit" in result
+ assert "5" in result
+
+ def test_sorted_output(self, tmp_path):
+ """Test that entries are sorted alphabetically."""
+ (tmp_path / "cherry.txt").touch()
+ (tmp_path / "apple.txt").touch()
+ (tmp_path / "banana.txt").touch()
+
+ result = tree(tmp_path)
+ lines = result.split("\n")
+ content_lines = [
+ line
+ for line in lines
+ if any(f in line for f in ["apple", "banana", "cherry"])
+ ]
+ names = [line.split("── ")[-1] for line in content_lines]
+ assert names == ["apple.txt", "banana.txt", "cherry.txt"]