mirror of
https://github.com/macaodha/batdetect2.git
synced 2025-06-29 14:41:58 +02:00
Added docstrings for the batdetect2 legacy annotation format
This commit is contained in:
mbsantiago
parent
b78e5a3a2f
commit
bf14f4d37e
@ -22,23 +22,23 @@ from batdetect2.data.annotations.aoef import (
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AOEFAnnotations,
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load_aoef_annotated_dataset,
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)
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from batdetect2.data.annotations.batdetect2_files import (
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from batdetect2.data.annotations.batdetect2 import (
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AnnotationFilter,
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BatDetect2FilesAnnotations,
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load_batdetect2_files_annotated_dataset,
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)
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from batdetect2.data.annotations.batdetect2_merged import (
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BatDetect2MergedAnnotations,
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load_batdetect2_files_annotated_dataset,
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load_batdetect2_merged_annotated_dataset,
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)
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from batdetect2.data.annotations.types import AnnotatedDataset
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__all__ = [
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"load_annotated_dataset",
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"AnnotatedDataset",
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"AOEFAnnotations",
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"AnnotatedDataset",
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"AnnotationFilter",
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"AnnotationFormats",
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"BatDetect2FilesAnnotations",
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"BatDetect2MergedAnnotations",
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"AnnotationFormats",
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"load_annotated_dataset",
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]
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291
batdetect2/data/annotations/batdetect2.py
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291
batdetect2/data/annotations/batdetect2.py
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@ -0,0 +1,291 @@
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"""Loads annotation data from legacy BatDetect2 JSON formats.
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This module provides backward compatibility for loading annotation data stored
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in two related formats used by older BatDetect2 tools:
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1. **`batdetect2` format** (Directory-based): Annotations are stored in
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individual JSON files (one per audio recording) within a specified
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directory.
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Each JSON file contains a `FileAnnotation` structure. Loaded via
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`load_batdetect2_files_annotated_dataset` defined by
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`BatDetect2FilesAnnotations`.
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2. **`batdetect2_file` format** (Single-file): Annotations for multiple
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recordings are merged into a single JSON file, containing a list of
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`FileAnnotation` objects. Loaded via
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`load_batdetect2_merged_annotated_dataset` defined by
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`BatDetect2MergedAnnotations`.
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Both formats use the same internal structure for annotations per file and
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support filtering based on `annotated` and `issues` flags within that
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structure.
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The loading functions convert data from these legacy formats into the modern
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`soundevent` data model (primarily `ClipAnnotation`) and return the results
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aggregated into a `soundevent.data.AnnotationSet`.
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"""
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import json
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import os
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from pathlib import Path
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from typing import Literal, Optional, Union
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from pydantic import Field
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from soundevent import data
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from batdetect2.configs import BaseConfig
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from batdetect2.data.annotations.legacy import (
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FileAnnotation,
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file_annotation_to_clip,
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file_annotation_to_clip_annotation,
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list_file_annotations,
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load_file_annotation,
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)
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from batdetect2.data.annotations.types import AnnotatedDataset
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PathLike = Union[Path, str, os.PathLike]
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__all__ = [
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"load_batdetect2_files_annotated_dataset",
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"load_batdetect2_merged_annotated_dataset",
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"BatDetect2FilesAnnotations",
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"BatDetect2MergedAnnotations",
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"AnnotationFilter",
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]
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class AnnotationFilter(BaseConfig):
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"""Configuration for filtering legacy FileAnnotations based on flags.
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Specifies criteria based on boolean flags (`annotated` and `issues`)
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present within the legacy `FileAnnotation` JSON structure to select which
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entries (either files or records within a merged file) should be loaded and
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converted.
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Attributes
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----------
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only_annotated : bool, default=True
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If True, only process entries where the `annotated` flag in the JSON
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is set to `True`.
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exclude_issues : bool, default=True
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If True, skip processing entries where the `issues` flag in the JSON
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is set to `True`.
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"""
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only_annotated: bool = True
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exclude_issues: bool = True
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class BatDetect2FilesAnnotations(AnnotatedDataset):
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"""Configuration for the legacy 'batdetect2' format (directory-based).
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Defines a data source where annotations are stored as individual JSON files
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(one per recording, containing a `FileAnnotation` structure) within the
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`annotations_dir`. Requires a corresponding `audio_dir`. Assumes a naming
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convention links audio files to JSON files
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(e.g., `rec.wav` -> `rec.wav.json`).
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Attributes
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----------
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format : Literal["batdetect2"]
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The fixed format identifier for this configuration type.
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annotations_dir : Path
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Path to the directory containing the individual JSON annotation files.
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filter : AnnotationFilter, optional
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Configuration for filtering which files to process based on their
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`annotated` and `issues` flags. Defaults to requiring `annotated=True`
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and `issues=False`. Set explicitly to `None` in config (e.g.,
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`filter: null`) to disable filtering.
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"""
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format: Literal["batdetect2"] = "batdetect2"
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annotations_dir: Path
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filter: AnnotationFilter = Field(
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default_factory=AnnotationFilter,
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)
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class BatDetect2MergedAnnotations(AnnotatedDataset):
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"""Configuration for the legacy 'batdetect2_file' format (merged file).
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Defines a data source where annotations for multiple recordings (each as a
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`FileAnnotation` structure) are stored within a single JSON file specified
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by `annotations_path`. Audio files are expected in `audio_dir`.
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Inherits `name`, `description`, and `audio_dir` from `AnnotatedDataset`.
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Attributes
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----------
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format : Literal["batdetect2_file"]
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The fixed format identifier for this configuration type.
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annotations_path : Path
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Path to the single JSON file containing a list of `FileAnnotation`
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objects.
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filter : AnnotationFilter, optional
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Configuration for filtering which `FileAnnotation` entries within the
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merged file to process based on their `annotated` and `issues` flags.
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Defaults to requiring `annotated=True` and `issues=False`. Set to `None`
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in config (e.g., `filter: null`) to disable filtering.
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"""
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format: Literal["batdetect2_file"] = "batdetect2_file"
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annotations_path: Path
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filter: AnnotationFilter = Field(
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default_factory=AnnotationFilter,
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)
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def load_batdetect2_files_annotated_dataset(
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dataset: BatDetect2FilesAnnotations,
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base_dir: Optional[PathLike] = None,
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) -> data.AnnotationSet:
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"""Load and convert 'batdetect2_file' annotations into an AnnotationSet.
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Scans the specified `annotations_dir` for individual JSON annotation files.
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For each file: loads the legacy `FileAnnotation`, applies filtering based
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on `dataset.filter` (`annotated`/`issues` flags), attempts to find the
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corresponding audio file, converts valid entries to `ClipAnnotation`, and
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collects them into a single `soundevent.data.AnnotationSet`.
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Parameters
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----------
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dataset : BatDetect2FilesAnnotations
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Configuration describing the 'batdetect2' (directory) data source.
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base_dir : PathLike, optional
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Optional base directory to resolve relative paths in `dataset.audio_dir`
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and `dataset.annotations_dir`. Defaults to None.
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Returns
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-------
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soundevent.data.AnnotationSet
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An AnnotationSet containing all successfully loaded, filtered, and
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converted `ClipAnnotation` objects.
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Raises
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------
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FileNotFoundError
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If the `annotations_dir` or `audio_dir` does not exist. Errors finding
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individual JSON or audio files during iteration are logged and skipped.
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"""
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audio_dir = dataset.audio_dir
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path = dataset.annotations_dir
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if base_dir:
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audio_dir = base_dir / audio_dir
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path = base_dir / path
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paths = list_file_annotations(path)
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annotations = []
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for p in paths:
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try:
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file_annotation = load_file_annotation(p)
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except FileNotFoundError:
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continue
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if dataset.filter.only_annotated and not file_annotation.annotated:
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continue
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if dataset.filter.exclude_issues and file_annotation.issues:
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continue
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try:
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clip = file_annotation_to_clip(
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file_annotation,
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audio_dir=audio_dir,
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)
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except FileNotFoundError:
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continue
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annotations.append(
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file_annotation_to_clip_annotation(
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file_annotation,
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clip,
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)
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)
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return data.AnnotationSet(
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name=dataset.name,
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description=dataset.description,
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clip_annotations=annotations,
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)
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def load_batdetect2_merged_annotated_dataset(
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dataset: BatDetect2MergedAnnotations,
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base_dir: Optional[PathLike] = None,
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) -> data.AnnotationSet:
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"""Load and convert 'batdetect2_merged' annotations into an AnnotationSet.
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Loads a single JSON file containing a list of legacy `FileAnnotation`
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objects. For each entry in the list: applies filtering based on
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`dataset.filter` (`annotated`/`issues` flags), attempts to find the
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corresponding audio file, converts valid entries to `ClipAnnotation`, and
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collects them into a single `soundevent.data.AnnotationSet`.
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Parameters
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----------
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dataset : BatDetect2MergedAnnotations
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Configuration describing the 'batdetect2_file' (merged) data source.
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base_dir : PathLike, optional
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Optional base directory to resolve relative paths in `dataset.audio_dir`
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and `dataset.annotations_path`. Defaults to None.
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Returns
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-------
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soundevent.data.AnnotationSet
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An AnnotationSet containing all successfully loaded, filtered, and
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converted `ClipAnnotation` objects from the merged file.
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Raises
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------
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FileNotFoundError
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If the `annotations_path` or `audio_dir` does not exist. Errors
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finding individual audio files referenced within the JSON are logged
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and skipped.
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json.JSONDecodeError
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If the annotations file is not valid JSON.
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TypeError
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If the root JSON structure is not a list.
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pydantic.ValidationError
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If entries within the JSON list do not conform to the legacy
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`FileAnnotation` structure.
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"""
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audio_dir = dataset.audio_dir
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path = dataset.annotations_path
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if base_dir:
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audio_dir = base_dir / audio_dir
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path = base_dir / path
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content = json.loads(Path(path).read_text())
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annotations = []
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for ann in content:
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try:
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ann = FileAnnotation.model_validate(ann)
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except ValueError:
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continue
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if dataset.filter.only_annotated and not ann.annotated:
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continue
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if dataset.filter.exclude_issues and ann.issues:
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continue
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try:
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clip = file_annotation_to_clip(ann, audio_dir=audio_dir)
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except FileNotFoundError:
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continue
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annotations.append(file_annotation_to_clip_annotation(ann, clip))
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return data.AnnotationSet(
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name=dataset.name,
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description=dataset.description,
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clip_annotations=annotations,
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)
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@ -1,80 +0,0 @@
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import os
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from pathlib import Path
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from typing import Literal, Optional, Union
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from soundevent import data
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from batdetect2.data.annotations.legacy import (
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file_annotation_to_annotation_task,
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file_annotation_to_clip,
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file_annotation_to_clip_annotation,
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list_file_annotations,
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load_file_annotation,
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)
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from batdetect2.data.annotations.types import AnnotatedDataset
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PathLike = Union[Path, str, os.PathLike]
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__all__ = [
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"load_batdetect2_files_annotated_dataset",
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"BatDetect2FilesAnnotations",
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]
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class BatDetect2FilesAnnotations(AnnotatedDataset):
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format: Literal["batdetect2"] = "batdetect2"
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annotations_dir: Path
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def load_batdetect2_files_annotated_dataset(
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dataset: BatDetect2FilesAnnotations,
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base_dir: Optional[PathLike] = None,
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) -> data.AnnotationProject:
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"""Convert annotations to annotation project."""
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audio_dir = dataset.audio_dir
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path = dataset.annotations_dir
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if base_dir:
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audio_dir = base_dir / audio_dir
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path = base_dir / path
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paths = list_file_annotations(path)
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annotations = []
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tasks = []
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for p in paths:
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try:
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file_annotation = load_file_annotation(p)
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except FileNotFoundError:
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continue
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try:
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clip = file_annotation_to_clip(
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file_annotation,
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audio_dir=audio_dir,
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)
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except FileNotFoundError:
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continue
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annotations.append(
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file_annotation_to_clip_annotation(
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file_annotation,
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clip,
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)
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)
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tasks.append(
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file_annotation_to_annotation_task(
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file_annotation,
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clip,
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)
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)
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return data.AnnotationProject(
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name=dataset.name,
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description=dataset.description,
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clip_annotations=annotations,
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tasks=tasks,
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)
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@ -1,64 +0,0 @@
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import json
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import os
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from pathlib import Path
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from typing import Literal, Optional, Union
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from soundevent import data
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from batdetect2.data.annotations.legacy import (
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FileAnnotation,
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file_annotation_to_annotation_task,
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file_annotation_to_clip,
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file_annotation_to_clip_annotation,
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)
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from batdetect2.data.annotations.types import AnnotatedDataset
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PathLike = Union[Path, str, os.PathLike]
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__all__ = [
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"BatDetect2MergedAnnotations",
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"load_batdetect2_merged_annotated_dataset",
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]
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class BatDetect2MergedAnnotations(AnnotatedDataset):
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format: Literal["batdetect2_file"] = "batdetect2_file"
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annotations_path: Path
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def load_batdetect2_merged_annotated_dataset(
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dataset: BatDetect2MergedAnnotations,
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base_dir: Optional[PathLike] = None,
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) -> data.AnnotationProject:
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audio_dir = dataset.audio_dir
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path = dataset.annotations_path
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if base_dir:
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audio_dir = base_dir / audio_dir
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path = base_dir / path
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content = json.loads(Path(path).read_text())
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annotations = []
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tasks = []
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for ann in content:
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try:
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ann = FileAnnotation.model_validate(ann)
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except ValueError:
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continue
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try:
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clip = file_annotation_to_clip(ann, audio_dir=audio_dir)
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except FileNotFoundError:
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continue
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annotations.append(file_annotation_to_clip_annotation(ann, clip))
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tasks.append(file_annotation_to_annotation_task(ann, clip))
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return data.AnnotationProject(
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name=dataset.name,
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description=dataset.description,
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clip_annotations=annotations,
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tasks=tasks,
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)
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