datamint.importers

Format-specific importers that parse an externally-labeled dataset and upload it to a Datamint project. See Client Python API for a narrative walkthrough and the 05_import_dataset.ipynb tutorial notebook.

COCO

class datamint.importers.coco.COCOBox(label, x, y, width, height)

Bases: object

Parameters:

  • label (str)

  • x (float)

  • y (float)

  • width (float)

  • height (float)

height: float
label: str
width: float
x: float
y: float
class datamint.importers.coco.COCOImportResult(project, resource_ids, n_images_uploaded, n_boxes_uploaded, errors=<factory>)

Bases: object

Parameters:

  • project (Project | str)

  • resource_ids (list[str])

  • n_images_uploaded (int)

  • n_boxes_uploaded (int)

  • errors (list[tuple[str, Exception]])

errors: list[tuple[str, Exception]]
n_boxes_uploaded: int
n_images_uploaded: int
project: Project | str
resource_ids: list[str]
class datamint.importers.coco.COCOImporter(annotations_file, images_dir=None)

Bases: object

Parse a COCO-format annotations file and upload it to a Datamint project.

Parameters:

  • annotations_file (str | Path)

  • images_dir (str | Path | None)

import_to_project(project, api=None, *, tags=None, imported_from='coco-import', on_error='raise', progress_bar=True)

Upload the parsed images and box annotations to a Datamint project.

Calls parse() first (reusing the cached result if already called). api defaults to a new Api instance if not given.

Parameters:

  • project (Project | str)

  • api (Api | None)

  • tags (Sequence[str] | None)

  • imported_from (str)

  • on_error (Literal['raise', 'skip'])

  • progress_bar (bool)

Return type:

COCOImportResult

parse(force=False)

Read and validate the COCO JSON file.

Cached after the first call; pass force=True to reparse.

Raises:

ValueError – If the file is structurally invalid (missing required keys, or an annotation references an unknown category/image id).

Parameters:

force (bool)

Return type:

COCOParseResult

class datamint.importers.coco.COCOParseResult(samples, class_names, missing_images, unsupported_annotations)

Bases: object

Parameters:

  • samples (list[COCOSample])

  • class_names (list[str])

  • missing_images (list[str])

  • unsupported_annotations (int)

class_names: list[str]
missing_images: list[str]
property num_boxes: int
property num_images: int
samples: list[COCOSample]
unsupported_annotations: int
class datamint.importers.coco.COCOSample(image_path, file_name, boxes=<factory>)

Bases: object

Parameters:

  • image_path (Path)

  • file_name (str)

  • boxes (list[COCOBox])

boxes: list[COCOBox]
file_name: str
image_path: Path

Pascal VOC

class datamint.importers.pascal_voc.PascalVOCBox(label, x1, y1, x2, y2, difficult=False)

Bases: object

Parameters:

  • label (str)

  • x1 (float)

  • y1 (float)

  • x2 (float)

  • y2 (float)

  • difficult (bool)

difficult: bool = False
label: str
x1: float
x2: float
y1: float
y2: float
class datamint.importers.pascal_voc.PascalVOCImportResult(project, resource_ids, n_images_uploaded, n_boxes_uploaded, errors=<factory>)

Bases: object

Parameters:

  • project (Project | str)

  • resource_ids (list[str])

  • n_images_uploaded (int)

  • n_boxes_uploaded (int)

  • errors (list[tuple[str, Exception]])

errors: list[tuple[str, Exception]]
n_boxes_uploaded: int
n_images_uploaded: int
project: Project | str
resource_ids: list[str]
class datamint.importers.pascal_voc.PascalVOCImporter(annotations_dir, images_dir)

Bases: object

Parse a Pascal VOC-format annotations directory and upload it to a Datamint project.

Only bounding-box annotations (the bndbox field) are imported.

Parameters:

  • annotations_dir (str | Path)

  • images_dir (str | Path)

import_to_project(project, api=None, *, tags=None, imported_from='pascal-voc-import', on_error='raise', progress_bar=True)

Upload the parsed images and box annotations to a Datamint project.

Calls parse() first (reusing the cached result if already called). api defaults to a new Api instance if not given.

Parameters:

  • project (Project | str)

  • api (Api | None)

  • tags (Sequence[str] | None)

  • imported_from (str)

  • on_error (Literal['raise', 'skip'])

  • progress_bar (bool)

Return type:

PascalVOCImportResult

parse(force=False)

Read and validate the Pascal VOC XML annotation files.

Cached after the first call; pass force=True to reparse.

Raises:

ValueError – If annotations_dir doesn’t exist, or an XML file is missing its required filename element.

Parameters:

force (bool)

Return type:

PascalVOCParseResult

class datamint.importers.pascal_voc.PascalVOCParseResult(samples, class_names, missing_images, unsupported_annotations)

Bases: object

Parameters:

  • samples (list[PascalVOCSample])

  • class_names (list[str])

  • missing_images (list[str])

  • unsupported_annotations (int)

class_names: list[str]
missing_images: list[str]
property num_boxes: int
property num_images: int
samples: list[PascalVOCSample]
unsupported_annotations: int
class datamint.importers.pascal_voc.PascalVOCSample(image_path, file_name, boxes=<factory>)

Bases: object

Parameters:

  • image_path (Path)

  • file_name (str)

  • boxes (list[PascalVOCBox])

boxes: list[PascalVOCBox]
file_name: str
image_path: Path

YOLO

class datamint.importers.yolo.YOLOBox(label, x1, y1, x2, y2)

Bases: object

Parameters:

  • label (str)

  • x1 (float)

  • y1 (float)

  • x2 (float)

  • y2 (float)

label: str
x1: float
x2: float
y1: float
y2: float
class datamint.importers.yolo.YOLOImportResult(project, resource_ids, n_images_uploaded, n_boxes_uploaded, errors=<factory>)

Bases: object

Parameters:

  • project (Project | str)

  • resource_ids (list[str])

  • n_images_uploaded (int)

  • n_boxes_uploaded (int)

  • errors (list[tuple[str, Exception]])

errors: list[tuple[str, Exception]]
n_boxes_uploaded: int
n_images_uploaded: int
project: Project | str
resource_ids: list[str]
class datamint.importers.yolo.YOLOImporter(images_dir, labels_dir, *, class_names=None, data_yaml=None, image_extensions=('.jpg', '.jpeg', '.png', '.bmp', '.tif', '.tiff', '.webp'))

Bases: object

Parse a YOLO-format (images + normalized-bbox label .txt files) dataset and upload it to a Datamint project.

Parameters:

  • images_dir (str | Path)

  • labels_dir (str | Path)

  • class_names (Sequence[str] | None)

  • data_yaml (str | Path | None)

  • image_extensions (Sequence[str])

import_to_project(project, api=None, *, tags=None, imported_from='yolo-import', on_error='raise', progress_bar=True)

Upload the parsed images and box annotations to a Datamint project.

Calls parse() first (reusing the cached result if already called). api defaults to a new Api instance if not given.

Parameters:

  • project (Project | str)

  • api (Api | None)

  • tags (Sequence[str] | None)

  • imported_from (str)

  • on_error (Literal['raise', 'skip'])

  • progress_bar (bool)

Return type:

YOLOImportResult

parse(force=False)

Read and validate the YOLO label files.

Cached after the first call; pass force=True to reparse.

Raises:

ValueError – If class names can’t be resolved, a label line references an unknown class index, or a normalized coordinate is outside the expected [0, 1] range.

Parameters:

force (bool)

Return type:

YOLOParseResult

class datamint.importers.yolo.YOLOParseResult(samples, class_names, missing_images, unsupported_annotations)

Bases: object

Parameters:

  • samples (list[YOLOSample])

  • class_names (list[str])

  • missing_images (list[str])

  • unsupported_annotations (int)

class_names: list[str]
missing_images: list[str]
property num_boxes: int
property num_images: int
samples: list[YOLOSample]
unsupported_annotations: int
class datamint.importers.yolo.YOLOSample(image_path, file_name, boxes=<factory>)

Bases: object

Parameters:

  • image_path (Path)

  • file_name (str)

  • boxes (list[YOLOBox])

boxes: list[YOLOBox]
file_name: str
image_path: Path