empty_annotations

Dataset.empty_annotations() → Self

Create a dataset object with an empty annotation dataframe, but with the same columns, and the same images dataframe.

Useful when trying to construct a prediction dataset from another dataset

Returns:

New dataset instance with the same images as the original dataset, but an empty annotation dataframe

See also

• filter_annotations()

• loc_annot

• iloc_annot

Example

>>> from lours.utils.doc_utils import dummy_dataset
>>> example = dummy_dataset(2, 2, seed=1)
>>> example
Dataset object containing 2 images and 2 objects
Name :
    shake_effort_many
Images root :
    care/suggest
Images :
    width  height        relative_path  type  split
id
0     955     229  determine/story.jpg  .jpg  train
1     131     840       air/method.bmp  .bmp  train
Annotations :
    image_id category_str  category_id  ...   box_y_min   box_width  box_height
id                                      ...
0          1       listen           14  ...  276.974642    9.718823  184.684056
1          0        reach           22  ...    6.311037  123.141689  174.239136

[2 rows x 8 columns]
Label map :
{14: 'listen', 15: 'marriage', 22: 'reach'}
>>> example.empty_annotations()
Dataset object containing 2 images and 0 object
Name :
    shake_effort_many
Images root :
    care/suggest
Images :
    width  height        relative_path  type  split
id
0     955     229  determine/story.jpg  .jpg  train
1     131     840       air/method.bmp  .bmp  train
Annotations :
Empty DataFrame
Columns: [image_id, category_str, category_id, split, box_x_min, box_y_min, box_width, box_height]
Index: []
Label map :
{14: 'listen', 15: 'marriage', 22: 'reach'}