iter_images

Dataset.iter_images() → Iterator[tuple[Series, DataFrame]]

Iterate through images, by yielding

Yields:

tuple containing – - image Series with image data, and named as the image id - annotations DataFrame

See also

• related tutorial

• get_one_frame()

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'}
>>> for i, (frame, annot) in enumerate(example.iter_images()):
...     print(f"Frame {i}")
...     print(frame)
...     print(annot)
...
Frame 0
width                            955
height                           229
relative_path    determine/story.jpg
type                            .jpg
split                          train
Name: 0, dtype: object
    image_id category_str  category_id  ... box_y_min   box_width  box_height
id                                      ...
1          0        reach           22  ...  6.311037  123.141689  174.239136

[1 rows x 8 columns]
Frame 1
width                       131
height                      840
relative_path    air/method.bmp
type                       .bmp
split                     train
Name: 1, dtype: object
    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 rows x 8 columns]