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mediapipe_model_maker.object_detector.Dataset

Dataset library for object detector.

mediapipe_model_maker.object_detector.Dataset(
    dataset: tf.data.Dataset,
    label_names: List[str],
    size: Optional[int] = None
)

Args
`tf_dataset`	A tf.data.Dataset object that contains a potentially large set of elements, where each element is a pair of (input_data, target). The `input_data` means the raw input data, like an image, a text etc., while the `target` means the ground truth of the raw input data, e.g. the classification label of the image etc.
`size`	The size of the dataset. tf.data.Dataset donesn't support a function to get the length directly since it's lazy-loaded and may be infinite.

Attributes
`label_names`
`num_classes`
`size`	Returns the size of the dataset. Same functionality as calling len. See the len method definition for more information.

Attributes

label_names

num_classes

size

Returns the size of the dataset.

Same functionality as calling len. See the len method definition for more information.

@classmethod
from_cache(
    tfrecord_cache_files: cache_files.TFRecordCacheFiles
) -> 'Dataset'

Loads the TFRecord data from cache.

Args
`tfrecord_cache_files`	The TFRecordCacheFiles object containing the already cached TFRecord and metadata files.

Returns
ObjectDetectorDataset object.

Raises
ValueError if tfrecord_cache_files are not already cached.

@classmethod
from_coco_folder(
    data_dir