Dataset library for object detector.
Inherits From: ClassificationDataset
, Dataset
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.
|
Methods
from_cache
View source
@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.
|
from_coco_folder
View source
@classmethod
from_coco_folder(
data_dir