metadata
license: apache-2.0
language:
- en
LVIS
Dataset Summary
This dataset is the implementation of LVIS dataset into Hugging Face datasets. Please visit the original website for more information.
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This code returns train, validation and test generators.
from datasets import load_dataset
dataset = load_dataset("winvoker/lvis")
Objects is a dictionary which contains annotation information like bbox, class.
DatasetDict({
train: Dataset({
features: ['id', 'image', 'height', 'width', 'objects'],
num_rows: 100170
})
validation: Dataset({
features: ['id', 'image', 'height', 'width', 'objects'],
num_rows: 4809
})
test: Dataset({
features: ['id', 'image', 'height', 'width', 'objects'],
num_rows: 19822
})
})
Access Generators
train = dataset["train"]
validation = dataset["validation"]
test = dataset["test"]
An example row is as follows.
{ 'id': 0,
'image': '000000437561.jpg',
'height': 480,
'width': 640,
'objects': {
'bboxes': [[[392, 271, 14, 3]],
'classes': [117],
'segmentation': [[376, 272, 375, 270, 372, 269, 371, 269, 373, 269, 373]]
}
}