数据集:
winvoker/lvis
This dataset is the implementation of LVIS dataset into Hugging Face datasets. Please visit the original website for more information.
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 }) })
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]] } }