新工具：Fiftyone
可以采用colab运行程序，点击即可：
完整代码：
!pip install opencv-python-headless==4.5.4.60
!pip install fiftyone
!pip install tensorflow torch torchvision umap-learn
!pip install ipywidgets>=7.5
import fiftyone as fo
import fiftyone.zoo as foz
连接谷歌云盘
from google.colab import drive
drive.mount('/content/drive')
其中一个示例
dataset = foz.load_zoo_dataset(
"open-images-v6",
split="validation",
label_types=["segmentations", "detections"],
# classes = ,
# max_samples=100,
seed=51,
shuffle=True,
dataset_dir="/content/drive/MyDrive/Colab Notebooks/openiamges/", # 指定下载的数据集保存的路径,尽量不要随意更改，这是保存原始图片的路径，
dataset_name="open-images",
# numexpr_max_threads=20,
)
更多示例参考官方示例。
参数详解：
- label_types – a list of label types to load. The supported values are (“detections”, “classifications”, “segmentations”, “relationships”). By default, all available labels types will be loaded. Specifying [] will load only the images
- classes – a list of classes of interest. If specified, only samples with at least one object, segmentation, or image-level label in the specified classes will be downloaded
- attrs – a list of attributes of interest. If specified, only download samples if they contain at least one attribute in attrs or one class in classes (only applicable when label_types contains “relationships”)
- load_hierarchy – whether to load the class hierarchy into dataset.info[“hierarchy”]
- image_ids – an array of specific image IDs to download
- image_ids_file – a path to a .txt, .csv, or .json file containing image IDs to download
In addition, like all other zoo datasets, you can specify:
- max_samples – the maximum number of samples to load
- shuffle – whether to randomly chose which samples to load if max_samples is given
- seed – a random seed to use when shuffling
Original: https://blog.csdn.net/qq_45033722/article/details/124161999
Author: 大笨钟47
Title: OpenImages V6下载
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