Note

This is a Hugging Face dataset. Learn how to load datasets from the Hub in the Hugging Face integration docs.

Hugging Face

Dataset Card for VisDrone2019-DET#

image/png

This is a FiftyOne version of the VisDrone2019-DET dataset with 8629 samples.

Installation#

If you haven’t already, install FiftyOne:

pip install -U fiftyone

Usage#

import fiftyone as fo
import fiftyone.utils.huggingface as fouh

# Load the dataset
# Note: other available arguments include 'max_samples', 'persistent`, 'overwrite' etc
dataset = fouh.load_from_hub("Voxel51/VisDrone2019-DET")

# Launch the App
session = fo.launch_app(dataset)

Dataset Details#

Dataset Description#

  • Curated by: AISKYEYE team at the Lab of Machine Learning and Data Mining, Tianjin University, China

  • Language(s) (NLP): en

  • License: cc-by-sa-3.0

Dataset Sources#

Dataset Structure#

Name:        VisDrone2019-DET
Media type:  image
Num samples: 8629
Persistent:  False
Tags:        []
Sample fields:
    id:           fiftyone.core.fields.ObjectIdField
    filepath:     fiftyone.core.fields.StringField
    tags:         fiftyone.core.fields.ListField(fiftyone.core.fields.StringField)
    metadata:     fiftyone.core.fields.EmbeddedDocumentField(fiftyone.core.metadata.ImageMetadata)
    ground_truth: fiftyone.core.fields.EmbeddedDocumentField(fiftyone.core.labels.Detections)

The dataset has 3 splits: “train”, “val”, and “test”. Samples are tagged with their split.

Dataset Creation#

Created by the AISKYEYE team at the Lab of Machine Learning and Data Mining, Tianjin University, China.

Source Data#

Who are the source data producers?#

The VisDrone Dataset is a large-scale benchmark created by the AISKYEYE team at the Lab of Machine Learning and Data Mining, Tianjin University, China. It contains carefully annotated ground truth data for various computer vision tasks related to drone-based image and video analysis.

Personal and Sensitive Information#

The authors of the dataset have done their best to exclude identifiable information from the data to protect privacy. If you find your vehicle or personal information in this dataset, please contact them and they will remove the corresponding information from their dataset. They are not responsible for any actual or potential harm as the result of using this dataset.

Citation#

BibTeX:

@ARTICLE{9573394,
  author={Zhu, Pengfei and Wen, Longyin and Du, Dawei and Bian, Xiao and Fan, Heng and Hu, Qinghua and Ling, Haibin},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  title={Detection and Tracking Meet Drones Challenge},
  year={2021},
  volume={},
  number={},
  pages={1-1},
  doi={10.1109/TPAMI.2021.3119563}}