|
--- |
|
annotations_creators: [] |
|
language: en |
|
license: bsd |
|
task_categories: |
|
- image-classification |
|
- object-detection |
|
task_ids: [] |
|
pretty_name: bdd100k-validation |
|
tags: |
|
- fiftyone |
|
- image |
|
- image-classification |
|
- object-detection |
|
dataset_summary: ' |
|
|
|
|
|
|
|
 |
|
|
|
|
|
|
|
This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 10000 samples. |
|
|
|
|
|
## Installation |
|
|
|
|
|
If you haven''t already, install FiftyOne: |
|
|
|
|
|
```bash |
|
|
|
pip install -U fiftyone |
|
|
|
``` |
|
|
|
|
|
## Usage |
|
|
|
|
|
```python |
|
|
|
import fiftyone as fo |
|
|
|
import fiftyone.utils.huggingface as fouh |
|
|
|
|
|
# Load the dataset |
|
|
|
# Note: other available arguments include ''split'', ''max_samples'', etc |
|
|
|
dataset = fouh.load_from_hub("dgural/bdd100k") |
|
|
|
|
|
# Launch the App |
|
|
|
session = fo.launch_app(dataset) |
|
|
|
``` |
|
|
|
' |
|
--- |
|
|
|
# Dataset Card for bdd100k-validation |
|
|
|
|
|
From one of the largest open source driving datasets, [BDD100k](https://www.vis.xyz/bdd100k/), is the BDD100K images dataset. |
|
The dataset consists of every 10th second in the videos and contains a train, validation and test split. |
|
It contains labels for object detection, weather, time of day, and scene of the driving! |
|
|
|
|
|
 |
|
|
|
|
|
This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 10000 samples. |
|
|
|
## Installation |
|
|
|
If you haven't already, install FiftyOne: |
|
|
|
```bash |
|
pip install -U fiftyone |
|
``` |
|
|
|
## Usage |
|
|
|
```python |
|
import fiftyone as fo |
|
import fiftyone.utils.huggingface as fouh |
|
|
|
# Load the dataset |
|
# Note: other available arguments include 'split', 'max_samples', etc |
|
dataset = fouh.load_from_hub("dgural/bdd100k") |
|
|
|
# Launch the App |
|
session = fo.launch_app(dataset) |
|
``` |
|
|
|
|
|
## Dataset Details |
|
|
|
### Dataset Description |
|
|
|
|
|
- **Curated by:** [ETH VIS Group](https://www.vis.xyz/) |
|
- **Language(s) (NLP):** en |
|
- **License:** bsd |
|
|
|
### Dataset Sources [optional] |
|
|
|
|
|
- **Repository:** [bdd100k](https://github.com/bdd100k/bdd100k) |
|
- **Paper :** [BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning](https://arxiv.org/abs/1805.04687) |
|
|
|
## Uses |
|
|
|
By downoading, you are agreeing to the [BDD100K License](https://doc.bdd100k.com/license.html#license). |
|
Copyright ©2018. The Regents of the University of California (Regents). All Rights Reserved. |
|
|
|
THIS SOFTWARE AND/OR DATA WAS DEPOSITED IN THE BAIR OPEN RESEARCH COMMONS REPOSITORY ON 1/1/2021 |
|
|
|
Permission to use, copy, modify, and distribute this software and its documentation for educational, research, and not-for-profit purposes, without fee and without a signed licensing agreement; and permission to use, copy, modify and distribute this software for commercial purposes (such rights not subject to transfer) to BDD and BAIR Commons members and their affiliates, is hereby granted, provided that the above copyright notice, this paragraph and the following two paragraphs appear in all copies, modifications, and distributions. Contact The Office of Technology Licensing, UC Berkeley, 2150 Shattuck Avenue, Suite 510, Berkeley, CA 94720-1620, (510) 643-7201, otl@berkeley.edu, http://ipira.berkeley.edu/industry-info for commercial licensing opportunities. |
|
|
|
IN NO EVENT SHALL REGENTS BE LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF REGENTS HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
|
|
|
REGENTS SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE AND ACCOMPANYING DOCUMENTATION, IF ANY, PROVIDED HEREUNDER IS PROVIDED “AS IS”. REGENTS HAS NO OBLIGATION TO PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. |
|
|
|
### Direct Use |
|
|
|
This dataset is great for self driving car applications, especially for dealing with many different weather conditions and different times of day! |
|
|
|
|
|
## Dataset Structure |
|
``` |
|
Name: bdd100k-validation |
|
Media type: image |
|
Num samples: 10000 |
|
Persistent: True |
|
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) |
|
weather: fiftyone.core.fields.EmbeddedDocumentField(fiftyone.core.labels.Classification) |
|
timeofday: fiftyone.core.fields.EmbeddedDocumentField(fiftyone.core.labels.Classification) |
|
scene: fiftyone.core.fields.EmbeddedDocumentField(fiftyone.core.labels.Classification) |
|
detections: fiftyone.core.fields.EmbeddedDocumentField(fiftyone.core.labels.Detections) |
|
``` |
|
|
|
|
|
|
|
|
|
### Source Data |
|
|
|
The dataset is sourced from [BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning](https://arxiv.org/abs/1805.04687) |
|
|
|
|
|
#### Who are the source data producers? |
|
|
|
BDD100K is now managed by the [ETH VIS Group](https://www.vis.xyz/bdd100k/) |
|
|
|
|
|
## Citation |
|
|
|
**BibTeX:** |
|
|
|
@misc{yu2020bdd100k, |
|
title={BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning}, |
|
author={Fisher Yu and Haofeng Chen and Xin Wang and Wenqi Xian and Yingying Chen and Fangchen Liu and Vashisht Madhavan and Trevor Darrell}, |
|
year={2020}, |
|
eprint={1805.04687}, |
|
archivePrefix={arXiv}, |
|
primaryClass={cs.CV} |
|
} |
|
|
