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---
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
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** en
- **License:** bsd
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
By downoading, you are agreeing to the [BDD100K License](https://doc.bdd100k.com/license.html#license).
### Direct Use
This dataset is great for self driving car applications, especially for dealing with many different weather conditions and different times of day!
[More Information Needed]
[More Information Needed]
## 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}
}
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