|
--- |
|
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). |
|
|
|
### 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} |
|
} |
|
|
