File size: 5,599 Bytes
600666e ca86707 600666e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 |
---
annotations_creators:
- machine-generated
language_creators:
- found
language: []
license:
- other
multilinguality:
- monolingual
pretty_name: BSD100
size_categories:
- unknown
source_datasets:
- original
task_categories:
- other
task_ids:
- other-other-image-super-resolution
---
# Dataset Card for BSD100
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage**: https://www2.eecs.berkeley.edu/Research/Projects/CS/vision/bsds/
- **Repository**: https://huggingface.co/datasets/eugenesiow/BSD100
- **Paper**: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=937655
- **Leaderboard**: https://github.com/eugenesiow/super-image#scale-x2
### Dataset Summary
BSD is a dataset used frequently for image denoising and super-resolution. Of the subdatasets, BSD100 is aclassical image dataset having 100 test images proposed by [Martin et al. (2001)](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=937655). The dataset is composed of a large variety of images ranging from natural images to object-specific such as plants, people, food etc. BSD100 is the testing set of the Berkeley segmentation dataset BSD300.
Install with `pip`:
```bash
pip install datasets super-image
```
Evaluate a model with the [`super-image`](https://github.com/eugenesiow/super-image) library:
```python
from datasets import load_dataset
from super_image import EdsrModel
from super_image.data import EvalDataset, EvalMetrics
dataset = load_dataset('eugenesiow/BSD100', 'bicubic_x2', split='validation')
eval_dataset = EvalDataset(dataset)
model = EdsrModel.from_pretrained('eugenesiow/edsr-base', scale=2)
EvalMetrics().evaluate(model, eval_dataset)
```
### Supported Tasks and Leaderboards
The dataset is commonly used for evaluation of the `image-super-resolution` task.
Unofficial [`super-image`](https://github.com/eugenesiow/super-image) leaderboard for:
- [Scale 2](https://github.com/eugenesiow/super-image#scale-x2)
- [Scale 3](https://github.com/eugenesiow/super-image#scale-x3)
- [Scale 4](https://github.com/eugenesiow/super-image#scale-x4)
- [Scale 8](https://github.com/eugenesiow/super-image#scale-x8)
### Languages
Not applicable.
## Dataset Structure
### Data Instances
An example of `validation` for `bicubic_x2` looks as follows.
```
{
"hr": "/.cache/huggingface/datasets/downloads/extracted/BSD100_HR/3096.png",
"lr": "/.cache/huggingface/datasets/downloads/extracted/BSD100_LR_x2/3096.png"
}
```
### Data Fields
The data fields are the same among all splits.
- `hr`: a `string` to the path of the High Resolution (HR) `.png` image.
- `lr`: a `string` to the path of the Low Resolution (LR) `.png` image.
### Data Splits
| name |validation|
|-------|---:|
|bicubic_x2|100|
|bicubic_x3|100|
|bicubic_x4|100|
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
No annotations.
#### Who are the annotators?
No annotators.
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
- **Original Authors**: [Martin et al. (2001)](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=937655)
### Licensing Information
You are free to download a portion of the dataset for non-commercial research and educational purposes.
In exchange, we request only that you make available to us the results of running your segmentation or
boundary detection algorithm on the test set as described below. Work based on the dataset should cite
the [Martin et al. (2001)](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=937655) paper.
### Citation Information
```bibtex
@inproceedings{martin2001database,
title={A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics},
author={Martin, David and Fowlkes, Charless and Tal, Doron and Malik, Jitendra},
booktitle={Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001},
volume={2},
pages={416--423},
year={2001},
organization={IEEE}
}
```
### Contributions
Thanks to [@eugenesiow](https://github.com/eugenesiow) for adding this dataset.
|