|
--- |
|
annotations_creators: |
|
- self |
|
language_creators: |
|
- found |
|
language: |
|
- en |
|
license: |
|
- unknown |
|
multilinguality: |
|
- monolingual |
|
size_categories: |
|
- n<1K |
|
source_datasets: |
|
- original |
|
task_categories: |
|
- object-detection |
|
task_ids: [] |
|
paperswithcode_id: food |
|
pretty_name: food |
|
tags: |
|
- food |
|
dataset_info: |
|
features: |
|
- name: image_id |
|
dtype: int64 |
|
- name: image |
|
dtype: Image |
|
- name: width |
|
dtype: int32 |
|
- name: height |
|
dtype: int32 |
|
- name: objects |
|
sequence: |
|
- name: id |
|
dtype: int64 |
|
- name: area |
|
dtype: int64 |
|
- name: bbox |
|
sequence: float32 |
|
length: 4 |
|
- name: category |
|
dtype: |
|
class_label: |
|
names: |
|
'1': Broccoli |
|
'2': Tomato |
|
'3': Potato |
|
--- |
|
|
|
# Dataset Card for Food |
|
|
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## Table of Contents |
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- [Table of Contents](#table-of-contents) |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Languages](#languages) |
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- [Dataset Structure](#dataset-structure) |
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- [Data Instances](#data-instances) |
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- [Data Fields](#data-fields) |
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- [Data Splits](#data-splits) |
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- [Dataset Creation](#dataset-creation) |
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- [Curation Rationale](#curation-rationale) |
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- [Source Data](#source-data) |
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- [Annotations](#annotations) |
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- [Personal and Sensitive Information](#personal-and-sensitive-information) |
|
|
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## Dataset Description |
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|
|
|
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|
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### Dataset Summary |
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|
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Sample dataset with vegetable annotations |
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|
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### Supported Tasks and Leaderboards |
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|
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- `object-detection`: The dataset can be used to train a model for Object Detection. |
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|
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### Languages |
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|
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English |
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|
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## Dataset Structure |
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[More Information Needed] |
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|
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### Data Instances |
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|
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A data point comprises an image and its object annotations. |
|
|
|
``` |
|
{ |
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'image_id': 75, |
|
'image': Test_233.jpg, |
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'width': 620, |
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'height': 350, |
|
'objects': { |
|
'id': [212,213,214,215,216,217], |
|
'area': [9138.402799999996,7127.4616,8837.071,7997.723299999998,7590.117599999998,8844.078], |
|
'bbox': [ |
|
[245.82,165.21,95.63,95.56], |
|
[363.72,100.47,84.08,84.77], |
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[ 154.88,99.7,91.01,97.1], |
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[308.24,8.77,89.47,89.39] |
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], |
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'category': [2, 2, 2, 2] |
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} |
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} |
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``` |
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|
|
### Data Fields |
|
|
|
- `image`: the image id |
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- `image`: `image name` |
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- `width`: the image width |
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- `height`: the image height |
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- `objects`: a dictionary containing bounding box metadata for the objects present on the image |
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- `id`: the annotation id |
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- `area`: the area of the bounding box |
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- `bbox`: the object's bounding box (in the [coco](https://albumentations.ai/docs/getting_started/bounding_boxes_augmentation/#coco) format) |
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- `category`: the object's category:`Broccoli` (1),`Tomato` (2),`Potato` (3) |
|
|
|
### Data Splits |
|
|
|
The data is not split |
|
|
|
## Dataset Creation |
|
|
|
### Curation Rationale |
|
|
|
[More Information Needed] |
|
|
|
### Source Data |
|
|
|
#### Initial Data Collection and Normalization |
|
|
|
[More Information Needed] |
|
|
|
#### Who are the source language producers? |
|
|
|
The images for this dataset were collected from Flickr and Google Images. |
|
|
|
### Annotations |
|
|
|
#### Annotation process |
|
|
|
The dataset was labelled : Broccoli, Tomato, Potato |
|
|
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#### Who are the annotators? |
|
|
|
Hadassah did the annotations using CVAT tool. |
|
|
|
### 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] |
|
|
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## Additional Information |
|
|
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### Dataset Curators |
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[More Information Needed] |
|
|
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### Licensing Information |
|
|
|
[More Information Needed] |
|
|
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### Citation Information |
|
|
|
### Contributions |
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|
