Datasets:
Tasks:
Image Classification
Languages:
English
Size Categories:
1K<n<10K
Source Datasets:
original
License:
| annotations_creators: | |
| - expert-generated | |
| - machine-generated | |
| language: | |
| - en | |
| language_creators: [] | |
| license: | |
| - mit | |
| multilinguality: [] | |
| paperswithcode_id: acronym-identification | |
| pretty_name: Nailbiting Classification | |
| size_categories: | |
| - 1K<n<10K | |
| source_datasets: | |
| - original | |
| tags: | |
| - nailbiting | |
| - image | |
| - preprocesses | |
| task_categories: | |
| - image-classification | |
| task_ids: [] | |
| train-eval-index: | |
| - col_mapping: | |
| labels: tags | |
| tokens: tokens | |
| config: default | |
| splits: | |
| eval_split: test | |
| task: token-classification | |
| task_id: entity_extraction | |
| dataset_info: | |
| features: | |
| - name: image | |
| dtype: image | |
| - name: label | |
| dtype: | |
| class_label: | |
| names: | |
| '0': biting | |
| '1': no_biting | |
| splits: | |
| - name: train | |
| num_bytes: 11965731.715 | |
| num_examples: 6629 | |
| - name: test | |
| num_bytes: 1485426.0 | |
| num_examples: 736 | |
| download_size: 11546517 | |
| dataset_size: 13451157.715 | |
| # Dataset Card for Nail Biting Classification | |
| ## 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://huggingface.co/datasets/alecsharpie/nailbiting_classification](https://huggingface.co/datasets/alecsharpie/nailbiting_classification) | |
| - **Repository:** [https://github.com/alecsharpie/nomo_nailbiting](https://github.com/alecsharpie/nomo_nailbiting) | |
| - **Point of Contact:** [alecsharpie@gmail.com](alecsharpie@gmail.com) | |
| ### Dataset Summary | |
| A binary image dataset for classifying nailbiting. Images are cropped to only show the mouth area. | |
| Should contain edge cases such as drinking water, talking on the phone, scratching chin etc.. all in "no biting" category | |
| ## Dataset Structure | |
| ### Data Instances | |
| - 7147 Images | |
| - 14879790 bytes total | |
| - 12332617 bytes download | |
| ### Data Fields | |
| 128 x 64 (w x h, pixels) | |
| Black and white | |
| Labels | |
| - '0': biting | |
| - '1': no_biting | |
| ### Data Splits | |
| - train: 6629 (11965737 bytes) | |
| - test: 1471 (2914053 bytes) | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| I wanted to create a notification system to help me stop biting my nails. It needed to contain lots of possible no-biting scenarios. eg talking on the phone | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| The data was scraped from stock images sites and photos of myself were taken with my webcam. | |
| MTCNN (https://github.com/ipazc/mtcnn) was then used to crop the images down to only the show the mouth area | |
| The images were then converted to a black & white colour scheme. | |
| ### Annotations | |
| #### Annotation process | |
| During the scraping process images were labelled with a description, which I then manually sanity checked. I labelled the ones of me manually. | |
| #### Who are the annotators? | |
| Alec Sharp | |
| ## Considerations for Using the Data | |
| ### Discussion of Biases & Limitations | |
| Tried to make the dataset diverse in terms of age and skin tone. Although, this dataset contains a large number of images of one subject (me) so is biased towards lower quality webcam pictures of a white male with a short beard. | |
| ### Dataset Curators | |
| Alec Sharp | |
| ### Licensing Information | |
| MIT | |
| ### Contributions | |
| Thanks to [@alecsharpie](https://github.com/alecsharpie) for adding this dataset. |