Datasets:
Tasks:
Image Feature Extraction
Modalities:
Image
Formats:
imagefolder
Languages:
English
Size:
1K - 10K
License:
annotations_creators: [] | |
language: en | |
license: cc-by-4.0 | |
size_categories: | |
- 1K<n<10K | |
task_categories: | |
- image-feature-extraction | |
task_ids: [] | |
pretty_name: Emojis | |
tags: | |
- fiftyone | |
- image | |
dataset_summary: > | |
![image/png](dataset_preview.gif) | |
This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 1816 | |
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 'max_samples', etc | |
dataset = fouh.load_from_hub("jamarks/emojis") | |
# Launch the App | |
session = fo.launch_app(dataset) | |
``` | |
# Dataset Card for Emojis | |
<!-- Provide a quick summary of the dataset. --> | |
![image/png](dataset_preview.gif) | |
This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 1816 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 'max_samples', etc | |
dataset = fouh.load_from_hub("jamarks/emojis") | |
# Launch the App | |
session = fo.launch_app(dataset) | |
``` | |
## Dataset Details | |
### Dataset Description | |
<!-- Provide a longer summary of what this dataset is. --> | |
- **Curated by:** Jacob Marks | |
- **Language(s) (NLP):** en | |
- **License:** cc-by-4.0 | |
### Dataset Sources | |
<!-- Provide the basic links for the dataset. --> | |
- **Demo:** https://try.fiftyone.ai/datasets/emojis/samples | |
## Dataset Creation | |
### Curation Rationale | |
Emojis sit at the intersection between textual and visual, providing a fascinating test-bed for exploring multimodal search and reranking techniques. This dataset was constructed to facilitate these experiments. For connected projects, check out: | |
- [Emoji Search CLI Library](https://github.com/jacobmarks/emoji_search) | |
- [Semantic Emoji Search Plugin for FiftyOne](https://github.com/jacobmarks/emoji-search-plugin) | |
### Source Data | |
Samples in this dataset were constructed from rows in the Kaggle [Full Emoji Image Dataset](https://www.kaggle.com/datasets/subinium/emojiimage-dataset) | |
#### Data Collection and Processing | |
The base64-encoded images in the original csv were upscaled by 10x using [Real-ESRGAN](https://replicate.com/nightmareai/real-esrgan). | |
OpenAI's CLIP-VIT-B/32 model was used to embed these images (vision encoder), the emoji names (text encoder), and the unicode sequences (text encoder). These embeddings were used to construct [Brain Runs](https://docs.voxel51.com/user_guide/brain.html) for performing similarity and semantic searches, as well as visualizing the structure of the dataset using UMAP dimensionality reduction. | |
## Dataset Card Authors | |
[Jacob Marks](https://huggingface.co/jamarks) |