Commit
·
9e17b03
1
Parent(s):
e21c681
Update README.md
Browse files
README.md
CHANGED
|
@@ -1,3 +1,63 @@
|
|
| 1 |
---
|
| 2 |
license: cc-by-nc-nd-4.0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 3 |
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
---
|
| 2 |
license: cc-by-nc-nd-4.0
|
| 3 |
+
task_categories:
|
| 4 |
+
- image-classification
|
| 5 |
+
- image-to-image
|
| 6 |
+
language:
|
| 7 |
+
- en
|
| 8 |
+
tags:
|
| 9 |
+
- code
|
| 10 |
---
|
| 11 |
+
# Facial Emotion Recognition Dataset
|
| 12 |
+
|
| 13 |
+
The dataset consists of images capturing people displaying **7 distinct emotions** (*anger, contempt, disgust, fear, happiness, sadness and surprise*). Each image in the dataset represents one of these specific emotions, enabling researchers and machine learning practitioners to study and develop models for emotion recognition and analysis.
|
| 14 |
+
|
| 15 |
+
The images encompass a diverse range of individuals, including different *genders, ethnicities, and age groups*. The dataset aims to provide a comprehensive representation of human emotions, allowing for a wide range of use cases.
|
| 16 |
+
|
| 17 |
+
### The dataset's possible applications:
|
| 18 |
+
- automatic emotion detection
|
| 19 |
+
- mental health analysis
|
| 20 |
+
- artificial intelligence (AI) and computer vision
|
| 21 |
+
- entertainment industries
|
| 22 |
+
- advertising and market research
|
| 23 |
+
- security and surveillance
|
| 24 |
+
|
| 25 |
+
|
| 26 |
+
|
| 27 |
+
# Get the Dataset
|
| 28 |
+
|
| 29 |
+
### This is just an example of the data
|
| 30 |
+
|
| 31 |
+
If you need access to the entire dataset, contact us via **[[email protected]](mailto:[email protected])** or leave a request on **[https://trainingdata.pro/data-market](https://trainingdata.pro/data-market?utm_source=huggingface)**
|
| 32 |
+
|
| 33 |
+
# Content
|
| 34 |
+
|
| 35 |
+
- **images**: includes folders corresponding to people and containing images with 8 different impersonated emotions, each file is named according to the expressed emotion
|
| 36 |
+
- **.csv** file: contains information about people in the dataset
|
| 37 |
+
|
| 38 |
+
### Emotions in the dataset:
|
| 39 |
+
- anger
|
| 40 |
+
- contempt
|
| 41 |
+
- disgust
|
| 42 |
+
- fear
|
| 43 |
+
- happy
|
| 44 |
+
- sad
|
| 45 |
+
- surprised
|
| 46 |
+
|
| 47 |
+
|
| 48 |
+
### File with the extension .csv
|
| 49 |
+
|
| 50 |
+
includes the following information for each set of media files:
|
| 51 |
+
|
| 52 |
+
- **set_id**: id of the set of images,
|
| 53 |
+
- **gender**: gender of the person,
|
| 54 |
+
- **age**: age of the person,
|
| 55 |
+
- **country**: country of the person
|
| 56 |
+
|
| 57 |
+
# Images for facial emotion recognition might be collected in accordance with your requirements.
|
| 58 |
+
|
| 59 |
+
## **[TrainingData](https://trainingdata.pro/data-market?utm_source=huggingface)** provides high-quality data annotation tailored to your needs
|
| 60 |
+
|
| 61 |
+
More datasets in TrainingData's Kaggle account: **https://www.kaggle.com/trainingdatapro/datasets**
|
| 62 |
+
|
| 63 |
+
TrainingData's GitHub: **https://github.com/trainingdata-pro**
|