Image Classification
Keras
English
emotion-detection
facial-expression
fer2012
Eval Results (legacy)
Instructions to use Goutham204/Emotion_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Goutham204/Emotion_detection with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Goutham204/Emotion_detection") - Notebooks
- Google Colab
- Kaggle
Facial Expression Recognition using CNN (FER-2012 Dataset)
This repository contains a Convolutional Neural Network (CNN) model trained using the FER-2012 dataset to classify facial expressions into seven emotion categories.
Model Details
- Framework: TensorFlow / Keras
- Input: 48x48 grayscale facial image
- Output: Emotion class (0β6)
- Model Format:
.keras(Keras native format)
Emotion Classes
0 β Angry
1 β Disgust
2 β Fear
3 β Happy
4 β Sad
5 β Surprise
6 β Neutral
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Evaluation results
- Accuracy on FER-2012self-reported0.840