Image Classification
Keras
English
cnn
facial-expression
emoji
emotion-detection
Eval Results (legacy)
Instructions to use Goutham204/Emoji_generator_from_facial_expression with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Goutham204/Emoji_generator_from_facial_expression with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://Goutham204/Emoji_generator_from_facial_expression") - Notebooks
- Google Colab
- Kaggle
Emoji Generator from Facial Expressions using CNN
This project uses a Convolutional Neural Network (CNN) to recognize human facial expressions from grayscale images and maps the detected emotion to a representative emoji (e.g., π for Happy, π’ for Sad, π for Angry).
Model Info
- Framework: TensorFlow / Keras
- Input: 48x48 grayscale facial image
- Output: Predicted emotion label mapped to an emoji
- Model Format:
.keras - Dataset: FER-2013
Emotion to Emoji Mapping
0 β Angry
1 β Disgust
2 β Fear
3 β Happy
4 β Neutral
5 β Sad
6 β Surprise
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Evaluation results
- Accuracy on FER-2013self-reported0.830