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face-expression-classification
harkishankhuva/face-expression-classification
face-expression-classification is a image classification model from harkishankhuva. Use it when you need a label for an image. It is set up for keras. The card lists the license as mit.
This model is designed for facial expression classification and it uses custom CNN model to classify the images into 7 different categories.
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At a glance
- Task
- Image Classification
- Library
- keras
- License
- mit
- Access
- Public
- Created
- May 19, 2025
- Updated
- May 19, 2025
- SHA
- b61f003f
Model card
From the Hugging Face model README
Facial expression classification model
This model is designed for facial expression classification and it uses custom CNN model to classify the images into 7 different categories.
This CNN Model is to classify the facial expression into one of the following categories:
- Anger
- Disgust
- Fear
- Happiness
- Neutral
- Sadness
- Surprise
Architecture Summary
| Layer (type) | Output Shape | Param # |
|---|---|---|
| conv2d (Conv2D) | (None, 46, 46, 32) | 320 |
| max_pooling2d (MaxPooling2D) | (None, 23, 23, 32) | 0 |
| dropout (Dropout) | (None, 23, 23, 32) | 0 |
| conv2d_1 (Conv2D) | (None, 21, 21, 64) | 18,496 |
| max_pooling2d_1 (MaxPooling2D) | (None, 10, 10, 64) | 0 |
| batch_normalization (BatchNormalization) | (None, 10, 10, 64) | 256 |
| dropout_1 (Dropout) | (None, 10, 10, 64) | 0 |
| conv2d_2 (Conv2D) | (None, 8, 8, 128) | 73,856 |
| max_pooling2d_2 (MaxPooling2D) | (None, 4, 4, 128) | 0 |
| batch_normalization_1 (BatchNormalization) | (None, 4, 4, 128) | 512 |
| dropout_2 (Dropout) | (None, 4, 4, 128) | 0 |
| conv2d_3 (Conv2D) | (None, 2, 2, 128) | 147,584 |
| flatten (Flatten) | (None, 512) | 0 |
| dense (Dense) | (None, 96) | 49,248 |
| dropout_3 (Dropout) | (None, 96) | 0 |
| dense_1 (Dense) | (None, 96) | 9,312 |
| dropout_4 (Dropout) | (None, 96) | 0 |
| dense_2 (Dense) | (None, 64) | 6,208 |
| dense_3 (Dense) | (None, 7) | 455 |
Total params: 306,247 (1.17 MB)
Trainable params: 305,863 (1.17 MB)
Non-trainable params: 384 (1.50 KB)
Training details
- Dataset: https://www.kaggle.com/datasets/manishshah120/facial-expression-recog-image-ver-of-fercdataset
| Name | Value |
|---|---|
| Input shape | 48x48 (48, 48, 1) |
| Optimizer | Adam |
| Loss | Crossentropy |
| Max epochs | 200 |
| Early stopping monitor | val_loss |
| Early stopping patience | 12 |
Model performance
- Training Accuracy: 0.5758 (Epoch #84)
- Training Loss: 1.1272 (Epoch #84)
- Validation Accuracy: 0.5823 (Epoch #84)
- Validation Loss: 1.1285 (Epoch #84)
Classification report
precision recall f1-score support
0 0.52 0.40 0.45 491
1 0.00 0.00 0.00 55
2 0.43 0.17 0.25 528
3 0.83 0.84 0.83 879
4 0.51 0.67 0.58 626
5 0.39 0.58 0.47 594
6 0.73 0.72 0.73 416
accuracy 0.58 3589
macro avg 0.49 0.48 0.47 3589
weighted avg 0.58 0.58 0.57 3589
Notebook
Training notebook: https://www.kaggle.com/code/harkishankhuva/facial-expression-classification
- Task
- Image Classification
- Library
- keras
- License
- mit
- Created
- May 19, 2025
- Updated
- May 19, 2025