---
license: mit
tags:
  - pytorch
  - vgg16
  - image-classification
  - reaction-recognition
---

# Classroom Reaction Recognition - VGG16

A VGG16 classifier trained to recognize facial reactions of students
from cropped person bounding boxes in classroom lecture videos.

## Classes

| Index | Label            | Description                        |
|-------|------------------|------------------------------------|
| 0     | `Neutral`        | No visible expression              |
| 1     | `Confused`       | Furrowed brow, squinting           |
| 2     | `Smiling_Amused` | Visible smile, laughter            |
| 3     | `Surprised`      | Raised eyebrows, open mouth        |
| 4     | `Bored_Tired`    | Yawning, blank stare               |

## Architecture

- **Backbone:** VGG16 (ImageNet pre-trained, feature layers frozen)
- **Classifier head:** `nn.Linear(4096, 5)`
- **Loss:** Weighted `CrossEntropyLoss` to handle class imbalance
- **Optimizer:** Adam (lr=0.001)
- **Input size:** 224 x 224 RGB, ImageNet-normalized

## Training

Trained on manually annotated person crops extracted from classroom
lecture videos using YOLOv8-nano detection. 70/10/20 stratified
train/val/test split.

## Usage

```python
import torch
from torchvision import models

model = models.vgg16(weights=None)
model.classifier[6] = torch.nn.Linear(4096, 5)
model.load_state_dict(torch.load("best_vgg16.pth", map_location="cpu"))
model.eval()
```