---
license: mit
tags:
  - pytorch
  - mobilenetv2
  - image-classification
  - classroom-engagement
---

# Classroom Engagement MobileNetV2

A lightweight MobileNetV2 classifier trained to estimate classroom
engagement from cropped person bounding boxes.

## Classes

| Index | Label         | Description                              |
|-------|---------------|------------------------------------------|
| 0     | `0_oriented`  | Student facing the instructor/board      |
| 1     | `1_diverted`  | Student turned away or looking elsewhere |
| 2     | `2_obscured`  | Student occluded or not clearly visible  |

## Architecture

- **Backbone:** MobileNetV2 (ImageNet pre-trained, features frozen)
- **Classifier head:** `nn.Linear(1280, 3)`
- **Loss:** Weighted `CrossEntropyLoss` to handle class imbalance
- **Optimizer:** Adam (lr=0.001)
- **Input size:** 224 x 224 RGB, ImageNet-normalized

## Training

Trained on ~200 manually annotated person crops extracted from
classroom lecture videos using YOLOv8-nano detection. Strict
video-level train/val/test split to prevent data leakage.

## Usage

```python
import torch
from torchvision import models, transforms

model = models.mobilenet_v2(weights=None)
model.classifier[1] = torch.nn.Linear(1280, 3)
model.load_state_dict(torch.load("best_baseline.pth", map_location="cpu"))
model.eval()
```