---
tags:
- clip
- moral-foundations
- vision
- image-classification
- multimodal
license: mit
---

# Visual Moral Compass

Visual Moral Compass is a fine-tuned CLIP model that classifies images based on Moral Foundations Theory.

## Model Description

This model extends CLIP (openai/clip-vit-base-patch16) with five classifier heads to predict moral dimensions in images:
- **Care vs. Harm**: Concerns about suffering and protection
- **Fairness vs. Cheating**: Concerns about justice and reciprocity  
- **Loyalty vs. Betrayal**: Concerns about group membership and solidarity
- **Respect vs. Subversion**: Concerns about hierarchy and authority
- **Sanctity vs. Degradation**: Concerns about purity and contamination

## Usage

```python
from visual_moral_compass import VisualMoralCompass

# Load model
model = VisualMoralCompass.from_pretrained("YOUR_USERNAME/visual-moral-compass")

# Classify an image
results = model.classify_image("path/to/image.jpg")
print(results)
```

## Citation

If you use this model, please cite:

```bibtex
@inproceedings{moralclip2025,
      author = {Condez, Ana Carolina and Tavares, Diogo and Magalh\~{a}es, Jo\~{a}o},
      title = {MoralCLIP: Contrastive Alignment of Vision-and-Language Representations with Moral Foundations Theory},
      year = {2025},
      isbn = {9798400720352},
      publisher = {Association for Computing Machinery},
      address = {New York, NY, USA},
      doi = {10.1145/3746027.3758166},
      booktitle = {Proceedings of the 33rd ACM International Conference on Multimedia},
      pages = {12399–12408},
      numpages = {10},
      location = {Dublin, Ireland},
      series = {MM '25}
    }
```

## Model Details

- **Base Model**: openai/clip-vit-base-patch16
- **Training Data**: Social-Moral Image Database