---
language: en
license: apache-2.0
library_name: pytorch
tags:
- image-classification
- autonomous-vehicles
- ai-safety
metrics:
- accuracy
---

# Vehicle Classification - UTD Evaluation

This model is a custom CNN architecture trained to classify 8 categories of vehicles. 

## 📝 Model Card
- **Architecture:** 3-Block Custom CNN (Not Pretrained)
- **Target Accuracy:** >50.0%
- **Final Test Accuracy:** 78.54%

## 📂 Dataset & Split
The model utilizes a dataset of 26,378 images with an 8:2 train-test split.
- **Training Samples:** 21,102
- **Testing Samples:** 5,276
- **Normalization:** Mean [0.485, 0.456, 0.406], Std [0.229, 0.224, 0.225]

## 🛡️ Safety & Robustness Features
To align with AI Safety principles, the following design choices were implemented:
1. **High Regularization:** Dropout (0.5) to prevent over-reliance on high-frequency noise.
2. **Feature Stability:** Batch Normalization to maintain stable gradient flow across epochs.
3. **Generalization Proof:** The 0.06% delta between training and testing accuracy confirms the model's reliability on unseen data.

## ⚠️ Limitations & Future Scope
- **Edge Cases:** Slight confusion between 2-wheeled vehicle classes (Bicycle/Motorcycle).
- **Environment:** Performance has not yet been validated for low-light or adverse weather conditions.

## 🔗 Links for this project
* **[GitHub Repository](https://github.com/abhiprd200/vehicle_classification_model-utd)**
* **[Hugging Face Model Card](https://huggingface.co/abhiprd20/vehicle_classification_model-utd)**
* **[Hugging Face Spaces Deployment](https://huggingface.co/spaces/abhiprd20/vehicle_classification_model-utd)**
* **[Published Technical Note](https://zenodo.org/records/19098404)**

## 🛠️ Other Key Projects
* **Language Datasets**: Curated and published 100k+ rows datasets for low resource languages on Hugging Face for regional NLP research.
* **CNSD Model Architecture**: Authored research on neural network configurations for optimized feature extraction.
* Custom 4 sentiment models, 1 vehicle classification model and several datasets.
* Link to my Hugging Face account : https://huggingface.co/abhiprd20 (with all models and datasets)
* My NLP research paper pre-print : https://zenodo.org/records/19054785
* 2nd research project : https://github.com/abhiprd200/CNSD_prototype
* **Demo of this project:** [Live on Hugging Face Spaces]((https://huggingface.co/spaces/abhiprd20/vehicle_classification_model-utd))
* My github with other projects : https://github.com/abhiprd200



## Contact
* E-mail : abhiprd20@gmail.com


## 🚀 Usage
```python
import torch
# Architecture must match VehicleClassifier class in provided app.py
model.load_state_dict(torch.load("model.pth", map_location="cpu"))
model.eval()