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| function AboutPage() { | |
| return ( | |
| <div className="page"> | |
| <h2 className="section-title">About CattleAI</h2> | |
| <p className="section-subtitle"> | |
| An AI-powered cattle breed classification system for Indian indigenous breeds. | |
| </p> | |
| <div className="about-grid"> | |
| <div className="card about-card"> | |
| <h3>π§ The Models</h3> | |
| <p>Four deep learning approaches were trained and rigorously compared:</p> | |
| <ul> | |
| <li>MLP Baseline β flatten + dense layers</li> | |
| <li>CNN from Scratch β 5 conv blocks + GAP</li> | |
| <li>ResNet50 Transfer Learning β ImageNet pretrained</li> | |
| <li>ViT-B/16 Transfer Learning β Vision Transformer</li> | |
| </ul> | |
| <p style={{ marginTop: '0.75rem' }}> | |
| The best model is selected using a weighted composite score considering F1, accuracy, | |
| inference speed, and model size. | |
| </p> | |
| </div> | |
| <div className="card about-card"> | |
| <h3>π The Dataset</h3> | |
| <p> | |
| 3,056 images across 26 indigenous Indian breeds (21 cow + 5 buffalo breeds). | |
| Stratified 70/15/15 train/val/test split. | |
| </p> | |
| <ul> | |
| <li>Images resized to 224Γ224 pixels</li> | |
| <li>Augmentation: flip, rotation, jitter, crop</li> | |
| <li>ImageNet normalization applied</li> | |
| <li>Corrupt image validation at preprocessing</li> | |
| </ul> | |
| </div> | |
| <div className="card about-card"> | |
| <h3>βοΈ Tech Stack</h3> | |
| <ul> | |
| <li>PyTorch 2.x + torchvision + timm</li> | |
| <li>FastAPI backend with Pydantic schemas</li> | |
| <li>React + Vite frontend</li> | |
| <li>Docker containerized deployment</li> | |
| <li>Config-driven experiments with YAML</li> | |
| </ul> | |
| </div> | |
| <div className="card about-card"> | |
| <h3>π― Best Model Selection</h3> | |
| <p>Weighted scoring ensures the production model balances performance and practicality:</p> | |
| <div style={{ marginTop: '0.5rem', fontSize: '0.85rem', color: 'var(--color-text-secondary)' }}> | |
| <div className="breed-card-detail"><span className="label">Macro F1</span><span className="value">50%</span></div> | |
| <div className="breed-card-detail"><span className="label">Top-1 Accuracy</span><span className="value">20%</span></div> | |
| <div className="breed-card-detail"><span className="label">Inference Latency</span><span className="value">15%</span></div> | |
| <div className="breed-card-detail"><span className="label">Model Size</span><span className="value">10%</span></div> | |
| <div className="breed-card-detail"><span className="label">Calibration</span><span className="value">5%</span></div> | |
| </div> | |
| </div> | |
| <div className="card about-card"> | |
| <h3>πΎ For Farmers</h3> | |
| <p> | |
| This tool is designed for real-world agricultural use. Features include: | |
| </p> | |
| <ul> | |
| <li>Camera capture for field use</li> | |
| <li>Low-confidence warnings for uncertain predictions</li> | |
| <li>Image quality tips for better results</li> | |
| <li>Breed details including milk yield and primary use</li> | |
| <li>Works offline after initial load (PWA-ready)</li> | |
| </ul> | |
| </div> | |
| <div className="card about-card"> | |
| <h3>π€ Creator</h3> | |
| <p> | |
| Built by Ajaya and team. | |
| </p> | |
| <p style={{ marginTop: '0.5rem' }}> | |
| Source code on{' '} | |
| <a href="https://github.com/amoghakoulapure/cattle-breed-classifier" target="_blank" rel="noreferrer"> | |
| GitHub | |
| </a>. | |
| </p> | |
| <ul style={{ marginTop: '0.5rem' }}> | |
| <li>Backend: FastAPI with PyTorch inference</li> | |
| <li>Frontend: React + Vite</li> | |
| <li>Training: Jupyter notebooks with shared ML package</li> | |
| </ul> | |
| </div> | |
| </div> | |
| </div> | |
| ); | |
| } | |
| export default AboutPage; | |