function AboutPage() { return (

About CattleAI

An AI-powered cattle breed classification system for Indian indigenous breeds.

🧠 The Models

Four deep learning approaches were trained and rigorously compared:

  • MLP Baseline — flatten + dense layers
  • CNN from Scratch — 5 conv blocks + GAP
  • ResNet50 Transfer Learning — ImageNet pretrained
  • ViT-B/16 Transfer Learning — Vision Transformer

The best model is selected using a weighted composite score considering F1, accuracy, inference speed, and model size.

📊 The Dataset

3,056 images across 26 indigenous Indian breeds (21 cow + 5 buffalo breeds). Stratified 70/15/15 train/val/test split.

  • Images resized to 224×224 pixels
  • Augmentation: flip, rotation, jitter, crop
  • ImageNet normalization applied
  • Corrupt image validation at preprocessing

⚙️ Tech Stack

  • PyTorch 2.x + torchvision + timm
  • FastAPI backend with Pydantic schemas
  • React + Vite frontend
  • Docker containerized deployment
  • Config-driven experiments with YAML

🎯 Best Model Selection

Weighted scoring ensures the production model balances performance and practicality:

Macro F150%
Top-1 Accuracy20%
Inference Latency15%
Model Size10%
Calibration5%

🌾 For Farmers

This tool is designed for real-world agricultural use. Features include:

  • Camera capture for field use
  • Low-confidence warnings for uncertain predictions
  • Image quality tips for better results
  • Breed details including milk yield and primary use
  • Works offline after initial load (PWA-ready)

👤 Creator

Built by Ajaya and team.

Source code on{' '} GitHub .

  • Backend: FastAPI with PyTorch inference
  • Frontend: React + Vite
  • Training: Jupyter notebooks with shared ML package
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