AI-Powered Horse Characteristics Measurement and Description

Project Snapshot

• Industry: Agriculture / Veterinary AI

• Client Type: Animal Health & Livestock Management Organizations

• Duration: Multi-phase implementation

• Deployment Model: Cloud-native solution on AWS

• Technologies: CNN, YOLO, Pose Estimation, Pixel-to-CM Conversion, OpenAI GPT, Django, Docker, AWS EC2, S3

The Challenge

Measuring and documenting horse characteristics is traditionally a manual, time-consuming, and error-prone process. The client needed an AI-driven system to:

• Accurately detect horse breed, color, and body parts

• Perform pose estimation and dimensional measurements with high precision

• Automate the process of generating detailed descriptive reports

• Ensure scalable and reliable deployment on the cloud for broad usability

Our Solution

We engineered a computer vision and AI-powered solution for automated horse characteristics measurement and reporting:

• Breed & Color Detection

  • Trained a Convolutional Neural Network (CNN) for the classification of horse breeds and colors with high accuracy.

• Body Part Detection

  • Deployed YOLO-based object detection for identifying key body parts of horses.

• Pose Estimation & Measurement

  • Implemented pose estimation techniques combined with pixel-to-CM conversion, achieving 90–95% accuracy in measurements.

• AI-Generated Descriptions

  • Developed an AI-powered description generator using OpenAI GPT, automating the generation of natural language summaries for horses’ physical characteristics.

• Cloud Deployment

  • Delivered a production-ready platform using Django for APIs and dashboards, deployed on AWS EC2 with secure storage on S3 and containerized with Docker.

The Impact

The solution delivered measurable benefits:

• 90–95% Accuracy in dimensional measurement through pose estimation

• Automated Descriptions reduced the manual documentation workload

• Enhanced Reliability for livestock assessments and veterinary records

• Scalable Cloud Deployment ensured usability across multiple sites and teams

• Time Efficiency → Significant reduction in manual measurement and reporting efforts

Our Role

We collaborated with the client to:

• Build CNN and YOLO models for visual classification and detection

• Implement pose estimation and measurement systems

• Develop an AI-based description generation with GPT

• Deploy a cloud-native solution using AWS and Docker

Client Testimonial

“The AI-powered horse measurement and description system has significantly improved efficiency and accuracy in livestock management. Automated detection and reporting save us time while maintaining reliability.”
— Head of Veterinary Analytics