Pawsighnt is an AI-powered veterinary emotion analysis system built as both a software platform and a hardware-integrated solution. It analyzes dog posture, movement, and behavior from video input to determine emotional states such as happiness, stress, activity level, and overall mental well-being. The system presents these insights through a user-friendly interface, AI-generated vet summaries, voice feedback, and visual graphs.

The project demonstrates how computer vision, AI reasoning, and user-centered design can be combined to create an intelligent digital vet assistant.

Pet owners often misinterpret or overlook subtle behavioral changes in their dogs, which can be early signs of stress, discomfort, or health issues. Traditional monitoring methods rely heavily on human observation, which is subjective and inconsistent. There is a strong need for an intelligent, automated system that can continuously analyze dog behavior and emotions to provide meaningful insights. PawSighnt is motivated by the goal of improving animal welfare, enabling early intervention, and strengthening the bond between pets and their owners through technology.

python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Create a .env file in the root directory and add:

NOVITA_KEY=your_novita_api_key
ELEVAN_LAB=your_elevenlabs_api_key
TAVILY=your_tavily_api_key

python app.py

http://127.0.0.1:5000

Upload a dog video and explore emotion analysis, AI vet summary, voice feedback, graphs, and chatbot.

• Python 3.8+
• GPU (optional but recommended for YOLO)