Dog_emotion_classification_webapp

Overview

This is a web applcation built on react and fastapi. It takes an image of a dog as an input and uses deep learning to classify the emotion of dog in three classes (happy, sad, angry)

Features

• Image upload: Users can upload pictures of dogs.
• Deep Learning Model: Utilizes a pre-trained model for dog emotion recognition.
• Real-time Classification: Emotion classification happens in real-time as users capture images.
• Intuitive UI: A user-friendly interface displaying the picture and the classified emotion.

Technologies Used

• Your Framework or Technology: Brief description.
• Deep Learning Framework: Mention the deep learning framework or library you used.
• Camera Integration: Briefly describe how the camera is integrated.

Getting Started

Installation

1. Clone the repository:

   git clone https://github.com/Rc17git/Dog_emotion_classification_webapp.git
   cd movie-recommendation-app
   

2. install dependencies:

   pip install -r requirements.txt

3. Set up a virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate

4. Run the application:

   cd fastapi
   uvicorn main:app --reload
   cd ..
   cd emotion-app
   npm start
   

Screenshots

This is how the website should look once you have set up everything correctly.

Caption: This is the landing page

Caption: This is the results page

Contributing

If you'd like to contribute to this project, please follow the standard GitHub fork and pull request workflow.