https://github.com/shashanksola/bird-species-classification-in-natural-habitat

The aim of this project is to predict Indian bird species. This project can validate if the image contains a bird, the scenery of the image (lake, forest etc) finally predicting the bird.
https://github.com/shashanksola/bird-species-classification-in-natural-habitat

aws birds classification javascript machine-learning nodejs python recognition validation

Last synced: 21 days ago
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The aim of this project is to predict Indian bird species. This project can validate if the image contains a bird, the scenery of the image (lake, forest etc) finally predicting the bird.

• Host: GitHub
• URL: https://github.com/shashanksola/bird-species-classification-in-natural-habitat
• Owner: shashanksola
• License: mit
• Created: 2024-08-24T10:49:22.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2025-05-03T16:13:49.000Z (6 months ago)
• Last Synced: 2025-05-03T17:24:03.365Z (6 months ago)
• Topics: aws, birds, classification, javascript, machine-learning, nodejs, python, recognition, validation
• Language: JavaScript
• Homepage: https://indian-bird-species.vercel.app/
• Size: 114 MB
• Stars: 3
• Watchers: 1
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md

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README

          
# bird-species-classification-in-natural-habitat

### Web Application Summary: Indian Bird Species Detection using Deep Learning

## 1. Project Description and Requirements:

The web application is designed to detect and classify Indian bird species from user-uploaded images using deep learning. Users can either upload a photo or select one from their gallery. The system needs to identify bird species accurately, validate the presence of birds in the image, and handle multiple bird detections.

Key Requirements:



  
Develop a custom dataset with images of various Indian bird species. 

  
Train a deep learning model capable of accurate bird species classification. 

  
Implement the model in a web application with a user-friendly interface. 

  
Deploy the web application on a cloud platform for scalability and accessibility. 



## 2. Purpose:

The purpose of the web application is to provide a tool for bird enthusiasts, researchers, and educators to identify bird species from images, supporting bird conservation and education efforts.

## 3. Specifications:



  
Dataset: A diverse collection of images representing different bird species in India 

  
Functionality: Users can upload images, and the system will classify the species, validate bird presence, and detect multiple species if present. 

  
Model Inference: TensorFlow will be used to ensure efficient processing of images. 

  
User Interface: A responsive design to ensure compatibility across different devices and screen sizes. 

  
Deployment: Hosted on AWS to provide a scalable and accessible platform. 



## 4. Summary of the Approach:

The approach for the web application starts with the development of a custom dataset and the training of a deep learning model. The model will be integrated into a web application built with NodeJS for the backend and React for the frontend.

The application will allow users to upload images, which are then processed by the model to classify the bird species. The model will be hosted on a cloud platform to enable access from any device. The application will undergo testing to ensure accuracy and usability before being deployed publicly

### Architecture (Progressive):

Iteration 1

![image](https://github.com/user-attachments/assets/0ffd68aa-cbb9-4e5a-b072-3c74f4594481)

Iteration 2