An API utilizing ResNet50 Architecture to identify Egyptian monuments/Landmarks and provide relevant information. The API aims to enhance tourists' experience by providing historical context and relevant information about the rich cultural heritage of Egypt.
# Identifying-Egyptian-Artifacts-Landmarks-API
### Project Idea
An API utilizing ResNet50 Architecture with Knowledge Transfer (KT) to identify Egyptian monuments/Landmarks and provide relevant information. The API aims to enhance tourists' experience by providing historical context and relevant information about the rich cultural heritage of Egypt.
> Note: API may stop working after AWS free tier ends for my account
> #### GET All Classes [GET]:
identifying-egyptian-artifa…
> #### Prediction Endpoint [POST]:
identifying-egyptian-artifa…
> #### GET Specific Classe using class id: [GET]:
identifying-egyptian-artifa…
> #### Search Using Class Name [GET]:
identifying-egyptian-artifa…'search_keyword_without_quotes'
> #### Dataset:
kaggle.com
### Main objectives
- Robust AI-powered image classification API capable of accurately classifying Egyptian artifacts and landmarks.
- List classes availabe in the database with relevant information
### Technologies used in this project:
- AWS (EC2)
- Circleci
- Docker
- Python
- Pytorch
- Flask
- PostgreSQL
### To be added:
- Unit Testing
- Linting/Prettier module
> Note: No sensitive data are hardcoded in the code, instead it is passed through the environment variables in both amazon EC2 and CircleCI
#### Database schemas ERD
#### Documentation of all dependencies is found in the App dependencies.md file in the docs directory
#### A screenshot of the last build is found the docs directory in the Github repository
#### Documentation of the pipeline is found in the Pipeline process.md file in the docs directory
> Click on the status icon to view the pipeline
#### Architecture diagram for an overview of the infrastructure and the pipeline