Simple UI demo
Screencast.from.13-07-23.00.16.11.webm
- Raw Arabic captions dataset
- preprocessed train and test sets
- Deep learning model with attention (CNN encoder + RNN Decoder)
- fastapi server
To get started with the project, you will need to clone the repository to your local machine:
git clone [email protected]:AmgadHasan/arabic-image-captioning.git
Once you have cloned the repository, you can open the project in your preferred code editor and start exploring the code.
To run the project, you will need to have the following installed on your machine:
- tensorflow (for the deep learning model)
- tensorflow, fastapi, uvicron, pyantic (for the api)
You can run the following command to install these packages:
pip install -r requirements.txt
To run the web app, go to the project's directory and run the following command:
python -m uvicorn main:app --reload
Contributions are welcome! To contribute, please follow these steps:
Fork the repository. Create a new branch for your feature or bug fix: git checkout -b my-new-feature.
Make changes and commit them:
git commit -am 'Add some feature'
Push to the branch:
git push origin my-new-feature
Submit a pull request.
This project is licensed under the Apache 2.0 License - see the LICENSE file for details.
This project was created by:
Special thanks to Mr. Mohamed El Mesawy for supervising this project.
Copyright 2023 Amgad Hasan, Abdelwahab Elghandour
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.