This machine learning-based web application is designed to identify famous Bangladeshi personalities based on their photographs and provide details based on that. By analyzing the visual features of the images and applying advanced algorithms, the application is able to accurately classify and recognize the individuals depicted in the photos upto a certain extent.
Steps for Adding and Preprocessing Additional Dataset for Famous Bangladeshi Personality Classification:
- Create a new folder with at least 30-40 images of a specific person, ensuring that the images clearly show their face.
- Rename the folder with the person's name (e.g. Mr Tom).
- Copy or cut and paste the folder into the following directories:
- Run the following notebooks in the specified order:
To complete these instructions, you will need to have Python and the required packages installed on your system. You can install the required packages by running the command pip install -r requirements in your terminal. This will install all of the necessary packages specified in the requirements.txt file.
- Machine Learning Algorithms : Random Forest, Support Vector Machine (SVM), Logistic Regression
- Machine Learning Library : scikit-learn
- Front-End : HTML, Bootstrap, JavaScript
- Go to
Server
directory - Open terminal on this directory
- Type
python server.py
in the terminal and hit Enter - Go to
UI
directory - Open
app.html
- Hurrah...!!
- 2018331089 - Ali Al - Reza
- 2018331029 - Ishrat Jahan
- 2018331071 - Nishat Rahman
- 2018331081 - Md Ataullha
- 2018331111 - Redwanur Rahman Akanda
This deep learning-based web application is designed to identify famous Bangladeshi personalities based on their photographs and provide details based on that. By analyzing the visual features of the images and applying advanced cnn algorithm, the application is able to accurately classify and recognize the individuals depicted in the photos upto a certain extent.
- Machine Learning Algorithms : Convolutional Neural Network (CNN)
- Deep Learning Framework : TensorFlow
- Web App Framework : Streamlit
- Go to
.spyder-py3
directory - Open terminal on this directory
- Type
streamlit run temp.py
in the terminal and hit Enter (tensorflow needed) - Hurrah...!!
- 2018331089 - Ali Al - Reza
- 2018331029 - Ishrat Jahan
- 2018331071 - Nishat Rahman
- 2018331081 - Md Ataullha
- 2018331111 - Redwanur Rahman Akanda