Music Videos Visual Feature Extraction

This repository contains utilities for extracting visual features from Music Videos.

☑️ Prerequisites

In order to run the application, you will need to install the Python libraries listed below:

• Python >= 3.7
• NumPy >= 1.19
• SciPy >= 1.6
• PyInquirer >= 1.0.3
• OpenCV-Python >= 4.1.1
• Tensorflow >= 2.6.0
• Keras >= 2.6.0
• CUDA >= 11.4
• Pandas >= 1.3.4

For a simple solution, you can simply run the below command in the root directory:

pip install -r requirements.txt

Note that you should also install NVIDIA® CUDA® Deep Neural Network library™ (cuDNN) for high-performance GPU acceleration. This is used when training the DNN models in the feature extraction stage.

🚀 Launch the Application

The first step to run the engine of the application is to provide a proper configuration file. The main.py file, which is the start point of the application, needs such file to provide customized configurations for its differernt modules and then run the application:

I. Make a Configuration File

You can find a config.example.py in the root directory. What you need to do is to make a copy of this file and rename it to config.py. There, you can apply your customized settings. Please note that the config.py is placed in .gitignore file due to the customized settings.

II. Run the Application

After providing the configurations, you can easily run the app using the command below in the root directory:

python ./main.py

Please note that we assumed videos are already FPS=1 and ignored the process capturing one frame per second.