ScreenTimeCalculator

ScreenTimeCalculator is a tool for calculating character screen time in videos using face detection and recognition techniques. It employs RetinaFace for accurate face detection and FaceNet for embedding extraction, enabling users to analyze video content efficiently. Ideal for filmmakers and researchers seeking to quantify character presence.

Key Features

• Detects faces in videos using RetinaFace.
• Clusters faces to identify different characters.
• Calculates screen time for each character.
• User-friendly command-line interface for easy interaction.

Technologies Used

• Python
• OpenCV
• Keras with TensorFlow
• NumPy
• Matplotlib

Installation

1. Clone the repository:

   git clone https://github.com/SAHFEERULWASIHF/ScreenTimeCalculator.git

2. Navigate to the project directory:

   cd ScreenTimeCalculator

3. Install the required dependencies:

   pip install -r requirements.txt

Usage Instructions

1. Place your video file in the input directory (create this directory if it doesn’t exist).
2. Run the main script:

   python main.py

3. Follow the prompts to analyze the video. The program will process the video, detect faces, and calculate screen time for each identified character.

Example Output

The program will output the detected characters along with their respective screen time. Below is an example of the expected output format:

Total screen time for women: 35.34 seconds based on 848 frames
Total screen time for kamal: 9.17 seconds based on 220 frames

Additionally, a visual representation (e.g., a plot or chart) may be displayed to illustrate the screen time distribution among characters.

[Sample Input]

sample.input.mp4

[Respective Sample Output]

sample.output.mp4