/python-face-emotion-video

combines facial landmark detection and emotion recognition to analyze emotions in a video using artificial intelligence

Primary LanguagePython

README.md

AI-Enhanced Facial Emotion Recognition in Video

Overview

This project combines facial landmark detection and emotion recognition to analyze emotions in a video using artificial intelligence. It utilizes computer vision techniques, TensorFlow, and Mediapipe to detect facial landmarks and a pre-trained model to predict emotions. The resulting video is annotated with emotion labels for a more immersive viewing experience.

Dependencies

Ensure you have the following dependencies installed:

  • OpenCV (cv2)
  • Mediapipe
  • NumPy
  • TensorFlow (with Keras)
  • Various other Python libraries

To install the required dependencies, run the following command:

pip install opencv-python mediapipe numpy tensorflow

Downloading Required Files

  1. FER (Facial Emotion Recognition) Model:

    • Download the FER model files from the following link: FER Model

      Place the downloaded files in the project directory, and update the file path in the script:

      fer_model = load_model("path/to/FER_model.h5")  # Replace with the actual path

  2. Emotion Recognition Retail Model:

    • Download the Emotion Recognition Retail model files from the OpenVINO Model Zoo: Emotion Recognition Retail Model

      Place the downloaded files (emotions-recognition-retail-0003.bin and emotions-recognition-retail-0003.xml) in the project directory, and update the file paths in the script:

      emotion_model_bin = "path/to/emotions-recognition-retail-0003.bin"  # Replace with the actual path
emotion_model_xml = "path/to/emotions-recognition-retail-0003.xml"  # Replace with the actual path

  3. Other Dependencies:

    • Install the necessary Python libraries by running:

      pip install opencv-python mediapipe numpy tensorflow

    • Make sure to have OpenCV, Mediapipe, NumPy, and TensorFlow installed.

Usage

  1. Clone this repository:
git clone <repository-url>
cd <repository-directory>
  1. Install dependencies:
pip install -r requirements.txt

  1. Download the FER (Facial Emotion Recognition) model:

    Replace "path/to/FER_model.h5" with the actual path where the FER model is located.

  2. Run the script:

python emotion_recognition.py

The script will process the input video, annotate facial landmarks, and display the video with emotion labels.

Notes

  • The script assumes the input video is located at "nosubs.mp4". Replace this with the actual path of your video.
  • The output video will be saved as "nosubs-output.mp4".
  • Press q to exit the application.

Additional Information

For more details on the project and its components, refer to the code documentation and associated resources.

Acknowledgments

  • Mediapipe for providing facial landmark detection capabilities.
  • FER Model for emotion recognition.

Feel free to explore and modify the code to suit your specific requirements.

Note: Adjust the paths, video filenames, and other configurations based on your local setup.