A demo program of MPIIGaze and MPIIFaceGaze

With this program, you can runs gaze estimation on images and videos. By default, the video from a webcam is used.

(The original video is from this public domain.)

(The original image is from this public domain.)

To train a model, use this repository.

Quick start

Installation

pip install ptgaze

Run demo

ptgaze --mode eye

Usage

usage: ptgaze [-h] [--config CONFIG] [--mode {eye,face}]
              [--face-detector {dlib,face_alignment_dlib,face_alignement_sfd}]
              [--device {cpu,cuda}] [--image IMAGE] [--video VIDEO]
              [--camera CAMERA] [--output-dir OUTPUT_DIR] [--ext {avi,mp4}]
              [--no-screen] [--debug]

optional arguments:
  -h, --help            show this help message and exit
  --config CONFIG       Config file for YACS. When using a config file, all
                        the other commandline arguments are ignored. See https
                        ://github.com/hysts/pytorch_mpiigaze_demo/configs/demo
                        _mpiigaze.yaml
  --mode {eye,face}     With 'eye', MPIIGaze model will be used. With 'face',
                        MPIIFaceGaze model will be used. (default: 'eye')
  --face-detector {dlib,face_alignment_dlib,face_alignement_sfd}
                        The method used to detect faces and find face
                        landmarks (default: 'dlib')
  --device {cpu,cuda}   Device used for model inference.
  --image IMAGE         Path to an input image file.
  --video VIDEO         Path to an input video file.
  --camera CAMERA       Camera calibration file. See https://github.com/hysts/
                        pytorch_mpiigaze_demo/ptgaze/data/calib/sample_params.
                        yaml
  --output-dir OUTPUT_DIR, -o OUTPUT_DIR
                        If specified, the overlaid video will be saved to this
                        directory.
  --ext {avi,mp4}, -e {avi,mp4}
                        Output video file extension.
  --no-screen           If specified, the video is not displayed on screen,
                        and saved to the output directory.
  --debug

While processing an image or video, press the following keys on the window to show or hide intermediate results:

• l: landmarks
• h: head pose
• t: projected points of 3D face model
• b: face bounding box

References

• Zhang, Xucong, Yusuke Sugano, Mario Fritz, and Andreas Bulling. "Appearance-based Gaze Estimation in the Wild." Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. arXiv:1504.02863, Project Page
• Zhang, Xucong, Yusuke Sugano, Mario Fritz, and Andreas Bulling. "It's Written All Over Your Face: Full-Face Appearance-Based Gaze Estimation." Proc. of the IEEE Conference on Computer Vision and Pattern Recognition Workshops(CVPRW), 2017. arXiv:1611.08860, Project Page
• Zhang, Xucong, Yusuke Sugano, Mario Fritz, and Andreas Bulling. "MPIIGaze: Real-World Dataset and Deep Appearance-Based Gaze Estimation." IEEE transactions on pattern analysis and machine intelligence 41 (2017). arXiv:1711.09017