Skip to main content

Gaze estimation using MPIIGaze and MPIIFaceGaze

Project description

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.

MPIIGaze video result MPIIFaceGaze video result

(The original video is from this public domain.)

MPIIGaze image result

(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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ptgaze-0.0.4.tar.gz (20.6 kB view details)

Uploaded Source

Built Distribution

ptgaze-0.0.4-py3-none-any.whl (26.3 kB view details)

Uploaded Python 3

File details

Details for the file ptgaze-0.0.4.tar.gz.

File metadata

  • Download URL: ptgaze-0.0.4.tar.gz
  • Upload date:
  • Size: 20.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.7.3 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.9.2

File hashes

Hashes for ptgaze-0.0.4.tar.gz
Algorithm Hash digest
SHA256 8d630c2b507783ab702f50dca38283c09af156f635a0e54b3750a65a3cdcffee
MD5 f4ba13b33b4c735b5f27f9522484c3c7
BLAKE2b-256 916d53d100ac75f7e22dfbed8643d9842ed2dfe069f1c975739a6bbcb863745a

See more details on using hashes here.

File details

Details for the file ptgaze-0.0.4-py3-none-any.whl.

File metadata

  • Download URL: ptgaze-0.0.4-py3-none-any.whl
  • Upload date:
  • Size: 26.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.7.3 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.9.2

File hashes

Hashes for ptgaze-0.0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 16023f8b36945d00efd6159a252410eea00c64c536934cbd88fe19bf454835de
MD5 26b8d1f56bb6e3df655f458ffb62d4b7
BLAKE2b-256 4a4e5a787aa8801a7e1de800e3bb2f717281c73f7b46c6ffb0c0f7c329e3b063

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page