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Py-Feat - Home
  • Py-Feat: Python Facial Expression Analysis Toolbox

Getting Started

  • How to install Py-Feat
  • Included pre-trained detectors
  • Action Unit Reference
  • Tips, Community, and Known Issues
  • FAQS

Basic Tutorials

  • 1. Detecting facial expressions from images
  • 2. Detecting facial expressions from videos
  • 3. Visualizing Facial Expressions
  • 4. Running a full analysis

Advanced Tutorials

  • 6. Training an AU visualization model
  • 7. Example labels and landmark dataset loading
  • 8. Training HOG-based AU detectors
  • 9. Benchmarking Bounding Box using data
  • 10. Benchmarking Landmark models using data
  • 11. Benchmarking Pose detectors using data
  • 12. Benchmarking Action Unit detector using data
  • 13. Benchmarking pyfeat Emotion detection algorithms using data

API

  • API Reference

Benchmarks

  • Accuracy benchmarks
  • Throughput benchmarks

Contributing

  • General contributions guidelines
  • Contributing new detectors
  • Change Log
  • GitHub Repository
  • Repository
  • Open issue

Index

F | G | H | I | M | S

F

  • feat.utils
    • module
  • flatten_list() (in module feat.utils)

G

  • generate_coordinate_names() (in module feat.utils)

H

  • hf_hub_download_with_fallback() (in module feat.utils)

I

  • is_list_of_lists_empty() (in module feat.utils)

M

  • module
    • feat.utils

S

  • set_torch_device() (in module feat.utils)

By Eshin Jolly, Jin Hyun Cheong, Tiankang Xie, Luke J. Chang

© Copyright 2022.