Skip to main content

High-performance cross-platform MTCNN face detection with CUDA and Apple Neural Engine support

Project description

pymtcnn

MTCNN face detection with CoreML (Apple Silicon) and CUDA support.

Installation

pip install pymtcnn

Usage

from pymtcnn import MTCNN

detector = MTCNN()  # auto-selects best backend
boxes, landmarks = detector.detect(image)

What it does

  • Detects faces and 5-point facial landmarks
  • Auto-selects backend: CoreML on Mac, CUDA on NVIDIA, CPU fallback
  • ~34 FPS on Apple Silicon, ~50 FPS on CUDA

Citation

If you use this in research, please cite:

Wilson IV, J., Rosenberg, J., Gray, M. L., & Razavi, C. R. (2025). A split-face computer vision/machine learning assessment of facial paralysis using facial action units. Facial Plastic Surgery & Aesthetic Medicine. https://doi.org/10.1177/26893614251394382

License

CC BY-NC 4.0 — free for non-commercial use with attribution.

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

pymtcnn-1.1.1.tar.gz (1.9 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pymtcnn-1.1.1-py3-none-any.whl (1.9 MB view details)

Uploaded Python 3

File details

Details for the file pymtcnn-1.1.1.tar.gz.

File metadata

  • Download URL: pymtcnn-1.1.1.tar.gz
  • Upload date:
  • Size: 1.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for pymtcnn-1.1.1.tar.gz
Algorithm Hash digest
SHA256 a149fb3039b5531538b48d8c72487de087fe4ccd6fe5a67f49fc30456c76ceee
MD5 8d9e513cf75845ec9ec54105f2fac716
BLAKE2b-256 d7e5cd473e33f3814b0c15744fe4a394ded438e799a6b14e164f147bee542aab

See more details on using hashes here.

Provenance

The following attestation bundles were made for pymtcnn-1.1.1.tar.gz:

Publisher: publish.yml on johnwilsoniv/pymtcnn

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file pymtcnn-1.1.1-py3-none-any.whl.

File metadata

  • Download URL: pymtcnn-1.1.1-py3-none-any.whl
  • Upload date:
  • Size: 1.9 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for pymtcnn-1.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 5641cb37feaa28dd9ab3369432335801c6a48e32e9aef02d8f648eb68d3329e9
MD5 772f944b9a55bb255eb8a59293b431cf
BLAKE2b-256 4d2b176aa1b75de71bb5c31cfe2ea457b75c5547ec74bed47de2bd45e85edf81

See more details on using hashes here.

Provenance

The following attestation bundles were made for pymtcnn-1.1.1-py3-none-any.whl:

Publisher: publish.yml on johnwilsoniv/pymtcnn

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

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