ipazc/mtcnn

Health v2 · maintenance only

Adoption not part of the score

2485 stars · 527 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Python library implementing the MTCNN (Multitask Cascaded Convolutional Networks) algorithm for face detection and facial landmark alignment, built on TensorFlow 2.x and distributed as a pip package. It detects faces with bounding boxes and predicts keypoints (eyes, nose, mouth) using a cascade of three neural networks, with support for batch processing and device selection.

Use cases

• detect faces in images with bounding boxes
• find facial landmarks like eyes, nose and mouth
• align faces before face recognition preprocessing
• batch process a folder of photos to extract face crops
• filter images that contain no detectable faces
• build a face verification pipeline in Python

When to choose

• you need accurate face detection plus landmark points in a Python/TensorFlow stack
• you want a simple pip-installable detector with a minimal API
• you need face alignment keypoints for downstream recognition or embedding models
• you want batch processing of images on CPU or GPU

When to avoid

• you need real-time video face detection at high frame rates on edge devices
• your stack is PyTorch-only and you don't want a TensorFlow dependency
• you need face recognition or identity matching, not just detection
• you need masks, occlusion handling, or state-of-the-art detector accuracy on hard cases

Facets

library · maturity stable

computer-vision image-processing machine-learning deep-learning computer-vision image-processing machine-learning python cross-platform face-detection facial-landmarks mtcnn tensorflow face-alignment bounding-boxes pip-package gpu

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