Implementation of MTCNN using Pytorch.
Project description
MTCNN
pytorch
implementation of inference stage of face detection algorithm described in
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks.
Example
How to use it
Just download the repository and then do this
from src import detect_faces
from PIL import Image
image = Image.open('image.jpg')
bounding_boxes, landmarks = detect_faces(image)
For examples see test_on_images.ipynb
.
Requirements
- pytorch 0.2
- Pillow, numpy
Credit
This implementation is heavily inspired by:
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
torch-mtcnn-0.0.1.tar.gz
(6.6 kB
view hashes)
Built Distribution
Close
Hashes for torch_mtcnn-0.0.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0ba7e972b9114862b6f7199687ba19a06240c216041d2247714f8309e05962dd |
|
MD5 | b6cfe77649d0ed4ff342d5a147cd314f |
|
BLAKE2b-256 | 567b1074d38ec6d2e69f082082bb25f2ec2bc62620e2d6dd8a79d3d766664c40 |