face-compare

face-comparison

AI Face comparison using FaceNet, compare two photos and see if they are the same person.

Installation

pip install face-compare

Usage

Use compare_faces.py to compare two images of people to see if they are the same person.

compare_faces.py --image-one /path/to/image_one.png --image-two /path/to/image_two.png

Optionally output the cropped image output to a directory (useful for inspecting input to AI model)

compare_faces.py --image-one /path/to/image_one.png --image-two /path/to/image_two.png -s /path/to/outputs/

Steps Involved

• A cascade classifier is used to detect the face within the input images.
• The bounding box of this segmentation is then used to crop the images, and fed into the AI model.
• The FaceNet model then calculates the image embeddings for the two cropped images.
• Finally the second embedding is subtracted from the first, and the Euclidean norm of that vector is calculated.
• A threshold of 0.7 is used to determine whether they are the same person or not.

Known Issues

CPU Only runtime issue

If you are trying to run the module without a suitable GPU, you may run into the following error message:

tensorflow.python.framework.errors_impl.InvalidArgumentError:  Default MaxPoolingOp only supports NHWC on device type CPU

To fix this issue with Intel CPU architecture, you can install the TensorFlow Intel Optimization package via

pip install intel-tensorflow

References

This module uses the AI model FaceNet, which can be found here, and the journal article here.