The squared l2 distance values are different from that of official OpenFace demos. about keras-openface HOT 2 OPEN

This is almost little more than a year later than you asked.
Nevertheless, maybe the reason is that you haven't normalized the input image before computing the forward pass.
Try doing this before feeding the image to model.predict
img = np.around(np.transpose(img, (0,1,2))/255.0, decimals=12)
You can refer the generate embeddings section here for more details.

from keras-openface.

I got similar results without normalizing the input
0.036086053
0.03843207
0.022478495

after normalizing the input I got

0.3701709
1.8563383
2.1030128

which is closer to the demo.

I used the model against my own dataset using MTCNN to align the faces and got an average of .8 for the same person and 1.4 for different people.
is that to be expected?

from keras-openface.