CODEWITHSUNDEEP
pythonface-detectiondlib
Dennis
Dennis

Reputation: 81

dlib face detection failing to catch

Ive been exploring dlib's face detector over its python API. On most images in my data set it seems to perform slightly better than cv2 on most images so I kept playing around with it on multiple faces in picture scenarios.

Going through dlib's python examples it seems like it would be possible to train these images but I am wondering if anyone has a suggestion how to make sure that the two faces on the far left and right are detected out of the box?

This is he image that I am having trouble finding all 6 faces on (https://images2.onionstatic.com/onionstudios/6215/original/600.jpg)

Upvotes: 0

Views: 2571

Answers (2)

Alexey Antonenko
Alexey Antonenko

Reputation: 2637

Dlib has a very precise face detector. But it works bad detecting not frontal (like far left) and/or occluded faces (like far right).

Seeta (https://github.com/seetaface/SeetaFaceEngine) works better with those. But it's less precise.

Also I tried retraining Dlib's face detector. And obtained much lower precise than DLIB and less recall than Seeta. So, re-training DLIB seems not perfect idea.

Upvotes: 2

Gautham Velchuru
Gautham Velchuru

Reputation: 75

In my experience, Dlib does not do very well out of the box with obscured and profile faces out of the box. I would recommend training Dlib with more data of this kind.

Upvotes: 0

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