Improve faceness measure #59
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This was previously incorrectly calculated. The results for this are looking much more promising now. The method of calculation is more in-line with what was originally proposed: > As for your question about adapting the Viola-Jones face detector to return a measure of face-likeness - I think one simple thing you could use is the number of features computed before terminating from the cascade. Face patches always make it to the end of the cascade, i.e. all Haar-like features are computed. Non-faces usually result in early termination from the cascade, and the earlier, the less face-like the patch is (roughly speaking). This certainly would not be a perfect measure, but I'm confident that there is a positive correlation between the total number of features computed in the cascade and the "face-likeness".
Setting these environment variables in the main module file ([`FaceDetection.jl`](src/FaceDetecton.jl)) doesn't do anything to the environment for some reason. Various functions in Adaboost will pull from the environment, defaulting to `"true"`. If you need to turn off warnings and logging in the training phase, you can set these to `"false"` in your scripts.
As `get_score` no longer returns `faceness` (error in calculation; see 3a17220), it does not make sense to calculate the faceness of an image using a single feature, so we have ensured this is not implemented. We have changed the tests accordingly. You should use the other method of `get_faceness`, which calculates the faceness given potentially many classifiers.
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