face-landmark | caffe 68 points | Machine Learning library

Select Generic iOS Device while archiving

I find a solution! Thanks to Why does AVSampleBufferDisplayLayer fail with Operation Interrupted (-11847)?

If you had similar problem you need to set AVSampleBufferDisplayLayer each time app entering foreground. Like this:

Shape predictor trained mode file size depends on the count of points model training parameters. Existing model has the size of 98 MB and provide state-of-the-art accuracy of facial points detection. So you have three main ways to solve the problem:

1. some compression/quantization... that will change existing model. I will not help here - there are some answers in the question you are referenced
2. use different model training params. Existing model is trained with the code provided in "train_shape_predictor_ex" example in dlib package, but the training params are little different. simple running this example as-is with the images from example folder will give you model with the size of 15 MB. Yes, this model will be less-accurate, but this is the price of its small size
3. use less landmarks. to make this - use same "train_shape_predictor_ex" example, but remove some landmarks from training/testing dataset