Comments (2)
Hi Olexander,
The colorspace histogram concatenation model isn’t a good model after testing with different people. It seems to be sensitive with light settings. But you can try adjusting the threshold value to get better prediction. See _threshold_replay in liveness.py. Also I get better result using _print model instead of _replay model.
I’ll try to integrate other models soon. Thanks!
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Hi @richmondu ,
I am currently trying your liveness detection framework but not getting consistent results with replayable videos and hard printed photos. Could you please let me know if you have made further progress with it since your last reply above?
many thanks
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Related Issues (20)
- Unable to run “facial_recognition.py ” HOT 6
- face recognition with liveness detection on pretrained model HOT 1
- Parameters: FaceDetectorModels.MTCNN FaceEncoderModels.OPENFACE FaceClassifierModels.LINEAR_SVM Invalid parameter
- UnboundLocalError: local variable 'face_detector' referenced before assignment
- Import errors HOT 1
- bad performance for age and gender detection HOT 1
- Unknown face HOT 1
- ImportError: cannot import name 'FaceLivenessDetectorModels' HOT 1
- Issue fixed. File updated to use FaceLivenessModels. HOT 1
- Errors trying to run certain examples HOT 1
- File can't be opened for reading! in function 'cv::face::FaceRecognizer::read' HOT 4
- how to use PiCamera
- Invalid parameter - ERROR during training HOT 3
- webcam liveness detction
- issue regarding face id and rectangular box for recognized face
- Recognizing the face by capturing an image from webcam without opencv and detecting issue HOT 1
- LIveness.py is not working in RPI 4B
- testing_webcam.py always returns first person name
- when I want to run testing_webcam_livenessdetection.py It throws "Error, check if models and trained dataset models exists!" HOT 6
- Examples are not working HOT 1
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