Joint-Cascade-Face-Detection-and-Alignment
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does the code lack some functions?
test and train code seems nothing?
I do not implement train and test as functions. But you can find the similar codes in main.cpp.
LBFRegressor.cpp Predict function binfeatures is loss,if use binfeatures = DeriveBinaryFeat2(RandomForest_[stage1], images, image_index, current_shapes, bounding_boxs, result_face, score) ,the parameters number is wrong ,7parameters,but DeriveBinaryFeat2 is 9parameters. What's more, I hope to learn you detection and alignment use how long time! The paper show 30ms ,you receive it ?
- according to LBFRegressor.cpp, line 887. binfeatures=DeriveBinaryFeat2(RandomForest_[stage],images,image_index,current_shapes,bounding_boxs,face,score,fcount,fface);
- This version is used for training. i have another implementation which has been optimized to test, it coulde be faster than the paper by doing some optimizations.
PS: the speed is influenced by the mean number of weak classifiers(reject a negative sample), size of sliding window, offset of sliding, etc. I do not konw these parametesrs of origianl paper.
Oh,I see you have two predict functions in LBFRegressor.cpp.The mistake is founded in vector<Mat_
yes, the one you mentiond never be called. maybe i should delete it.
ok,is LBF6.model and Regressor6.model the same as the code 3000FPS? And the new model is inclde detection and alignment ? dou you have the trained model ?And dou you have a test code link? My Email is [email protected] .If possible ,I hope to have a chance to test the test code ! Thanks very much!
sorry, it is a long time since i finish it, i miss the model file.
you can train one with your dataset.
is LBF6.model and Regressor6.model the same as the code 3000FPS?
i do not remeber, you can veirify it by yourself.