Hetul Patel

@fo40225 Thanks. I will try this.

You can try importing tensorflow like this import tensorflow as tfv2 tf = tfv2.compat.v1 Tensorflow 2.x supports tensorflow 1.x code through tensorflow.compat.v1 module.

You can use linearSVC which is support vector classifier. Implementation is provided by sklearn like one shown here, svm = LinearSVC() clf = CalibratedClassifierCV(svm) clf.fit(arr_embeddings, arr_labels) y_proba = clf.predict_proba( arr_unknown_embeddings...

@sami-soliman I have already proposed a solution for using SVM for face matching at https://github.com/davidsandberg/facenet/issues/791#issuecomment-397163176. Other than svm, I would suggest calculating Euclidean distance between unknown embedding against know embeddings....

@yyoon Thanks for reviewing my PR. First I would like to answer your second question. > 2. Also, please add a comment explaining why the NullPointerException can be thrown and...

You can use a standard normal distribution to calculate the probability associated with any pixel as a function of pixel's distance from the center. ``` import cv2 import numpy as...