matched_face_rects = []
for idx,face_encoding in enumerate(face_encodings):
preds = self.svm_model.predict_proba([face_encoding])[0]
print (preds, self.svm_model.classes_)
best_pred_ndx = np.argmax(preds)
best_pred = preds[best_pred_ndx]
loc = face_locations[idx]
if best_pred >= g.config["face_recog_min_confidence"]:
matched_face_names.append(self.svm_model.classes_[best_pred_ndx])
After Change
// Use the KNN model to find the best matches for the test face
closest_distances = self.knn.kneighbors(face_encodings, n_neighbors=1)
are_matches = [closest_distances[0][i][0] <= g.config["face_recog_dist_threshold"] for i in range(len(face_locations))]
matched_face_names = []
matched_face_rects = []