1e619d91956c813d2328a5460da0a273fe135905,hook/zmes_hook_helpers/face.py,Face,detect,#Face#,123

Before Change

            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"]:

After Change

        face_encodings = face_recognition.face_encodings(rgb_image, known_face_locations=face_locations, num_jitters=self.num_jitters)

        // 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 = []

        for pred, loc, rec in zip(self.knn.predict(face_encodings), face_locations, are_matches):
            label = pred if rec else g.config["unknown_face_name"]
            matched_face_rects.append((loc[3], loc[0], loc[1], loc[2]))
            matched_face_names.append(label)
            conf.append(1)

        return matched_face_rects, matched_face_names, conf

Instances