KNNClassifier for face detection data format issue

Versions

river version: river==0.13.0 Python version: 3.8 Operating system: Ubuntu 20.04

Describe the bug

I’m trying to train and predict face detection using KNNClassifier

Steps/code to reproduce

Here is the training code.

import math
import pickle

import pandas as pd
from river import neighbors
from river import preprocessing
from river import compose
import os
import face_recognition
from face_recognition.face_recognition_cli import image_files_in_folder


def train(train_dir, model_save_path=None, n_neighbors=None, verbose=False):
    X = []
    y = []
    # Loop through each person in the training set
    for class_dir in os.listdir(train_dir):
        if not os.path.isdir(os.path.join(train_dir, class_dir)):
            continue

        # Loop through each training image for the current person
        for img_path in image_files_in_folder(os.path.join(train_dir, class_dir)):
            image = face_recognition.load_image_file(img_path)
            face_bounding_boxes = face_recognition.face_locations(image)
            # face_bounding_boxes = face_recognition.face_locations(image, number_of_times_to_upsample=2, model="cnn")

            if len(face_bounding_boxes) != 1:
                # If there are no people (or too many people) in a training image, skip the image.
                if verbose:
                    print("Image {} not suitable for training: {}".format(img_path, "Didn't find a face" if len(
                        face_bounding_boxes) < 1 else "Found more than one face"))
            else:
                # Add face encoding for current image to the training set
                # X.append(face_recognition.face_encodings(image, known_face_locations=face_bounding_boxes, num_jitters=100)[0])
                X.append(face_recognition.face_encodings(image, known_face_locations=face_bounding_boxes)[0])
                y.append(class_dir)

    if n_neighbors is None:
        n_neighbors = int(round(math.sqrt(len(X))))
        if verbose:
            print("Chose n_neighbors automatically:", n_neighbors)

    model = neighbors.KNNClassifier(n_neighbors=n_neighbors)
    # xdf = pd.DataFrame(X)
    # ydf = pd.Series(y)
    for encoding, name in zip(X, y):
        model.learn_one({"body": encoding.tolist()}, name)
    # model.learn_many(xdf, ydf)

    if model_save_path is not None:
        with open(model_save_path, 'wb') as f:
            pickle.dump(model, f)


if __name__ == "__main__":
    # STEP 1: Train the KNN classifier and save it to disk
    # Once the model is trained and saved, you can skip this step next time.
    print("Training KNN classifier...")
    train("corpus/train", model_save_path="models/trained_knn_model.clf", n_neighbors=2)
    print("Training complete!")

I have trained a model without any errors but when I tried to predict the face it throws the following error.

import face_recognition
import river
import pickle


def prediction(image):
    with open("models/trained_knn_model.clf", 'rb') as f:
        model = pickle.load(f)
    X_img = face_recognition.load_image_file(image)
    X_face_locations = face_recognition.face_locations(X_img)
    faces_encodings = face_recognition.face_encodings(X_img, known_face_locations=X_face_locations)
    print(model.predict_one({"body": faces_encodings[0].tolist()}))


if __name__ == "__main__":
    # STEP 1: Train the KNN classifier and save it to disk
    # Once the model is trained and saved, you can skip this step next time.
    print("Predicting ....")
    prediction("corpus/train/user_1/User 1.1.jpg")

error:

Predicting ....
Traceback (most recent call last):
  File "/home/iffi/PycharmProjects/FaceDetectionVerification/pred.py", line 19, in <module>
    prediction("corpus/train/user_1/User 1.1.jpg")
  File "/home/iffi/PycharmProjects/FaceDetectionVerification/pred.py", line 12, in prediction
    print(model.predict_one({"body": faces_encodings[0].tolist()}))
  File "/home/iffi/environments/FaceDetectionVerification/lib/python3.8/site-packages/river/base/classifier.py", line 68, in predict_one
    y_pred = self.predict_proba_one(x)
  File "/home/iffi/environments/FaceDetectionVerification/lib/python3.8/site-packages/river/neighbors/knn_classifier.py", line 150, in predict_proba_one
    nearest = self._nn.find_nearest((x, None), n_neighbors=self.n_neighbors)
  File "/home/iffi/environments/FaceDetectionVerification/lib/python3.8/site-packages/river/neighbors/base.py", line 142, in find_nearest
    return sorted(points, key=operator.itemgetter(-1))[:n_neighbors]
  File "/home/iffi/environments/FaceDetectionVerification/lib/python3.8/site-packages/river/neighbors/base.py", line 139, in <genexpr>
    points = ((*p, self.distance_func(item, p[0])) for p in self.window)
  File "/home/iffi/environments/FaceDetectionVerification/lib/python3.8/site-packages/river/neighbors/base.py", line 31, in __call__
    return self.distance_function(a[0], b[0])
  File "/home/iffi/environments/FaceDetectionVerification/lib/python3.8/site-packages/river/utils/math.py", line 163, in minkowski_distance
    return sum((abs(a.get(k, 0.0) - b.get(k, 0.0))) ** p for k in set([*a.keys(), *b.keys()]))
  File "/home/iffi/environments/FaceDetectionVerification/lib/python3.8/site-packages/river/utils/math.py", line 163, in <genexpr>
    return sum((abs(a.get(k, 0.0) - b.get(k, 0.0))) ** p for k in set([*a.keys(), *b.keys()]))
TypeError: unsupported operand type(s) for -: 'list' and 'list'

[mirfan899]

thanks it worked.

[mirfan899]

Okay, I will test it.