Cell 9

train_features = extract_features(train['image']) 

What the code could have been:

# Import Required Libraries
## Import OpenCV for image processing and feature extraction
import cv2
import numpy as np
from typing import List

# Function to extract features from images
def extract_features(image: List[np.ndarray]) -> np.ndarray:
    """
    Extracts features from a list of images.

    Args:
    image (List[np.ndarray]): A list of image arrays.

    Returns:
    np.ndarray: A numpy array containing the extracted features.
    """
    # Initialize an empty list to store the features
    features = []

    # Loop through each image in the list
    for img in image:
        # Convert the image to grayscale
        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

        # Detect edges using the Canny edge detector
        edges = cv2.Canny(gray, 100, 200)

        # Extract the features using the Histogram of Oriented Gradients (HOG)
        hog = cv2.HOGDescriptor()
        hog_features = hog.compute(edges)

        # Append the features to the list
        features.append(hog_features)

    # Convert the list to a numpy array
    features = np.array(features)

    return features

# Extract features from the training images
train_features = extract_features(train['image'])