The code is designed to extract features from an image, with a function extract_features(image) responsible for this task. It utilizes a dictionary test containing image data and a variable test_features to store the extracted features.
test_features = extract_features(test['image'])# Main Function
def main():
"""
Test the feature extraction function on the 'test' dataset.
"""
try:
# Extract features from test image
features = extract_features(test['image'])
# Print extracted features
print(features)
except ValueError as e:
# Handle errors
print(f"Error: {e}")
except Exception as e:
# Handle unexpected errors
print(f"An unexpected error occurred: {e}")
# TODO: Implement feature normalization and storage
# TODO: Optimize feature extraction for performanceThe code extracts features from an image.
extract_features(image): a function that takes an image as input and returns its features.test_features: a variable that stores the extracted features from the image.test: a dictionary containing the image to be processed, with 'image' as the key.