Improve example script

Minimal example of

- extracting features from an image and saving them in a file

- flattening the features

- detecting edges in an image and saving the edge image

- resizing the image and saving its features in a file

"""

import numpy as np

from skimage.io import imread # requirement: pip install scikit-image

from PIL import Image

import cv2 # requirement: pip install opencv-python

import cv2

from skimage.io import imread

# Read image from file

image = imread("../figures/banana.jpg", as_gray=False)

print("Shape of image: ", image.shape)

image = imread("../figures/examples_from_dataset/banana.jpg", as_gray=False)

print("Shape of original image: ", image.shape)

# Save features in file

with open('features-banana.txt', 'w') as f:

    f.write(str(image))

# Flatten feature array

features = np.reshape(image, (image.shape[0] * image.shape[1] * image.shape[2]))

features = image.flatten()

#features = np.reshape(image, (image.shape[0] * image.shape[1] * image.shape[2])) # Alternative to flatten

print("Shape of features after flattening: ", features.shape)

with open('features-banana-flattened.txt', 'w') as f:

    f.write(str(features))

print("Original features saved in file 'features-banana.txt'")

print("Flattened features saved in file 'features-banana-flattened.txt'\n")

# Resizing image to 50x50

image_resized = cv2.resize(image, (50, 50))

# Save features in file

with open('features-banana-resized.txt', 'w') as f:

    f.write(str(image_resized))

print("Shape of resized image: ", image_resized.shape)

# Flatten feature array of resized image

features_resized = image_resized.flatten()

with open('features-banana-resized-flattened.txt', 'w') as f:

    f.write(str(features_resized))

print("Shape of resized image after flattening: ", features_resized.shape)

print("Flattened features of resized image saved in file 'features-banana-resized-flattened.txt'")

print("Features saved in file 'features-banana-resized.txt'")

# Detect edges

img = Image.open("../figures/banana.jpg")

img = np.array(img)

edge_img = cv2.Canny(img, threshold1=50, threshold2=80)

#cv2.imshow("Edge Image", edge_img)

#cv2.waitKey(0)

# Save image

cv2.imwrite('../figures/banana-edges.jpg', edge_img)