Détection de fonctionnalités SURF

# Imports
from matplotlib import pyplot as plt
import cv2 as cv
import numpy as np
import os
import pickle
 
# Open and convert a input
# image from BGR to GRAYSCALE
image = cv.imread(filename = 'Figures/pexels-bestbe-models-2412691.jpg',
                   flags = cv.IMREAD_GRAYSCALE)
 
# SURF is a feature detector and descriptor

# Initiate SURF detector
SURF = cv.xfeatures2d.SURF_create()
 
 # Find the keypoints with SURF
keypoints = SURF.detect(image, None)
 
# Print number of keypoints detected
print("Number of keypoints Detected:", len(keypoints), "\n")
 
# Save Keypoints to a file

index = []
 
for point in keypoints:
    temp = (point.pt,
            point.size,
            point.angle,
            point.response,
            point.octave, 
            point.class_id)
 
    index.append(temp)
 
# File name
filename = "Outputs/SURF-keypoints.txt"
 
# Delete a file if it exists
if os.path.exists(filename):
    os.remove(filename)
 
# Open a file
file = open(filename, "wb")
 
# Write 
file.write(pickle.dumps(index))
 
# Close a file
file.close()
 
# Compute the descriptors with SURF
keypoints, descriptors = SURF.compute(image, keypoints)
 
# Print the descriptor size in bytes
print("Size of Descriptor:", SURF.descriptorSize(), "\n")
 
# Print the descriptor type
print("Type of Descriptor:", SURF.descriptorType(), "\n")
 
# Print the default norm type
print("Default Norm Type:", SURF.defaultNorm(), "\n")
 
# Print shape of descriptor
print("Shape of Descriptor:", descriptors.shape, "\n")
 
# Draw only 50 keypoints on input image
image = cv.drawKeypoints(image = image,
                         keypoints = keypoints[:50],
                         outImage = None,
                         flags = cv.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
 
# Plot input image

# Turn interactive plotting off
plt.ioff()
 
# Create a new figure
plt.figure()
plt.axis('off')
plt.imshow(image)
plt.show()
 
plt.imsave(fname = 'Figures/feature-detection-SURF.jpg',
           arr = image,
           dpi = 300)
 
# Close it
plt.close()