Cacher is the code snippet organizer for pro developers

import numpy as np
import cv2
from matplotlib import pyplot as plt

def draw_matches(img1, kp1, img2, kp2, matches, color=None): 
    	
    if len(img1.shape) == 3:
        new_shape = (max(img1.shape[0], img2.shape[0]), img1.shape[1]+img2.shape[1], img1.shape[2])
    elif len(img1.shape) == 2:
        new_shape = (max(img1.shape[0], img2.shape[0]), img1.shape[1]+img2.shape[1])
    new_img = np.zeros(new_shape, type(img1.flat[0]))  
    # Place images onto the new image.
    new_img[0:img1.shape[0],0:img1.shape[1]] = img1
    new_img[0:img2.shape[0],img1.shape[1]:img1.shape[1]+img2.shape[1]] = img2
    
    # Draw lines between matches.  Make sure to offset kp coords in second image appropriately.
    r = 15
    thickness = 2
    if color:
        c = color
    for m in matches:
        # Generate random color for RGB/BGR and grayscale images as needed.
        if not color: 
            c = np.random.randint(0,256,3) if len(img1.shape) == 3 else np.random.randint(0,256)
        # So the keypoint locs are stored as a tuple of floats.  cv2.line(), like most other things,
        # wants locs as a tuple of ints.
        end1 = tuple(np.round(kp1[m.trainIdx].pt).astype(int))
        end2 = tuple(np.round(kp2[m.queryIdx].pt).astype(int) + np.array([img1.shape[1], 0]))
        cv2.line(new_img, end1, end2, c, thickness)
        cv2.circle(new_img, end1, r, c, thickness)
        cv2.circle(new_img, end2, r, c, thickness)
    
    plt.figure(figsize=(15,15))
    plt.imshow(new_img)
    plt.show()



img1 = cv2.imread('img/krave.jpg',0)          # queryImage
img2 = cv2.imread('img/krave_scene.jpg',0) # trainImage

# Initiate SIFT detector
orb = cv2.ORB()

# find the keypoints and descriptors with SIFT
kp1, des1 = orb.detectAndCompute(img1,None)
kp2, des2 = orb.detectAndCompute(img2,None)


# create BFMatcher object
bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True)

# Match descriptors.
matches = bf.match(des1,des2)

# Sort them in the order of their distance.
matches = sorted(matches, key = lambda x:x.distance)

# Draw first 10 matches.
#img3 = cv2.drawMatches(img1,kp1,img2,kp2,matches[:10], flags=2)
img3 = draw_matches(img1,kp1,img2,kp2,matches)

plt.imshow(img3),plt.show()