import cv2 import numpy as np def resize(image,long_dim): h,w=image.shape[0],image.shape[1] image=cv2.resize(image,(int(w*long_dim/max(h,w)),int(h*long_dim/max(h,w)))) return image def draw_points(img,points,color=(0,255,0),radius=3): dp = [(int(points[i, 0]), int(points[i, 1])) for i in range(points.shape[0])] for i in range(points.shape[0]): cv2.circle(img, dp[i],radius=radius,color=color) return img def draw_match(img1, img2, corr1, corr2,inlier=[True],color=None,radius1=1,radius2=1,resize=None): if resize is not None: scale1,scale2=[img1.shape[1]/resize[0],img1.shape[0]/resize[1]],[img2.shape[1]/resize[0],img2.shape[0]/resize[1]] img1,img2=cv2.resize(img1, resize, interpolation=cv2.INTER_AREA),cv2.resize(img2, resize, interpolation=cv2.INTER_AREA) corr1,corr2=corr1/np.asarray(scale1)[np.newaxis],corr2/np.asarray(scale2)[np.newaxis] corr1_key = [cv2.KeyPoint(corr1[i, 0], corr1[i, 1], radius1) for i in range(corr1.shape[0])] corr2_key = [cv2.KeyPoint(corr2[i, 0], corr2[i, 1], radius2) for i in range(corr2.shape[0])] assert len(corr1) == len(corr2) draw_matches = [cv2.DMatch(i, i, 0) for i in range(len(corr1))] if color is None: color = [(0, 255, 0) if cur_inlier else (0,0,255) for cur_inlier in inlier] if len(color)==1: display = cv2.drawMatches(img1, corr1_key, img2, corr2_key, draw_matches, None, matchColor=color[0], singlePointColor=color[0], flags=4 ) else: height,width=max(img1.shape[0],img2.shape[0]),img1.shape[1]+img2.shape[1] display=np.zeros([height,width,3],np.uint8) display[:img1.shape[0],:img1.shape[1]]=img1 display[:img2.shape[0],img1.shape[1]:]=img2 for i in range(len(corr1)): left_x,left_y,right_x,right_y=int(corr1[i][0]),int(corr1[i][1]),int(corr2[i][0]+img1.shape[1]),int(corr2[i][1]) cur_color=(int(color[i][0]),int(color[i][1]),int(color[i][2])) cv2.line(display, (left_x,left_y), (right_x,right_y),cur_color,1,lineType=cv2.LINE_AA) return display