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| import numpy as np | |
| import h5py | |
| import cv2 | |
| def normalize_intrinsic(x,K): | |
| #print(x,K) | |
| return (x-K[:2,2])/np.diag(K)[:2] | |
| def normalize_size(x,size,scale=1): | |
| size=size.reshape([1,2]) | |
| norm_fac=size.max() | |
| return (x-size/2+0.5)/(norm_fac*scale) | |
| def np_skew_symmetric(v): | |
| zero = np.zeros_like(v[:, 0]) | |
| M = np.stack([ | |
| zero, -v[:, 2], v[:, 1], | |
| v[:, 2], zero, -v[:, 0], | |
| -v[:, 1], v[:, 0], zero, | |
| ], axis=1) | |
| return M | |
| 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 |