add camera inspector

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Kai-46 2020-11-13 19:43:50 -05:00
parent 2b00fbfef5
commit d893b217ef
6 changed files with 9581 additions and 0 deletions

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@ -75,3 +75,10 @@ Check `camera_visualizer/visualize_cameras.py` for visualizing cameras in 3D. It
<img src="camera_visualizer/screenshot_lowres.png" width="280">
## Inspect camera parameters
You can use `camera_inspector/inspect_epipolar_geometry.py` to inspect if the camera paramters are correct and follow the Opencv convention assumed by this codebase. The script creates a viewer for visually inspecting epipolar geometry like below: for key points in the top image, it plots their correspoinding epipolar lines in the bottom image. If the epipolar geometry does not look correct in this visualization, it's likely that there are some issues with the camera parameters.
<img src="camera_inspector/screenshot.png" width="280">

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@ -0,0 +1,80 @@
import cv2
import numpy as np
import os
import json
def skew(x):
return np.array([[0, -x[2], x[1]],
[x[2], 0, -x[0]],
[-x[1], x[0], 0]])
def two_view_geometry(intrinsics1, extrinsics1, intrinsics2, extrinsics2):
relative_pose = extrinsics2.dot(np.linalg.inv(extrinsics1))
R = relative_pose[:3, :3]
T = relative_pose[:3, 3]
tx = skew(T)
E = np.dot(tx, R)
F = np.linalg.inv(intrinsics2[:3, :3]).T.dot(E).dot(np.linalg.inv(intrinsics1[:3, :3]))
return E, F, relative_pose
def drawpointslines(img1, pts1, img2, lines2, colors):
h, w = img2.shape[:2]
# img1 = cv2.cvtColor(img1, cv2.COLOR_GRAY2BGR)
# img2 = cv2.cvtColor(img2, cv2.COLOR_GRAY2BGR)
print(pts1.shape, lines2.shape, colors.shape)
for p, l, c in zip(pts1, lines2, colors):
c = tuple(c.tolist())
img1 = cv2.circle(img1, tuple(p), 5, c, -1)
x0, y0 = map(int, [0, -l[2]/l[1]])
x1, y1 = map(int, [w, -(l[2]+l[0]*w)/l[1]])
img2 = cv2.line(img2, (x0, y0), (x1, y1), c, 1, lineType=cv2.LINE_AA)
return img1, img2
def inspect(img1, K1, W2C1, img2, K2, W2C2):
E, F, relative_pose = two_view_geometry(K1, W2C1, K2, W2C2)
orb = cv2.ORB_create()
kp1 = orb.detect(cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY), None)[:20]
pts1 = np.array([[int(kp.pt[0]), int(kp.pt[1])] for kp in kp1])
lines2 = cv2.computeCorrespondEpilines(pts1.reshape(-1,1,2), 1, F)
lines2 = lines2.reshape(-1, 3)
colors = np.random.randint(0, high=255, size=(len(pts1), 3))
img1, img2 = drawpointslines(img1, pts1, img2, lines2, colors)
im_to_show = np.concatenate((img1, img2), axis=0)
# down sample
h, w = im_to_show.shape[:2]
im_to_show = cv2.resize(im_to_show, (int(0.5*w), int(0.5*h)), interpolation=cv2.INTER_AREA)
cv2.imshow('epipolar geometry', im_to_show)
cv2.waitKey(0)
cv2.destroyAllWindows()
if __name__ == '__main__':
base_dir = './'
img_dir = os.path.join(base_dir, 'train/rgb')
cam_dict_file = os.path.join(base_dir, 'train/cam_dict_norm.json')
img_name1 = '000001.png'
img_name2 = '000005.png'
cam_dict = json.load(open(cam_dict_file))
img1 = cv2.imread(os.path.join(img_dir, img_name1))
K1 = np.array(cam_dict[img_name1]['K']).reshape((4, 4))
W2C1 = np.array(cam_dict[img_name1]['W2C']).reshape((4, 4))
img2 = cv2.imread(os.path.join(img_dir, img_name2))
K2 = np.array(cam_dict[img_name2]['K']).reshape((4, 4))
W2C2 = np.array(cam_dict[img_name2]['W2C']).reshape((4, 4))
inspect(img1, K1, W2C1, img2, K2, W2C2)

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