def runEighPoint(im1, im2, pts1, pts2, M):
F = eightpoint(pts1, pts2, M)
try:
hp.displayEpipolarF(im1, im2, F)
except Exception:
pass
np.savez('../results/files/q2_1.npz', F=F, M=M)
def testEightPoint():
im1 = cv2.imread('../data/im1.png')
im2 = cv2.imread('../data/im2.png')
pts = np.load('../data/some_corresp.npz')
pts1 = pts["pts1"]
pts2 = pts["pts2"]
M = max((im1.shape[0], im1.shape[1]))
F = eightpoint(pts1, pts2, M)
from helper import displayEpipolarF
displayEpipolarF(im1, im2, F)
np.savez('q2_1.npz', F=F, M=M)
def runRansac(pts1noisy, pts2noisy, M, im1, im2):
F = eightpoint(pts1noisy, pts2noisy, M)
F_ransac, _ = ransacF(pts1noisy, pts2noisy, M)
try:
hp.displayEpipolarF(im1, im2, F)
except Exception:
pass
try:
hp.displayEpipolarF(im1, im2, F_ransac)
except Exception:
pass
def q5_1(I1, I2, M):
with np.load("../data/some_corresp_noisy.npz") as data:
pts1 = data['pts1']
pts2 = data['pts2']
inliers = len(pts1)
# F = eightpoint(pts1, pts2, M)
F, inliers = ransacF(pts1=pts1, pts2=pts2, M=M, nIters=200, tol=4.5)
print(f"F:\n{F} matched {np.sum(inliers)}/{len(pts1)} points")
I1 = I1[::, ::, ::-1]
I2 = I2[::, ::, ::-1]
displayEpipolarF(I1, I2, F)
def runSevenPoint(im1, im2, pts1, pts2, M):
dist = np.power(np.subtract(pts1[:, 0], pts2[:, 0]), 2) + np.power(
np.subtract(pts1[:, 1], pts2[:, 1]), 2)
points = dist.argsort()[:7]
pts1_temp = pts1[points, :]
pts2_temp = pts2[points, :]
Farray = sevenpoint(pts1, pts2, M)
for i in range(0, Farray.shape[2]):
F = Farray[:, :, i]
try:
hp.displayEpipolarF(im1, im2, F)
except Exception:
continue
# saving the best F
np.savez('../results/files/q2_2.npz',
F=Farray[:, :, 0],
M=M,
pts1=pts1_temp,
pts2=pts2_temp)
def q2_1(I1, I2, M):
# Find the fundamental matrix
with np.load("../data/some_corresp.npz") as data:
pts1 = data['pts1']
pts2 = data['pts2']
F = eightpoint(pts1=pts1, pts2=pts2, M=M)
# np.savez(q2_1_file, F=F, M=M)
# sanity check
with np.load(q2_1_file) as data:
F = data['F']
assert F.shape == (3, 3), f"F shape is {F.shape} instead of (3, 3)"
M = data['M']
print(f"F:\n{F}\nM:{M}")
# Display epipolar lines
I1 = I1[::, ::, ::-1]
I2 = I2[::, ::, ::-1]
displayEpipolarF(I1, I2, F)
def testSevenPoint():
im1 = cv2.imread('../data/im1.png')
im2 = cv2.imread('../data/im2.png')
pts = np.load('../data/some_corresp.npz')
indexes = [0, 1, 17, 19, 58, 91, 109]
# 157 231
# 309 284
# 132 329
# 474 384
# 62 154
# 425 223
# 236 159
pts1 = pts["pts1"][indexes]
pts2 = pts["pts2"][indexes]
M = max((im1.shape[0], im1.shape[1]))
Farray = sevenpoint(pts1, pts2, M)
F = Farray[0]
print(F)
from helper import displayEpipolarF
displayEpipolarF(im1, im2, F)
np.savez('q2_2.npz', F=F, M=M, pts1=pts1, pts2=pts2)
import helper
import numpy as np
import submission
import matplotlib.pyplot as plt
img1 = plt.imread("../data/im1.png")
img2 = plt.imread("../data/im2.png")
h, w, c = img1.shape
points = np.load("../data/some_corresp.npz")
p1 = points['pts1']
p2 = points['pts2']
M = max(h, w)
F = submission.sevenpoint(p1, p2, M)
print(F.shape)
helper.displayEpipolarF(img1, img2, F)
pts1 = pts[a[0]]
pts2 = pts[a[1]]
image1 = cv2.imread(
'/home/geekerlink/Desktop/Computer Vision/Homeworks/hw4/hw4/data/im1.png'
)
image2 = cv2.imread(
'/home/geekerlink/Desktop/Computer Vision/Homeworks/hw4/hw4/data/im2.png'
)
im_width = image1.shape[1]
im_height = image1.shape[0]
#calculating the scaling factor
M = max(im_height, im_width)
M = float(M)
#calculating the fundamental matrix
F = submission.eightpoint(pts1, pts2, M)
helper.displayEpipolarF(image1, image2, F)
#seven point algorithm
F_seven_temp = submission.sevenpoint(pts1, pts2, M)
errorvalue = []
for i in range(0, 3):
least_error = np.sum(np.square(np.subtract(F, F_seven_temp[i])))
errorvalue.append(least_error)
error_index = np.argmin(errorvalue)
F_seven = F_seven_temp[error_index]
helper.displayEpipolarF(image1, image2, F_seven)
#intrinsic parameters
intrinsic = np.load(
'/home/geekerlink/Desktop/Computer Vision/Homeworks/hw4/hw4/data/intrinsics.npz'
)
b = intrinsic.files
k1 = intrinsic[b[0]]
import numpy as np
import cv2
from helper import displayEpipolarF
from submission import eightpoint, ransacF
im1 = cv2.imread('../data/im1.png')[:, :, ::-1]
im2 = cv2.imread('../data/im2.png')[:, :, ::-1]
corresp = np.load('../data/some_corresp_noisy.npz')
pts1 = corresp['pts1']
pts2 = corresp['pts2']
M = np.max(im1.shape)
print('======no RANSAC=======')
F1 = eightpoint(pts1, pts2, M)
print(F1)
displayEpipolarF(im1, im2, F1)
print('======RANSAC=======')
F2, _ = ransacF(pts1, pts2, M)
print(F2)
displayEpipolarF(im1, im2, F2)
"""
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import submission as sub
import helper
data = np.load('../data/some_corresp.npz')
im1 = plt.imread('../data/im1.png')
im2 = plt.imread('../data/im2.png')
N = data['pts1'].shape[0]
M = 640
# 2.1
F8 = sub.eightpoint(data['pts1'], data['pts2'], M)
helper.displayEpipolarF(im1, im2, F8)
np.savez('q2_1.npz', F=F8, M=M)
# 2.2
pts1 = np.array([[256,270],[162,152],[199,127],[147,131],[381,236],[193,290],[157,231]])
pts2 = np.array([[257,266],[161,151],[197,135],[146,133],[380,215],[194,284],[157,211]])
Farray = sub.sevenpoint(pts1, pts2, M)
helper.displayEpipolarF(im1, im2, Farray[1])
np.savez('q2_2.npz', F=Farray[1], M=M, pts1=pts1, pts2=pts2)
# 3.1
intrinsic = np.load('../data/intrinsics.npz')
K1, K2 = intrinsic['K1'], intrinsic['K2']
E = sub.essentialMatrix(F8, K1, K2)
print(E)
# print('win2 shape',win2.shape)
dist_tmp = np.sum((win2-win1)**2 * weight)
if dist_tmp < dist:
dist = dist_tmp
x2_ans = x2[i]
y2_ans = y2[i]
return x2_ans, y2_ans
'''
Q6.1 Multi-View Reconstruction of keypoints.
Input: C1, the 3x4 camera matrix
pts1, the Nx3 matrix with the 2D image coordinates and confidence per row
C2, the 3x4 camera matrix
pts2, the Nx3 matrix with the 2D image coordinates and confidence per row
C3, the 3x4 camera matrix
pts3, the Nx3 matrix with the 2D image coordinates and confidence per row
Output: P, the Nx3 matrix with the corresponding 3D points for each keypoint per row
err, the reprojection error.
'''
def MultiviewReconstruction(C1, pts1, C2, pts2, C3, pts3, Thres):
# Replace pass by your implementation
pass
if __name__ == '__main__':
image1 = np.load('../data/img1.png')
image2 = np.load('../data/img2.png')
F = eightpoint()
displayEpipolarF(image1,image2,F)
# roots=np.roots([a0,a1,a2,a3])
# roots=np.real(roots)
# print('roots=',roots)
#
# T = np.array([[1/M, 0, 0],
# [0, 1/M, 0],
# [0, 0, 1]])
# Farray=np.zeros([3,3,len(roots)])
# for i in range(len(roots)):
# F=roots[i] * F1 + (1 - roots[i]) * F2
# # [U1, S1, V1] = np.linalg.svd(F)
# # S1[2]=0
# # F = np.dot(U1,np.diag(S1)).dot(V1)
# F=np.dot(np.transpose(T), F).dot(T)
# Farray[:,:,i]=F
# np.savez('../data/q2_2.npz', F=F, M=M, pts1=pts1,pts2=pts2)
# return Farray
if __name__ == '__main__':
data = np.load('../data/some_corresp.npz')
im1 = plt.imread('../data/im1.png')
im2 = plt.imread('../data/im2.png')
N = data['pts1'].shape[0] # N=110
M = 640
pts1 = data['pts1']
pts2 = data['pts2']
Farray = sub.sevenpoint(pts1[7:14, :], pts2[7:14, :], M)
print('F=', Farray[:, :, 2])
helper.displayEpipolarF(im1, im2, Farray[:, :, 2])
pts2 = corresp['pts2']
# select 7 points
N = pts1.shape[0]
select_ids = [53, 17, 43, 46, 27, 56, 77]
pts1 = pts1[select_ids, :].copy()
pts2 = pts2[select_ids, :].copy()
M = np.max(im1.shape)
Farray = sevenpoint(pts1, pts2, M)
for idx, F in enumerate(Farray):
print('visualizing F%d' % idx)
print(F)
displayEpipolarF(im1, im2, F)
print('Enter the id of F which is correct:')
correct_id = int(input())
assert 0 <= correct_id < len(Farray)
F_correct = Farray[correct_id]
np.savez('q2_2.npz', F=F_correct, M=M, pts1=pts1, pts2=pts2)
'''
visualizing F0
[[ 1.37155686e-08 -8.61003099e-08 -8.27427609e-04]
[ 2.16183531e-07 1.90452142e-09 -2.92701083e-05]
[ 7.89066675e-04 1.84620407e-05 3.37863104e-03]]
visualizing F1
[[-1.48732736e-07 2.26439993e-06 -2.62220314e-04]
[-1.97195996e-06 -2.63484236e-06 2.05684451e-03]
[ 3.33774809e-04 -8.47499098e-04 -1.28974831e-01]]
M = np.max(I1.shape)
data = np.load("../data/some_corresp.npz")
pts1 = data['pts1']
pts2 = data['pts2']
data = np.load("../data/templeCoords.npz")
x1 = data['x1']
y1 = data['y1']
F = eightpoint(pts1, pts2, M)
np.savez_compressed('./q2_1.npz', F=F, M=M)
helper.displayEpipolarF(I1, I2, F)
bestF, Farray_best, points1, points2 = BestFSevenPoints(pts1, pts2, M)
np.savez_compressed('./q2_2.npz', F=bestF, M=M, pts1=points1, pts2=points2)
helper.displayEpipolarF(I1, I2, bestF)
E = essentialMatrix(F, K1, K2)
Ms = helper.camera2(E)
M2, M1, C2, C1, Points = findM2_function(K1, K2, Ms, pts1, pts2)
np.savez_compressed('./q3_3.npz', M2=M2, C2=C2, P=Points)
#5.1
pts = np.load('../data/some_corresp_noisy.npz')
pts1 = pts["pts1"]
pts2 = pts["pts2"]
im1 = plt.imread('../data/im1.png')
im2 = plt.imread('../data/im2.png')
M = np.max(np.shape(im1))
# F = eightpoint(pts1, pts2, M)
nIters = 200
tol = 0.002
args = []
args.append((pts1, pts2, M, nIters, tol))
p = Pool()
F = p.map(ransacF, args)
F = np.array(F).reshape(3, 3)
p.close()
p.join()
# F, inliers = ransacF(pts1, pts2, M)
print("F = ", F)
intrinsics = np.load('../data/intrinsics.npz')
K1 = intrinsics["K1"]
K2 = intrinsics["K2"]
E = essentialMatrix(F, K1, K2)
print("E = ", E)
helper.displayEpipolarF(im1, im2, F)
import numpy as np
import matplotlib.pyplot as plt
import submission as sub
import helper as hp
data = np.load('../data/some_corresp.npz')
im1 = plt.imread('../data/im1.png')
im2 = plt.imread('../data/im2.png')
K_matrices = np.load('../data/intrinsics.npz')
N = data['pts1'].shape[0]
M = 640
# 2.1
#F8 = sub.eightpoint(data['pts1'], data['pts2'], M)
#hp.displayEpipolarF(im1,im2,F8)
#F = F8
#2.2
F7 = sub.sevenpoint(data['pts1'][21:28, :], data['pts2'][21:28, :], M)
hp.displayEpipolarF(im1, im2, F7)
E = sub.essentialMatrix(F, K_matrices['K1'], K_matrices['K2'])
