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3dreconstruction's Issues

Is it possible to get the real coordinates of the dino?

Since the result of the 3D reconstructed points of dino with essential matrix seems unlikely the real world coordinates, and the steps include assuming P1 = [I 0], I wonder is it possible to get the real coordinates by the code provided here? If not, what else do I require to reconstruct the accurate world coordinates by two images or even more(through sfm)?

How to perform triangulation without intrinsic matrix?

As far as procedure is concerned, if the intrinsic is not available, the fundamental matrix will be calculated. However, recording the examples, all intrinsic matrices are required. May I ask how to use those examples without intrinsic matrices?

FileMissing

when i ran the example.py,an error ocurred

Traceback (most recent call last):
File "/home/ben/PyProjects/3Dreconstruction/example.py", line 9, in
import features
ImportError: No module named 'features'

it seems like the features.py is missing

[BUG] A path bug concerning the image folder

Hello @alyssaq , there is a small bug concerning the image folder. In the README.md, readers are told to put images under imgs/dino, but a better one is imgs/dinos. Otherwise, the path bug would cause the interruption.

The repository is awesome and I have stared it. Thanks a lot!

alueError: shapes (3,3) and (1,1) not aligned: 3 (dim 1) != 1 (dim 0)

Hi, just tried out python3 cube_reconstruction.py and got:

True essential matrix: [[matrix([[0.]]) matrix([[-1.]]) matrix([[0.]])]
 [matrix([[-0.361547]]) matrix([[0.]]) matrix([[-3.14154162]])]
 [matrix([[0.]]) matrix([[3.]]) matrix([[0.]])]]
Computed essential matrix: [[-4.85388477e-05 -1.00000000e+00 -4.21762070e-04]
 [-3.62391216e-01 -3.38325541e-02 -3.14887717e+00]
 [ 1.45616543e-04  3.00000000e+00  1.26528621e-03]]
True fundamental matrix: [[matrix([[0.]]) matrix([[-1.11111111e-05]]) matrix([[0.00166667]])]
 [matrix([[-4.01718887e-06]]) matrix([[0.]]) matrix([[-0.00986923]])]
 [matrix([[0.00060258]]) matrix([[0.01166667]]) matrix([[-0.26961594]])]]
Traceback (most recent call last):
  File "cube_reconstruction.py", line 119, in <module>
    print('Computed fundamental matrix:', (F * true_F[2][2]))
  File "/home/zangetsu/proj/prometheus-core/demo/demo-20-3dreconstruction-flame/3Dreconstruction/venv3/lib/python3.6/site-packages/numpy/matrixlib/defmatrix.py", line 226, in __rmul__
    return N.dot(other, self)
ValueError: shapes (3,3) and (1,1) not aligned: 3 (dim 1) != 1 (dim 0)

more images

Is it possible to use three or more images reconstruct an object?

sample image

The image download site in the sample is closed, where else can I download it?

Current OpenCV version do not support SIFT

Current OpenCV versions do not support SIFT.

python3 example.py

returns

Traceback (most recent call last): File "example.py", line 90, in <module> points1, points2, intrinsic = dino() File "example.py", line 68, in dino pts1, pts2 = features.find_correspondence_points(img1, img2) File "/content/3Dreconstruction/features.py", line 6, in find_correspondence_points sift = cv2.xfeatures2d.SIFT_create() cv2.error: OpenCV(3.4.3) /io/opencv_contrib/modules/xfeatures2d/src/sift.cpp:1207: error: (-213:The function/feature is not implemented) This algorithm is patented and is excluded in this configuration; Set OPENCV_ENABLE_NONFREE CMake option and rebuild the library in function 'create'

NO it(a difference in data points normalization)

in structure.py
def scale_and_translate_points(points): …… x = points[0] y = points[1] center = points.mean(axis=1) # mean of each row cx = x - center[0] # center the points cy = y - center[1] dist = np.sqrt(np.power(cx, 2) + np.power(cy, 2)) scale = np.sqrt(2) / dist.mean()
Here, computation of scale is different from reference http://ece631web.groups.et.byu.net/Lectures/ECEn631%2013%20-%208%20Point%20Algorithm.pdf

I am sorry that I make a mistake

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