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View Code? Open in Web Editor NEWPython version of GT/Udacity Introduction to Computer Vision quizzes
Python version of GT/Udacity Introduction to Computer Vision quizzes
The edge demo covers the use of canny on Lena and Laplacian of Gaussian
The student version calculates gmag thusly:
gmag = np.sqrt(gx2 + gy2) / (4 * np.sqrt(2))
While the answer uses:
gmag = np.sqrt(gx2 + gy2)
This is causing the gradient to be all zeros
I'm getting this error when trying to run the solution for gradient_quiz.py:
Traceback (most recent call last):
File "CV-lecture-quizzes-python/2A-L5/answers/gradient_quiz.py", line 22, in
cv2.imshow('Image', img) # assumes [0, 1] range for double images
cv2.error: OpenCV(4.0.0) c:\projects\opencv-python\opencv\modules\imgproc\src\color.hpp:261: error: (-2:Unspecified error) in function '__cdecl cv::CvtHelper<struct cv::Set<1,-1,-1>,struct cv::Set<3,4,-1>,struct cv::Set<0,2,5>,2>::CvtHelper(const class cv::_InputArray &,const class cv::_OutputArray &,int)'
> Unsupported depth of input image:
> 'VDepth::contains(depth)'
> where
> 'depth' is 6 (CV_64F)
Really minor, but caught me off guard:
in 3B-L3/match_two_strips.py
, b = 100,
while in 3B-L3/answers/match_two_strips.py
, b = 80
Could you please add one for Load and Display Image?
@pdvelez Would you want someone to contribute the missing gaussian noise method here? https://github.com/pdvelez/CV-lecture-quizzes-python/blob/master/2A-L3/apply_median_filter.py#L21
While I understand that we suppose to build the Hough model by ourselves for one of the PS, it will be good to have a baseline for comparison. Also, since past students using Matlab/Octave have this resource, it makes sense for this python generation to have access to the same baseline materials.
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