Mobile Technologies Web Technologies Digital Marketing Creative Design Career Talk Medical General Tech Interviews Internet Of Things

Embark on a journey of knowledge! Take the quiz and earn valuable credits.

Take A Quiz

Challenge yourself and boost your learning! Start the quiz now to earn credits.

Take A Quiz

Unlock your potential! Begin the quiz, answer questions, and accumulate credits along the way.

Take A Quiz

Popular Categories

Interview Questions
QuestionBank
Quantitative Aptitude
Engineering
Govt Exams
Digital Marketing
Management
Interviews
All

Numpy fastest 3D to 2D projection

General Tech Learning Aids/Tools 2 years ago

0 2 0 0 0 tuteeHUB earn credit +10 pts
5 Star Rating 1 Rating
Previous Next

Posted on 16 Aug 2022, this text provides information on Learning Aids/Tools related to General Tech. Please note that while accuracy is prioritized, the data presented might not be entirely correct or up-to-date. This information is offered for general knowledge and informational purposes only, and should not be considered as a substitute for professional advice.

Take Quiz To Earn Credits!

Turn Your Knowledge into Earnings.

tuteehub_quiz

Answers (2)

Post Answer
profilepic.png
manpreet Tuteehub forum best answer Best Answer 2 years ago

 

I have a 3D array of binary data. I want to project this to 3 2D images - side on, head on, birds eye.

I have written the code:

for x in range(data.shape[2]):
    for y in range(data.shape[0]):
        val = 0
        for z in range(data.shape[1]):
            if data[y][z][x] > 0:
                val = 255
                break
        side[y][x] = val

But this is horrifically slow (75s!) for a ~700x300x300 matrix.

What is the fastest way of achieving this task?

EDIT:

To save the image, I have used:

sideImage = Image.fromarray(side)
sideImage.convert('RGB').save("sideImage.png")
0 views
0 shares
profilepic.png
manpreet 2 years ago

You can compute it as follows:

>>> data = np.random.random_sample((200, 300, 100)) > 0.5
>>> data.any(axis=-1).shape # show the result has the shape we want
(200, 300)
>>> data.any(axis=-1)
array([[ True,  True,  True, ...,  True,  True,  True],
       [ True,  True,  True, ...,  True,  True,  True],
       [ True,  True,  True, ...,  True,  True,  True],
       ...,
       [ True,  True,  True, ...,  True,  True,  True],
       [ True,  True,  True, ...,  True,  True,  True],
       [ True,  True,  True, ...,  True,  True,  True]], dtype=bool)
>>>

You can scale values if you need

>>> data.any(axis=-1) * 255
array([[255, 255, 255, ..., 255, 255, 255],
       [255, 255, 255, ..., 255, 255, 255],
       [255, 255, 255, ..., 255, 255, 255],
       ...,
       [255, 255, 255, ..., 255, 255, 255],
       [255, 255, 255, ..., 255, 255, 255],
       [255, 255, 255, ..., 255, 255, 255
                                                    
                                                    



                                                        

                                                            0
                                                                views   
                                                                0 shares

No matter what stage you're at in your education or career, TuteeHub will help you reach the next level that you're aiming for. Simply,Choose a subject/topic and get started in self-paced practice sessions to improve your knowledge and scores.

Q

What is the full form of NABARD ?

Banking, Finance & Insurance
Q

How to refresh app upon shaking the device?

Mobile Technologies
Q

What are the govt exams after BCA?

Career Talk
Q

TYPO3 v8. Override function in Core class

General Tech
Q

Why do people in India give so much importance to Government jobs?

Commerce & Accounting
Q

<p>What are the best practices for optimizing website performance in 2024?</p>

Web Technologies 0 Answers
Q

How can I know Qibla direction?

General Tech 0 Answers
Q

How to viral my instagram post ?

Digital Marketing 0 Answers
Q

Prepare a slogan against imperialism that exist at present in one form or the other form.. plss fast​

Interview Questions 0 Answers
Q

Des cribe the main features of neolithic culture​

Interview Questions 0 Answers

Explore Other Libraries

Blogs Tutorials Question Bank Feeds Careernews

Related Searches

Numpy fastest 3D 2D projection

Important General Tech Links

 Bugs & Fixes
 Technology & Software
 Learning Aids/Tools
 QA/Testing