Assignment: EM Algorithm

For Noisy Image Reconstruction

📅 Deadline: 8.1.2026 21:59

🏦 Points: 5

Task Description

In this assignment, you are tasked with implementing the EM algorithm for image reconstruction from a sequence of shifted noisy images. You can find the complete description of the assignment in the Assignment .

You are provided with a template containing the following files:

  • main.py: This file includes the functions that you are required to implement.
  • utils.py: Contains helper functions for loading and saving data. You do not need to modify this file.
  • test-cases: A folder containing public test cases to help you verify your implementation before submitting to BRUTE.
All python files must be stored in the root of the .zip sent for submission.
The expected runtime of the evaluation is about 2 minutes.

Go make yourself a coffee while you wait.

How to Test

After completing your implementation, you can test your solution using the following commands before submitting it to BRUTE:


Test Case 1
python main.py test-cases/public/instances/instance_1.npz

—-

Test Case 2
python main.py test-cases/public/instances/instance_2.npz    

—-

Test Case 3
python main.py test-cases/public/instances/instance_3.npz

—-

Test Case 4
python main.py test-cases/public/instances/instance_4.npz

Submission Guidelines

  • Submit the completed code as a .zip via BRUTE.
  • All python files must be stored in the root of the .zip sent for submission.
  • Make sure your implementation passes the test cases provided above. Good luck! 😊
courses/be4m33ssu/homeworks/hw_em_prior_shift.txt · Last modified: 2025/12/11 10:02 by paplhjak