====== Labs ======

The labs cover selected image processing methods. For each method, the students are provided with a Jupyter notebook that contains a brief explanation and a template for the implementation. The students are tasked to follow the template and complete the implementation.

Attendance at the labs is **recommended but not mandatory**.

See information about the [[courses:zmo:semestral:start|semester work]].
===== Schedule =====

^ Week ^ Date    ^ Topic                                                                              ^
| 1    | 21.  9. | {{ :courses:zmo:tutorials:01_bsplines.zip | Introduction: B-splines}}              |
| 2    | 28.  9. | //Holiday//                                                                        |
| 3    | 5. 10.  | {{ :courses:zmo:tutorials:02_active_contours.zip | Active contours}}               |
| 4    | 12. 10. | {{ :courses:zmo:tutorials:03_shape_transform.zip | Shape transforms}}              |
| 5    | 19. 10. | //Canceled//                                                                       |
| 6    | 26. 10. | {{ :courses:zmo:tutorials:04_superpixels.zip | Superpixel segmentation }}          |
| 7    | 2. 11.  | {{ :courses:zmo:tutorials:05_graphcut.zip | Graph cut}}                            |
| 8    | 9. 11.  | {{ :courses:zmo:tutorials:06_unet.zip | Deep learning: U-Net}}                     |
| 9    | 16. 11. | Deep learning: U-net //cont.//                                                     |
| 10   | 23. 11. | {{ :courses:zmo:tutorials:08_classification.zip | Deep learning: classification }} |
| 11   | 30. 11. | {{ :courses:zmo:tutorials:09_frangi.zip | Frangi vesselness filter }}              |
| 12   | 7. 12.  | {{ :courses:zmo:tutorials:10_registration.zip | Image registration }}              |
| 13   | 14. 12. |  {{ :courses:zmo:tutorials:11_sitk_registration.zip | Image registration with SimpleITK }}                                                       |
| 14   | 11. 1.  | Semester work: presentation                                                        |


===== Required software =====

Although the students can use the lab computers, they are encouraged to use their own devices, which will allow them to work on the assignments at home. The easiest way to install all required software is through the [[https://conda.io/projects/conda|Conda]] system. Use the [[https://docs.conda.io/en/latest/miniconda.html|Miniconda]] installer to obtain a Conda installation. 

After installing Conda, create a new environment and install the required dependencies:

  conda create -n zmo python=3 jupyter matplotlib numpy

To verify the installation, activate the fresh environment

  conda activate zmo

and check that the following commands exit successfuly:

  python -c "import numpy; import matplotlib"
  jupyter notebook --version

<note important>
It is necessary to activate the Conda environment before using Jupyter, so it is required to run

  conda activate zmo

before working on the assignments.
</note>