https://cw.fel.cvut.cz/b191/ 2026-04-27T02:10:56+0200 https://cw.fel.cvut.cz/b191/ https://cw.fel.cvut.cz/b191/lib/tpl/bulma-cw/images/favicon.ico text/html 2019-10-24T15:48:45+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b191/courses/b3b33vir/tutorials/hw01?rev=1571924925&do=diff HW 01 - Image recognition Your first homework will be Image recognition. For this task, we have created our own dataset, which is based on ImageNet. The homework will be introduced in the labs in the 3rd week, we will try to clear any doubts. Dataset The dataset consists of 10 classes, 500 training images for each class, and 50 testing and 50 validation images for each class. Each image has resolution of $$pts_{individual} = 8\times\text{clip}(\frac{acc - 0.4}{0.55 - 0.4}, 0, 1)$$$$ c = \beg… text/html 2019-10-30T15:40:40+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b191/courses/b3b33vir/tutorials/hw02?rev=1572446440&do=diff HW 02 - Image segmentation Your second homework will be Image segmentation. For this task, we have created our minified version of A2D2 dataset The homework will be introduced in the labs in the 5th week, we will try to clear any doubts Dataset The dataset consists of 3127 training images, 460 testing and 408 validation images. Each image has a resolution of $$pts_{individual} = 8\times\text{clip}(\frac{mIOU - 0.5}{0.6 - 0.5}, 0, 1)$$$$ c = \begin{cases} \text{clip}(\frac{mIOU - 0.6}{\max(mI… text/html 2019-11-25T16:02:02+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b191/courses/b3b33vir/tutorials/start?rev=1574694122&do=diff Labs Schedule datum č.t. S/L náplň Tutoriály Materiály 23.09.2019 1 L Numpy HW0 NumPy & PyTorch tutorial [NumPy Basics] 24.09.2019 25.09.2019 30.09.2019 2 S PyTorch + Autograd Basic PyTorch & Autograd NumPy & PyTorch tutorial [hand-made Optimization] of Rosenbrock function 01.10.2019 02.10.2019 07.10.2019 3 L Pytorch eco-system + Classification