From c058386fe438334cd40308b2c594afcff24bb08f Mon Sep 17 00:00:00 2001 From: jackie840129 Date: Wed, 4 Jul 2018 23:39:49 +0800 Subject: [PATCH] add readme --- Lab_2/Readme.md | 8 +++++--- Readme.md | 2 +- 2 files changed, 6 insertions(+), 4 deletions(-) diff --git a/Lab_2/Readme.md b/Lab_2/Readme.md index db27ace..48c9f09 100644 --- a/Lab_2/Readme.md +++ b/Lab_2/Readme.md @@ -1,6 +1,6 @@ # Lab_2 -This is the simplified version of DLCV course HW2. +This is the simplified version of NTU Deep Learning for Computer Vision (DLCV) course HW2. **What you will learn :** - Color Segmentation @@ -11,8 +11,10 @@ This is the simplified version of DLCV course HW2. **Directory Tree** ``` -|__Lab1 +|__Lab2 | |__ Readme.md +| |__ train-100/ +| |__ test-100/ | |__ image/ | |__ filterBank.mat | |__ mountain.jpg @@ -107,7 +109,7 @@ for simplicity). The centroid of each cluster then indicates a visual word. Now compute BoW of training images in Train-100 with the saved "visual_words.npy", resulting in a 500×50 matrix. Choose one image from each category (5 category) and plot their **Hard-Sum**, **Soft-Sum**, and **Soft-Max**, respectively. Can you expect which BoW strategy results in better classification results and why? - hs ss sm + hs ss sm 4. ) Finally, We adopt the k-nearest neighbors classifier (**KNN**) to perform classification using the above BoW features. diff --git a/Readme.md b/Readme.md index 8671ebc..86a6fab 100644 --- a/Readme.md +++ b/Readme.md @@ -6,7 +6,7 @@ This Python Opencv Lab is split into two parts for morning and afternoon. 2. [Lab_2/](./Lab_2) : Color and Texture Segmentation (Clustering) , Recognition with Bag of Visual Words ### Reference -The lab practice referred to [OpenCVtutorial](http://opencv-python-tutroals.readthedocs.io/en/latest/index.html) and NTU DLCV course [website](http://vllab.ee.ntu.edu.tw/dlcv.html). +The lab practice referred to [OpenCVtutorial](http://opencv-python-tutroals.readthedocs.io/en/latest/index.html) and NTU Deep Learning for Computer Vision (DLCV) course [website](http://vllab.ee.ntu.edu.tw/dlcv.html). ### Prerequisites - python3.5+