This is the implementation of https://github.com/Hanqer/deep-hough-transform on Google Colab. The paper "Deep Hough Transform for Semantic Line Detection" (ECCV 2020, PAMI 2021).

1. Testing of pre-trained model on Google Colab

2. Training on NKL Dataset on Google Colab

3. Training on SEL Dataset on Google Colab

Demo 1

Demo 2

Table Of Contents

> Testing of pre-trained model on Google Colab

> Training on NKL Dataset on Google Colab

> Training on SEL Dataset on Google Colab

Testing of pre-trained model on Google Colab

Click on the following link.

https://colab.research.google.com/github/HassanBinHaroon/deep-hough-transform/blob/main/Hanqer_Deep_Hough_Transform.ipynb

Must Do After Clicking

>>>>> Change runtime type

>>>>> Select GPU

>>>>> Run All

Training on NKL Dataset on Google Colab

Click on the following link.

https://colab.research.google.com/github/HassanBinHaroon/deep-hough-transform/blob/main/Hanqer_Deep_Hough_Transform_Train_NKL.ipynb

Must Do After Clicking

>>>>> Change runtime type

>>>>> Select GPU

>>>>> Run All

Training on SEL Dataset on Google Colab

Click on the following link.

https://colab.research.google.com/github/HassanBinHaroon/deep-hough-transform/blob/main/Hanqer_Deep_Hough_Transform_Train_SEL.ipynb

Must Do After Clicking

>>>>> Change runtime type

>>>>> Select GPU

>>>>> Run Only The First Cell

>>>>> Open the configuration file (config.yaml) in the File section. Note that here we have to do some changes in the configuration file to configure the right paths.

>>>>> Comment-out line no 2-7 and uncomment line no 8-13

>>>>> Run After in the Runtime Tab