Sketch To Code

1. Create Conda env and activate it

conda create --prefix ./env python=3.8

2. Check whether NVIDIA Driver is available or not

nvidia-smi 

3. Download Cuda toolkit with maching the CUDA version you see by doing nvidia-smi

For our project we will continue with CUDA 11.7

wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-ubuntu2204.pin
sudo mv cuda-ubuntu2204.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget https://developer.download.nvidia.com/compute/cuda/11.7.0/local_installers/cuda-repo-ubuntu2204-11-7-local_11.7.0-515.43.04-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu2204-11-7-local_11.7.0-515.43.04-1_amd64.deb
sudo cp /var/cuda-repo-ubuntu2204-11-7-local/cuda-*-keyring.gpg /usr/share/keyrings/
sudo apt-get update
sudo apt-get -y install cuda

4. Set CUDA env variables

   Open .bashrc file of system

   nano /home/$USER/.bashrc
   

   Inside there add the following: (replace cuda-11.7 with your version)

   export PATH="/usr/local/cuda-11.7/bin:$PATH"
   export LD_LIBRARY_PATH="/usr/local/cuda-11.7/lib64:$LD_LIBRARY_PATH"
   

   Then do the following to save and close the editor:

   On you keyboard press the following: 
   
   ctrl + o             --> save 
   enter or return key  --> accept changes
   ctrl + x             --> close editor
   

   Close the terminal and open a new one. Now check if cuda is properly setup or not

   run:

   nvcc --version
   

If previous steps are completed

5. Install requirements

pip install -r requirements.txt 

6. . Download Detectron 2

                           python -m pip install 'git+https://github.com/facebookresearch/detectron2.git'

7. Clone mmocr repo and download the repository.