WarpFusion

Guides made by users:

youtu.be/HkM-7wxtkGA
youtube.com/watch?v=FxRTEILPCQQ
youtube.com/watch?v=wqXy_r_9qw8
youtube.com/watch?v=VMF7L0czyIg
youtube.com/watch?v=m8xaPnaooyg

1. Download and install git
2. Download and install miniconda

• You can skip these two steps and get a batch file here. Download it and run (doesn't matter which folder you run it from) It will download and install Git and Miniconda for you, you'll just need to accept all the incoming menus with default settings.

1. Create a folder for WarpFusion. It's recommended to have a general folder for WarpFusion and subfolders for each version. Like C:\code\WarpFusion\v5.27.5\
2. Download prepare_env_relative.bat and save it into your WarpFolder, C:\code\WarpFusion\v5.27.5\ in this example.
3. Run prepare_env_relative.bat. It will create a virtual python environment called "env" inside our folder and install dependencies, required to run the notebook and jupyter server for local colab.
4. Download run_relative.bat and save it into your WarpFolder, C:\code\WarpFusion\v5.27.5\ in this example.

1. Execute run_relative.bat. It will activate the environment and start jupyter server.
2. After the server has launched, go to https://colab.research.google.com
3. Click File -> Upload Notebook and upload the *.ipynb file
4. Click on the dropdown menu near "Connect" or "Reconnect" button on the topright part of the interface.
5. Select "connect to a local runtime" and paste the URL that will be generated below, which looks like "http://localhost:8888/?token=somenumbers"
6. Click "Connect" and CTRL+F9 to run all cells.

1. Create a folder for warp, for example d:\warp
2. Download Dockerfile and docker-compose.yml to d:\warp
3. Edit docker-compose.yml so that volumes point to your model, init_images, images_out folders that are outside of the warp folder. For example, d:\models\:/content/models will expose d:\models as /content/models to the notebook
4. Download and install docker from here - https://docs.docker.com/get-docker/
5. Run docker-compose up --build inside the warp folder.
6. Go to https://colab.research.google.com
7. Click File -> Upload Notebook and upload the *.ipynb file
8. Click on the dropdown menu near "Connect" or "Reconnect" button on the topright part of the interface.
9. Select "connect to a local runtime" and paste the token that was generated in your docker container, but leave the url as localhost. Should look like "http://localhost:8888/?token=somenumbers"
10. Click "Connect" and CTRL+F9 to run all cells.

1. Run docker-compose up inside the warp folder.
2. Go to https://colab.research.google.com
3. File -> open notebook -> open your previouslty uploaded notebook
4. Click on the dropdown menu near "Connect" or "Reconnect" button on the topright part of the interface.
5. Select "connect to a local runtime" and paste the token that was generated in your docker container, but leave the url as localhost. Should look like "http://localhost:8888/?token=somenumbers"
6. Click "Connect" and CTRL+F9 to run all cells.