V-Ray Standalone is a photorealistic rendering engine proposed by Chaos Group.
V-Ray Standalone versions adapted on Qarnot:
|V-Ray Standalone versions||Qarnot profiles|
|5, Update 2.2||vray-standalone-52002|
|5, Update 1.3||vray-standalone-51003|
|5, Hotfix 2||vray-standalone-50005|
If you are interested in another version, please send us an email at email@example.com.
Starting a render
Before starting a render, data needs to be uploaded to a bucket named vray-in that will be used for the render.
It can be done with different methods:
- Using a web interface, no code required:
Create the bucket in Render’s bucket section and upload your data using the “Upload” button.
- Using a S3 tool to download directly from your computer a large amount of data, no code required:
Use one of the S3 tools presented here.
- Using Python functions to allow integration to an existing pipeline:
Use the Python SDK functions in the render script (add_directory, sync_directory, …).
Note: using one of the tools presented in S3 Data methods is strongly recommended, especially for large volumes of data.
Using the web interface
The 3D-tailored web interface Render can be used to start V-Ray Standalone renders.
A video tutorial is available here (the video is about Blender renders, but the principle is the same for V-Ray renders).
Using the Python SDK
Before starting a render with the Python SDK, a few steps are required:
Be sure you have copied your authentication token in the script (instead of
<<<MY_SECRET_TOKEN>>>) to be able to launch the task on Qarnot.
To launch this script, simply copy the following code in a Python script and execute
python3 vray-standalone.py in your terminal.
Note: when one of the previous task constants is not filled, it will take the value contained by default in the file.
Monitoring and downloading results
At any given time, you can monitor the status of your task on the general web interface Console or on our 3D-tailored web interface Render.
The results will be stored in the vray-out bucket and can be retrieved with three methods:
- the download button in the Bucket section
- the download_results function from the Python SDK
- one of the S3 compatible tools for managing your data.
That’s it! If you have any questions, please contact firstname.lastname@example.org and we will help you with pleasure!