FAQs
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PerceptiLabs specializes in computer vision applications, but is also able to build models based on data in a CSV format, such as text analysis, regression, etc.
PerceptiLabs supports Nvidia GPUs. Note that since Mac use ATI GPUs, GPU-accelerated machine learning is not supported on that platform.
Currently you can export your model as a TensorFlow model. When you export your model, you can just deploy it to a TensorFlow server, if you have that set up. See this for an example of how to run an exported model.
PerceptiLabs v0.12.x uses TensorFlow 2.x. Prior versions use TensorFlow 1.x. See our for more information.
PerceptiLabsallows you to build models using deep learning (neural networks) like Convolution Neural Networks, as well as simple methods like linear regression.
Your data does not go to any server in the desktop version. The data we collect (e.g. error logs and similar) is used to fix bugs and improve the user experience.
This can happen if another application or service that is already running on your local machine is using port 5000, 8000, 8011, and/or 8080. Be sure to first close that application or service before running PerceptiLabs.
If you've just installed PerceptiLabs on Windows Subsystem for Linux (WSL) you must first stop and restart WSL before PerceptiLabs will run correctly.
The GPU version of PerceptiLabs (perceptilabs-gpu package) does not work with WSL.
PerceptiLabs' reads in which map data (e.g., image files) to labels.
On some machines this can be caused by an incorrect mime-type for .js files on Windows 10. Check out this for a work around.