FAQs
Yes, after you check out the Quickstart guide take a look at the Basic Image Recognition and Basic Image Segmentation tutorials. Also be sure to join our forums where you can ask questions and interact with our community of users.
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.
You can export/deploy your model as a TensorFlow model, FastAPI server, or Gradio. See Deploy View for more information.
PerceptiLabs v0.12.x uses TensorFlow 2.x. Prior versions use TensorFlow 1.x. See our change log for more information.
PerceptiLabs allows 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.
On some machines this can be caused by an incorrect mime-type for .js files on Windows 10. Check out this forum response for a work around.
No, PerceptiLabs is not yet compatible with M1 hardware.
Last modified 1yr ago