Real‑time segmentation optimized for mobile and edge.
UNet is a machine learning model that produces a segmentation mask for an image. The most basic use case will label each pixel in the image as being in the foreground or the background. More advanced usage will assign a class label to each pixel. This version of the model was trained on the data from Kaggle's Carvana Image Masking Challenge (see https://www.kaggle.com/c/carvana‑image‑masking‑challenge) and is used for vehicle segmentation.
Model checkpoint:unet_carvana_scale1.0_epoch2
Input resolution:224x224
Number of output classes:2 (foreground / background)
Number of parameters:31.0M
Model size (float):118 MB
Model size (w8a8):29.8 MB
Autonomous Vehicles
Medical Imaging
Factory Quality Control
Source Model: GPL-3.0
Deployable Model: GPL-3.0