Unet-Segmentation
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.
Not supported
This model is currently not supported on any Compute chipset.
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View for other chipsetsTechnical Details
Input resolution:640x1280
Model checkpoint:unet_carvana_scale1.0_epoch2
Model size (float):118 MB
Model size (w8a8):29.8 MB
Number of output classes:2 (foreground / background)
Number of parameters:31.0M
Applicable Scenarios
- Autonomous Vehicles
- Medical Imaging
- Factory Quality Control
License
Model:GPL-3.0
Tags
- backbone
- real-time
Supported Compute Devices
- Snapdragon X Elite CRD
- Snapdragon X Plus 8-Core CRD
- Snapdragon X2 Elite CRD
Supported Compute Chipsets
- Snapdragon® X Elite
- Snapdragon® X Plus 8-Core
- Snapdragon® X2 Elite
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