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 Mobile chipset.
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View for other chipsetsTechnical Details
Model checkpoint:unet_carvana_scale1.0_epoch2
Input resolution:640x1280
Number of output classes:2 (foreground / background)
Number of parameters:31.0M
Model size (float):118 MB
Model size (w8a8):29.8 MB
Applicable Scenarios
- Autonomous Vehicles
- Medical Imaging
- Factory Quality Control
Supported Mobile Form Factors
- Phone
- Tablet
License
Model:GPL-3.0
Tags
- backbone
- real-time
Supported Mobile Devices
- Samsung Galaxy S21
- Samsung Galaxy S21 Ultra
- Samsung Galaxy S22 5G
- Samsung Galaxy S22 Ultra 5G
- Samsung Galaxy S22+ 5G
- Samsung Galaxy S23
- Samsung Galaxy S23 Ultra
- Samsung Galaxy S23+
- Samsung Galaxy S24
- Samsung Galaxy S24 Ultra
- Samsung Galaxy S24+
- Samsung Galaxy S25
- Samsung Galaxy S25 Ultra
- Samsung Galaxy S25+
- Samsung Galaxy Tab S8
- Snapdragon 7 Gen 4 QRD
- Snapdragon 8 Elite Gen 5 QRD
- Xiaomi 12
- Xiaomi 12 Pro
Supported Mobile Chipsets
- Snapdragon® 7 Gen 4 Mobile
- Snapdragon® 8 Elite Mobile
- Snapdragon® 8 Elite Gen 5 Mobile
- Snapdragon® 8 Gen 1 Mobile
- Snapdragon® 8 Gen 2 Mobile
- Snapdragon® 8 Gen 3 Mobile
- Snapdragon® 888 Mobile
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