FFNet-78S-Quantized
Semantic segmentation for automotive street scenes.
FFNet‑78S‑Quantized is a "fuss‑free network" that segments street scene images with per‑pixel classes like road, sidewalk, and pedestrian. Trained on the Cityscapes dataset.
Technical Details
Model checkpoint:ffnet78S_dBBB_cityscapes_state_dict_quarts
Input resolution:2048x1024
Number of parameters:27.5M
Model size:26.7 MB
Number of output classes:19
Applicable Scenarios
- Automotive
- Autonomous Driving
- Camera
Supported Mobile Form Factors
- Phone
- Tablet
Licenses
Source Model:BSD-3-CLAUSE
Deployable Model:AI Model Hub License
Tags
- quantized
- real-time
Supported Mobile Devices
- Samsung Galaxy S21
- Samsung Galaxy S21 Ultra
- Samsung Galaxy S21+
- 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 Tab S8
- Snapdragon 8 Elite QRD
- Xiaomi 12
- Xiaomi 12 Pro
Supported Mobile Chipsets
- Snapdragon® 8 Elite Mobile
- Snapdragon® 8 Gen 1 Mobile
- Snapdragon® 8 Gen 2 Mobile
- Snapdragon® 8 Gen 3 Mobile
- Snapdragon® 888 Mobile
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