FFNet-40S-Quantized
Semantic segmentation for automotive street scenes.
FFNet‑40S‑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:ffnet40S_dBBB_cityscapes_state_dict_quarts
Input resolution:2048x1024
Number of parameters:13.9M
Model size:13.5 MB
Number of output classes:19
Applicable Scenarios
- Automotive
- Autonomous Driving
- Camera
Supported Form Factors
- Phone
- Tablet
Licenses
Source Model:BSD-3-CLAUSE
Deployable Model:AI Model Hub License
Tags
- quantized
- real-time
Supported Devices
- QCS6490 (Proxy)
- QCS8250 (Proxy)
- QCS8550 (Proxy)
- RB3 Gen 2 (Proxy)
- RB5 (Proxy)
- SA7255P ADP
- SA8255 (Proxy)
- SA8295P ADP
- SA8650 (Proxy)
- SA8775P ADP
- 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
- Snapdragon X Elite CRD
- Snapdragon X Plus 8-Core CRD
- Xiaomi 12
- Xiaomi 12 Pro
Supported Chipsets
- Qualcomm® QCS6490 (Proxy)
- Qualcomm® QCS8250 (Proxy)
- Qualcomm® QCS8550 (Proxy)
- Qualcomm® SA7255P
- Qualcomm® SA8255P (Proxy)
- Qualcomm® SA8295P
- Qualcomm® SA8650P (Proxy)
- Qualcomm® SA8775P
- Snapdragon® 8 Elite Mobile
- Snapdragon® 8 Gen 1 Mobile
- Snapdragon® 8 Gen 2 Mobile
- Snapdragon® 8 Gen 3 Mobile
- Snapdragon® 888 Mobile
- Snapdragon® X Elite
- Snapdragon® X Plus 8-Core
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