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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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