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FFNet-78S-LowRes

Semantic segmentation for automotive street scenes.

FFNet-78S-LowRes is a "fuss-free network" that segments street scene images with per-pixel classes like road, sidewalk, and pedestrian. Trained on the Cityscapes dataset.

Snapdragon® X Elite
8.77ms
Inference Time
29MB
Memory Usage
238NPU
Layers

Technical Details

Model checkpoint:ffnet78S_BCC_cityscapes_state_dict_quarts_pre_down
Input resolution:1024x512
Number of parameters:26.8M
Model size:102 MB

Applicable Scenarios

  • Automotive
  • Autonomous Driving
  • Camera

Licenses

Source Model:BSD-3-CLAUSE
Deployable Model:AI Model Hub License

Tags

  • real-time
    A “real-time” model can typically achieve 5-60 predictions per second. This translates to latency ranging up to 200 ms per prediction.

Supported Compute Chipsets

  • Snapdragon® X Elite