HomeIoT ModelsFFNet-78S-LowRes

    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.

    Qualcomm® QCS8550
    QCS8550 (Proxy)
    10.7ms
    Inference Time
    1-3MB
    Memory Usage
    149NPU
    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 IoT Devices

    • QCS8550 (Proxy)

    Supported IoT Chipsets

    • Qualcomm® QCS8550