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vehicle-attributes-recognition-barrier-0039.md

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vehicle-attributes-recognition-barrier-0039

Use Case and High-Level Description

This model presents a vehicle attributes classification algorithm for a traffic analysis scenario.

Example

Specification

Metric Value
Car pose Front facing cars
Occlusion coverage <50%
Min object width 72 pixels
Supported colors White, gray, yellow, red, green, blue, black
Supported types Car, bus, truck, van
GFlops 0.126
MParams 0.626
Source framework Caffe*

Accuracy - Confusion Matrix

Performance

Inputs

  1. name: "input" , shape: [1x3x72x72] - An input image in following format [1xCxHxW], where:

    • C - number of channels
    • H - image height
    • W - image width.

Expected color order - BGR.

Outputs

  1. name: "color", shape: [1, 7, 1, 1] - Softmax output across seven color classes [white, gray, yellow, red, green, blue, black]
  2. name: "type", shape: [1, 4, 1, 1] - Softmax output across four type classes [car, bus, truck, van]

Legal Information

[*] Other names and brands may be claimed as the property of others.