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

Link to performance table

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.