person-attributes-recognition-crossroad-0238

Use Case and High-Level Description

This model presents a person attributes classification algorithm analysis scenario. The model consists of the Inception V3 backbone and a head. For an input image with a pedestrian the model returns 7 values that are probabilities of the corresponding 7 attributes.

Specification

Metric

Value

Pedestrian pose

Standing person

Occlusion coverage

<20%

Min object width

80 pixels

Supported attributes

is_male, has_bag, has_hat, has_longsleeves, has_longpants, has_longhair, has_coat_jacket

GFlops

1.034

MParams

21.797

Source framework

PyTorch*

Accuracy

Attribute

F1

is_male

0.80

has_bag

0.48

has_hat

0.42

has_longsleeves

0.17

has_longpants

0.75

has_longhair

0.77

has_coat_jacket

NA

Inputs

Image, name: input, shape: 1, 3, 160, 80 in the format 1, C, H, W, where:

  • C - number of channels

  • H - image height

  • W - image width

The expected color order is BGR.

Outputs

The net output is a blob named attributes with shape 1, 7 across seven attributes: [is_male, has_bag, has_hat, has_longsleeves, has_longpants, has_longhair, has_coat_jacket]. Value > 0.5 means that the corresponding attribute is present.

Demo usage

The model can be used in the following demos provided by the Open Model Zoo to show its capabilities: