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.


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*


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


  1. name: input , shape: [1x3x160x80] - An input image in the format [1xCxHxW], where

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

    The expected color order is BGR.


  1. 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.

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