Gender Classification - Algorithm by deeplearning

deeplearning / GenderClassification / 2.0.0

README.md

1. Introduction

This algorithm classifies gender for each person in any given image. Currently it only supports two genders. (male & female)

Input:

(Required) Image Data API Url, Web (http/https) Url, binary image or a base64 encoded image.

Output:

Gender and bounding-box information of each person in the given image

Note: The first call to this algorithm will take a bit longer than sequential calls to due algorithm initialization. All following calls will be significantly faster.

2. Examples

Example 1.

Parameter 1: Data API Url

{
    "image": "data://deeplearning/example_data/m_ali.jpg"
}

Output

{
  "results": [
    {
      "bbox": {
        "bottom": 2908,
        "left": 700,
        "right": 2356,
        "top": 1252
      },
      "gender": [
        {"confidence": 0.997405171394348, "gender": "Male"},
        {"confidence": 0.0025948521215468645, "gender": "Female"}
      ],
      "person": 0
    }
  ]
}

Example 2.

Parameter 1: HTTP Url

{
    "image": "https://s3.amazonaws.com/algorithmia-assets/algo_desc_images/deeplearning_GenderClassification/m_ali.jpg"
}

Output:

{
  "results": [
    {
      "bbox": {
        "bottom": 2908,
        "left": 700,
        "right": 2356,
        "top": 1252
      },
      "gender": [
        {"confidence": 0.997405171394348, "gender": "Male"},
        {"confidence": 0.0025948521215468645, "gender": "Female"}
      ],
      "person": 0
    }
  ]
}

Example 3.

Parameter 1: Base64 image

{
    "image": "data:image/png;base64....",
}

Output;

{
  "results": [
    {
      "bbox": {
        "bottom": 2908,
        "left": 700,
        "right": 2356,
        "top": 1252
      },
      "gender": [
        {"confidence": 0.997405171394348, "gender": "Male"},
        {"confidence": 0.0025948521215468645, "gender": "Female"}
      ],
      "person": 0
    }
  ]
}

3. Credits

for more information, please refer to: http://www.openu.ac.il/home/hassner/projects/cnn_agegender/Gil Levi and Tal Hassner, Age and Gender Classification using Convolutional Neural Networks, IEEE Workshop on Analysis and Modeling of Faces and Gestures (AMFG), at the IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Boston, June 2015

dlib/FaceDetection

was used to detect faces in given images. Demo is was taken from:

https://en.wikipedia.org/wiki/Main_Page#/media/File:Muhammad_Ali_NYWTS.jpg

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