https://github.com/abars/YoloKerasFaceDetection

Face Detection and Gender and Age Classification using Keras
https://github.com/abars/YoloKerasFaceDetection

Last synced: 3 months ago
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Face Detection and Gender and Age Classification using Keras

• Host: GitHub
• URL: https://github.com/abars/YoloKerasFaceDetection
• Owner: abars
• License: mit
• Created: 2017-12-30T04:48:02.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2019-02-25T23:31:46.000Z (almost 6 years ago)
• Last Synced: 2024-02-11T22:47:10.097Z (about 1 year ago)
• Language: Python
• Homepage:
• Size: 6.17 MB
• Stars: 203
• Watchers: 14
• Forks: 79
• Open Issues: 9
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-face-detection-and-recognition - abars/YoloKerasFaceDetection
• awesome-yolo-object-detection - abars/YoloKerasFaceDetection
• awesome-yolo-object-detection - abars/YoloKerasFaceDetection

README

        
# Yolo Keras Face Detection

Implement Face detection, and Age and Gender Classification using Keras.



(image from wider face dataset)

# Overview

## Functions

Face Detection

Age and Gender Classification

## Requirements

Keras2 (Tensorflow backend)

OpenCV

Python 2.7

Darknet (for Training)

# Test

## Download Pretrained-Model

`python download_model.py`

## Predict from Camera Image

Here is a run using pretrained model .

`python agegender_demo.py`

# Train

## Install

### Keras

`pip install keras`

### Darknet

Download Darknet and put in the same folder.

https://github.com/pjreddie/darknet

## Face Detection (FDDB)

### Create dataset

Download fddb dataset (FDDB-folds and originalPics folder) and put in the dataset/fddb folder.

http://vis-www.cs.umass.edu/fddb/

Create dataset/fddb/FDDB-folds/annotations_darknet folder for darknet.

`python annotation_fddb_darknet.py`

Preview converted annotations.

`python annotation_view.py fddb`

[![FDDB dataset overview](https://img.youtube.com/vi/KGeY_PFhRYA/0.jpg)](https://www.youtube.com/watch?v=KGeY_PFhRYA&feature=youtu.be)

### Train using Darknet

Here is a training using YoloV2.

`cd darknet`

`./darknet detector train data/face-one-class.data cfg/yolov2-tiny-train-one-class.cfg`

### Test using Darknet

Here is a test.

`./darknet detector demo data/face-one-class.data cfg/yolov2-tiny-train-one-class.cfg backup-face/yolov2-tiny-train-one-class_32600.weights -c 0`

### Training Result



### Convert to Keras Model

Download YAD2K

https://github.com/allanzelener/YAD2K

This is a convert script.

`python3 yad2k.py yolov2-tiny-train-one-class.cfg yolov2-tiny-train-one-class_32600.weights yolov2_tiny-face.h5`

This is a converted model.

## Age and Gender classification

### Create Dataset

#### Use AdienceBenchmarkOfUnfilteredFacesForGenderAndAgeClassification dataset

Download AdienceBenchmarkOfUnfilteredFacesForGenderAndAgeClassification dataset and put in the dataset/adience folder.

https://www.openu.ac.il/home/hassner/Adience/data.html#agegender

Create dataset/agegender_adience/annotations for keras.

`python annotation_agegender_adience_keras.py`

#### Use IMDB-WIKI dataset

Download IMDB-WIKI dataset (Download faces only 7gb) and put in the dataset/imdb_crop folder.

https://data.vision.ee.ethz.ch/cvl/rrothe/imdb-wiki/

Create dataset/agegender_imdb/annotations for keras.

`python annotation_imdb_keras.py`

#### Use UTKFace dataset

Download UTKFace dataset and put in the dataset/imdb_crop folder.

https://susanqq.github.io/UTKFace/

Create dataset/agegender_utk/annotations for keras.

`python annotation_utkface_keras.py`

#### Use AppaReal dataset

Download AppaReal dataset and put in the dataset/appa-real-release folder.

http://chalearnlap.cvc.uab.es/dataset/26/description/

Create dataset/agegender_appareal/annotations for keras.

`python annotation_appareal_keras.py`

### Train using Keras

Install keras-squeezenet

https://github.com/rcmalli/keras-squeezenet

Run classifier task using keras.

`python agegender_train.py age101 squeezenet imdb`

`python agegender_train.py gender squeezenet imdb`

### Test using Keras

Test classifier task using keras.

`python agegender_predict.py age101 squeezenet imdb`

`python agegender_predict.py gender squeezenet imdb`

### Training result

Age101 (IMDB) (EPOCHS=100)





Gender (IMDB) (EPOCHS=25)





# Related Work