gender-detection-keras

by arunponnusamy

arunponnusamy / gender-detection-keras

Gender detection (from scratch) using deep learning with keras and cvlib.

140 Stars 53 Forks Last release: about 1 year ago (v0.1) MIT License 25 Commits 1 Releases

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Gender detection (from scratch) using deep learning with keras and cvlib

The keras model is created by training SmallerVGGNet from scratch on around 2200 face images (~1100 for each class). Face region is cropped by applying

face detection
using
cvlib
on the images gathered from Google Images. It acheived around 96% training accuracy and ~90% validation accuracy. (20% of the dataset is used for validation)

Update :

Checkout the gender detection functionality implemented in cvlib which can be accessed through a single function call

detect_gender()
.

Python packages

  • numpy
  • opencv-python
  • tensorflow
  • keras
  • requests
  • progressbar
  • cvlib

Install the required packages by executing the following command.

$ pip install -r requirements.txt

Note: Python 2.x is not supported

Make sure

pip
is linked to Python 3.x (
pip -V
will display this info).

If

pip
is linked to Python 2.7. Use
pip3
instead.
pip3
can be installed using the command
sudo apt-get install python3-pip

Using Python virtual environment is highly recommended.

Usage

image input

$ python detect_gender.py -i 

webcam

$ python detect_gender_webcam.py

When you run the script for the first time, it will download the pre-trained model from this link and place it under

pre-trained
directory in the current path.

(If

python
command invokes default Python 2.7, use
python3
instead)

Sample output :

Training

You can download the dataset I gathered from Google Images from this link and train the network from scratch on your own if you are interested. You can add more images and play with the hyper parameters to experiment different ideas.

Additional packages

  • scikit-learn
  • matplotlib

Install them by typing

pip install scikit-learn matplotlib

Usage

Start the training by running the command

$ python train.py -d 

(i.e) $ python train.py -d ~/Downloads/genderdatasetface/

Depending on the hardware configuration of your system, the execution time will vary. On CPU, training will be slow. After the training, the model file will be saved in the current path as

gender_detection.model
.

If you have an Nvidia GPU, then you can install

tensorflow-gpu
package. It will make things run a lot faster.

Help

If you are facing any difficulty, feel free to create a new issue or reach out on twitter @ponnusamy_arun .

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