Real-time face detection and emotion/gender classification using fer2013/imdb datasets with a keras CNN model and openCV.
Switch branches/tags
Nothing to show
Clone or download
Pull request Compare This branch is 4 commits ahead, 4 commits behind oarriaga:master.
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
datasets
images
src
trained_models
.gitignore
Dockerfile
LICENSE
README.md
REQUIREMENTS.txt
report.pdf

README.md

Face classification and detection from the B-IT-BOTS robotics team.

Real-time face detection and emotion/gender classification using fer2013/IMDB datasets with a keras CNN model and openCV.

  • IMDB gender classification test accuracy: 96%.
  • fer2013 emotion classification test accuracy: 66%.

For more information please consult the publication

Emotion/gender examples:

alt tag

Guided back-prop alt tag

Real-time demo:

B-IT-BOTS robotics team :) alt tag

Instructions

Run real-time emotion demo:

python3 video_emotion_color_demo.py

Run real-time guided back-prop demo:

python3 image_gradcam_demo.py

Make inference on single images:

python3 image_emotion_gender_demo.py <image_path>

e.g.

python3 image_emotion_gender_demo.py ../images/test_image.jpg

Running with Docker

With a few steps one can get its own face classification and detection running. Follow the commands below:

  • docker pull ekholabs/face-classifier
  • docker run -d -p 8084:8084 --name=face-classifier ekholabs/face-classifier
  • curl -v -F image=@[path_to_image] http://localhost:8084/classifyImage > image.png

To train previous/new models for emotion classification:

  • Download the fer2013.tar.gz file from here

  • Move the downloaded file to the datasets directory inside this repository.

  • Untar the file:

tar -xzf fer2013.tar

  • Run the train_emotion_classification.py file

python3 train_emotion_classifier.py

To train previous/new models for gender classification:

  • Download the imdb_crop.tar file from here (It's the 7GB button with the tittle Download faces only).

  • Move the downloaded file to the datasets directory inside this repository.

  • Untar the file:

tar -xfv imdb_crop.tar

  • Run the train_gender_classification.py file

python3 train_gender_classifier.py