Real-world Image Recognition for Multiple Human Attributes

This project is participating in NUS SoC 13th STePS. For more information, see here.

Information about the repository structure:

Project Report
Gender Classifier for the LFW dataset
- Implemented using PyTorch (https://pytorch.org) library.
- An older model can be found at here.
Long/short-sleeves Classifier for the WIDER dataset
- Implemented using TensorFlow (https://www.tensorflow.org) library.

Notes regarding the WIDER dataset

See here.

See here.

Sometimes, it can be quite troublesome to install tensorflow on your machine. If so, you can use Docker to release the pain.
Pull the Docker image by docker pull tensorflow/tensorflow:latest-py3
Let’s first create a container by docker run -it --name tensorflow -p 0.0.0.0:7007:6006 -v $PWD:/CS3244 tensorflow/tensorflow:latest-py3 bash.
- it is always used for interactive command, like a shell.
- rm will delete the container automatically after exit.
- v and w specifies how the directory sharing is done.
- p will do port forwarding (for tensorboard later). Use tensorboard --logdir ./ --host 0.0.0.0 to run tensorboard. Then you can see the board at http://localhost:7007.
From then on, you can start the container by docker start tensorflow. Then, you can login by docker exec -it tensorflow bash. To stop the container, run docker stop tensorflow.