Simple image classification models
pip install -r requierments.py
- Clone the codes; cd image-classification
- Config your parameters in the src/parameters.py module
- cd src
- Now you can run some of the following commands for running
- python LeNet-with-mnist.py (running LeNet over mnist dataset)
- python LeNet-with-rps.py (running LeNet over rps dataset)
- python MLP-with-mnist.py (running MLP over mnist dataset)
- mnist (it will be downloaded by keras)
- rps (download rps data ind extract it into a folder by the name data so the data will be as follow ./data/rps)
The following models are used.
INPUT => CONV => RELU => POOL => CONV => RELU => POOL => FC => RELU => FC
Contains two fully connected layers