Based on the AI Crowd Snake Species Identification Challenge
The Snake Species Identification Challenge or SSIC is a dataset containing 82601 images of snakes with varying backgrounds, crops and viewpoints. The goal of SSIC is to classify each snake contained in each image into one of 45 classes or snake species.
The goal of this project was to investigate the application of various computer vision approaches to this image classification task for the SSIC challenge. Additionally the project investigated why these methods perform differently.
Make sure to include submodules
git clone --recursive <repo_url>.git
Or if you have already cloned the repo, but are missing submodules
git submodule update --init
Run the following command to create a new conda env with the required packages:
conda env create -f environment.yml
To run jupyter notebooks you will need to add another kernel, do this as follows:
conda activate snakes
python -m ipykernel install --user --name=snakes
If you install more packages and need to add them to the .yml file, you can use this command:
conda env export > environment.yml
We trained a number of models, they are available via Google Drive
We included the report that we submitted.