Team Epoch's solution to the Pokémon Type Classification Competition.

Clone the repository and navigate to the project directory. Make sure Rye is installed on your machine and run:

rye sync

Alternatively, you can install the dependencies from requirements-dev.lock using the following command:

pip install -r requirements-dev.lock

This repository uses pre-commit for code quality checks and auto-formatting. To install the pre-commit hooks, run:

pre-commit install

To run the pre-commit checks on all files, run:

pre-commit run --all-files

Dataset is available in the data/raw folder. It contains the following files:

train_metadata.csv contains various details about each Pokémon, such as its name, type, species, height, weight, abilities, EV yield, catch rate, base friendship, base exp, growth rate.

CSV Descriptors:

• Pokemon: Name of the Pokémon.
• Type: One or dual type determining STAB (same-type attack bonus) and weaknesses or resistances to incoming attacks.
• Species: Identifies the Pokémon based on defining biological characteristics.
• Height: Height of each Pokémon.
• Weight: Weight of each Pokémon.
• Abilities: Special attributes aiding Pokémon in battle, introduced in Generation 3.
• EV Yield: Stats gained by defeating specific Pokémon.
• Catch Rate: Chances of catching a Pokémon with a Poké Ball.
• Base Friendship: Default friendship value when encountering a Pokémon.
• Base Exp: EXP yield when defeating a Pokémon at level 1.
• Growth Rate: Amount of EXP needed for leveling up.
• Egg Groups: Classification used in Pokémon breeding.
• Gender: Chance of Pokémon being male or female.
• Egg Cycles: Time unit for hatching Pokémon eggs.
• Base Stats (HP, Attack, Defense, Special Attack, Special Defense, Speed): Determine Pokémon strengths and weaknesses.

Training images are located in the data/raw/train_images folder. Test images are located in the data/raw/test_images folder.

These images are in-game sprites of the Pokémon, sources from all mainline Pokémon games.

For making a submission you are expected to run inference on the data/raw/test_images and create a CSV file with the following columns:

id, Bug, Dark, Dragon, Electric, Fairy, Fighting, Fire, Flying, Ghost, Grass, Ground, Ice, Normal, Poison, Psychic, Rock, Steel, Water

An example submission file is provided in submission/example_submission.csv.