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
.